distances_lpop.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9a7a4f19-52fb-4090-9d7f-921dadef5c77",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<frozen importlib._bootstrap>:219: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "#!pip install pivottablejs\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c813f040-8432-4c85-a57b-4c4a7b5f7040",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop = pd.read_stata('ARG_2021_LAPOP_AmericasBarometer_v1.2_w.dta',convert_categoricals=False)\n",
    "gpt = pd.read_csv('respuestas_gpt35_turbo')\n",
    "cohere = pd.read_csv('respuestas_cohere.csv')\n",
    "bard = pd.read_csv('respuestas_bard.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c616071b-8c5e-4828-9ce8-967c4afe0b6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Crea un StataReader para leer los metadatos\n",
    "reader = pd.io.stata.StataReader('ARG_2021_LAPOP_AmericasBarometer_v1.2_w.dta')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b3a2c30a-e78e-4501-8459-7250c4d1076f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open(r\"respuestas.pickle\", \"rb\") as input_file:\n",
    "    respuestas = pickle.load(input_file)\n",
    "with open(r\"preguntas_seleccionadas.pickle\", \"rb\") as input_file:\n",
    "    preguntas_seleccionadas = pickle.load(input_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d0f9a713-fb1e-47ab-bd13-21b07296b6c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop = lpop.drop('a4', axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9b2b5692-d972-48f8-8b9d-d730e6a5b4e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop = lpop.drop('DST1BN'.lower(), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "04336088-888b-4c35-b142-78aedc2f5dad",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop = lpop.drop('DRK1C'.lower(), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b8723882-68a2-4620-8115-70001a382898",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(30.0, 17, 1.7647058823529411)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import math\n",
    "def calculate_distance(responde,llm):    \n",
    "    result = 0\n",
    "    num_pregs = 0\n",
    "    for pregunta in list(preguntas_seleccionadas.keys()):\n",
    "        if((pregunta.lower() in responde.keys()) and (not math.isnan(responde[pregunta.lower()])) and (pregunta in list(llm['Pregunta'])) \n",
    "           and(llm[llm['Pregunta']== pregunta]['Respuesta'].values[0] < 10) ):\n",
    "            \n",
    "            result = result + (abs(responde[pregunta.lower()]-llm[llm['Pregunta']== pregunta]['Respuesta'].values[0]))\n",
    "            num_pregs = num_pregs + 1\n",
    "    if(num_pregs == 0):\n",
    "        result = -1\n",
    "        norm_result = -1\n",
    "    else:\n",
    "        norm_result = result/num_pregs\n",
    "    \n",
    "    return(result, num_pregs, norm_result)\n",
    "calculate_distance(lpop.loc[0],bard)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "7d6cf779-633a-42f1-a6c7-c1d8f81741e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop['gpt_results'] = lpop.apply(lambda x: calculate_distance(x, gpt), axis=1)\n",
    "lpop[['gpt_distance', 'gpt_num_preg','gpt_distance_norm']] = pd.DataFrame(lpop['gpt_results'].tolist(), index=lpop.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "b3bf7b3b-344f-4b65-aabe-feee5e86d19e",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop['bard_results'] = lpop.apply(lambda x: calculate_distance(x, bard), axis=1)\n",
    "lpop[['bard_distance', 'bard_num_preg','bard_distance_norm']] = pd.DataFrame(lpop['bard_results'].tolist(), index=lpop.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5fcef87d-88e1-4e09-bc0e-a6a3f77ca5e2",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop['cohere_results'] = lpop.apply(lambda x: calculate_distance(x, cohere), axis=1)\n",
    "lpop[['cohere_distance', 'cohere_num_preg', 'cohere_distance_norm']] = pd.DataFrame(lpop['cohere_results'].tolist(), index=lpop.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9f7d9195-2acf-4d7e-8d45-243f86157f2a",
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'etid'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "Input \u001b[1;32mIn [13]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[0m \u001b[43mpreguntas_seleccionadas\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43metid\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n",
      "\u001b[1;31mKeyError\u001b[0m: 'etid'"
     ]
    }
   ],
   "source": [
    "preguntas_seleccionadas['etid']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "da5f6c35-0277-4b5e-9a48-f789e9828f9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1: 'Una ciudad',\n",
       " 2: 'En la periferia o alrededores de una ciudad',\n",
       " 3: 'En un pueblo/poblado cercano a una zona/área rural',\n",
       " 4: 'En un área/zona rural',\n",
       " 2147483622: 'No sabe',\n",
       " 2147483623: 'No responde'}"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reader.value_labels()['ur1new_esp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "56b71c18-8b7e-4491-a958-aab5eb38e53d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "40    47\n",
       "32    42\n",
       "47    41\n",
       "30    38\n",
       "50    37\n",
       "      ..\n",
       "80     3\n",
       "69     3\n",
       "85     2\n",
       "79     2\n",
       "83     1\n",
       "Name: q2, Length: 66, dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lpop_distances['q2'.lower()].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "96cc3b4a-f500-417e-9f66-d818d135f1ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'La democracia es mejor que cualquier otra forma de gobierno'"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " reader.variable_labels()['ing4']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "e9ebd856-f004-44d6-bf39-b06d57627cb9",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop['q10newt'] = lpop['q10newt'].replace(171, 1)\n",
    "lpop['q10newt'] = lpop['q10newt'].replace(172, 2)\n",
    "lpop['q10newt'] = lpop['q10newt'].replace(173, 3)\n",
    "lpop['q10newt'] = lpop['q10newt'].replace(174, 4)\n",
    "lpop['q10newt'] = lpop['q10newt'].replace(175, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "dfbf88e1-f315-4444-8bb6-4f7782b14160",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop[(lpop['bard_num_preg'] >5)&(lpop['gpt_num_preg'] >5)&(lpop['cohere_num_preg'] >5)].to_csv('lpop_distances.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cfb1b492-4bc5-46c6-ab87-7fa5defdf5e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop_distances = lpop[lpop['bard_num_preg'] >5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "71d2e3ad-6e8b-4b9c-9840-18d73603c2c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "pregs = [p.lower() for p in preguntas_seleccionadas.keys() if p.lower() in lpop.columns]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a7458f24-b4e8-4d50-9102-ae25d569c1d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Series([], Name: q10newt, dtype: int64)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lpop_distances['q10newt'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "2563dc86-6a43-4396-90a7-865826834981",
   "metadata": {},
   "outputs": [],
   "source": [
    "lpop_distances = lpop[(lpop['bard_num_preg'] >5)&(lpop['gpt_num_preg'] >5)&(lpop['cohere_num_preg'] >5)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "2e2e1f3e-be3a-4180-904b-44a7c3240cd6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(dpi=150)\n",
    "\n",
    "sns.kdeplot(\n",
    "   lpop_distances['bard_distance_norm'], label=\"Bard\"\n",
    ")\n",
    "sns.kdeplot(\n",
    "   lpop_distances['gpt_distance_norm'], label=\"GPT\"\n",
    ")\n",
    "sns.kdeplot(\n",
    "   lpop_distances['cohere_distance_norm'], label=\"Cohere\"\n",
    ")\n",
    "plt.title(\"Distribución distancia según LLM\")\n",
    "plt.xlabel(\"Distancia\")\n",
    "plt.yticks([], [])\n",
    "plt.legend(loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "54b9840e-2d52-4154-9290-a138faf036b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 960x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "lpop_adulto = lpop_distances[lpop_distances['q2']>40]\n",
    "lpop_joven = lpop_distances[lpop_distances['q2']<25]\n",
    "plt.figure(dpi=150)\n",
    "\n",
    "sns.kdeplot(\n",
    "   lpop_adulto['bard_distance_norm'], label=\"Adultos\"\n",
    ")\n",
    "sns.kdeplot(\n",
    "   lpop_joven['bard_distance_norm'], label=\"Jóvenes\"\n",
    ")\n",
    "plt.title(\"Distribución Distancia de los jovenes\")\n",
    "plt.xlabel(\"Distancia\")\n",
    "plt.yticks([], [])\n",
    "plt.legend(loc='upper right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "eec2896c-2ea9-49d2-bc50-69e3fe8df0ba",
   "metadata": {},
   "outputs": [],
   "source": [
    "pregs = [p.lower() for p in preguntas_seleccionadas.keys() if p.lower() in lpop.columns]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "075f9541-8955-49f5-a98e-93fd81efc081",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>jc13</th>\n",
       "      <th>jc13covid</th>\n",
       "      <th>jc15a</th>\n",
       "      <th>jccov1</th>\n",
       "      <th>jccov2</th>\n",
       "      <th>countfair1</th>\n",
       "      <th>countfair2</th>\n",
       "      <th>countfair3</th>\n",
       "      <th>countfair4</th>\n",
       "      <th>wvsi2</th>\n",
       "      <th>wvsi3</th>\n",
       "      <th>chm1bn</th>\n",
       "      <th>chm2bn</th>\n",
       "      <th>cses6n</th>\n",
       "      <th>b2</th>\n",
       "      <th>b3</th>\n",
       "      <th>b6</th>\n",
       "      <th>dst1bn</th>\n",
       "      <th>drk1c</th>\n",
       "      <th>m1</th>\n",
       "      <th>ing4</th>\n",
       "      <th>anestg</th>\n",
       "      <th>mil10a</th>\n",
       "      <th>mil10e</th>\n",
       "      <th>ccch1</th>\n",
       "      <th>ccus1</th>\n",
       "      <th>ccch3</th>\n",
       "      <th>ccus3</th>\n",
       "      <th>ctaware</th>\n",
       "      <th>ctspecific1</th>\n",
       "      <th>ctdiffuse1</th>\n",
       "      <th>ctdiffuse2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2714</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2278</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2113</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>826</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2773</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2912</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>286</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1850</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1356</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>792</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2827</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1429</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2330</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1960</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>355</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>855</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1819</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2530</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>315</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1301</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>446</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2265</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2967</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2152</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1588</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2896</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2583</th>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1099</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1500</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1381</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2646</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1511</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2521</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1140</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2321</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>955</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2361</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2116</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2159</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>542</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2478</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2624</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1360</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2418</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2280</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2825</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>868</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2744</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>474</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1369</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1418</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>5.0</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>7.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1060</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>5.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1280</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1437</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>600</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1577</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1470</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1504</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>313</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2928</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>456</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1032</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>884</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1283</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1753</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>742</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1201</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>4.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2442</th>\n",
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       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1463</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1326</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1388</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2075</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1693</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1275</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>878</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1967</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2107</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>885</th>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>890</th>\n",
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       "      <td>1.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1660</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1203</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>678</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>377</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1076</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2977</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2105</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2204</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>669</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>684</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>392</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1362</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2070</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1615</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1359</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1953</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>960</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1581</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2659</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>852</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>701</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1880</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2200</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>534</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>545</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2639</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2084</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>3.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1565</th>\n",
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       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1725</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1582</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2209</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2156</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2086</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2048</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1260</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1156</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1145</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1448</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>436</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>373</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1894</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2399</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1937</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1050</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1762</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2722</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2974</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1963</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1897</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1630</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>6.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>645</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>692</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2174</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2600</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>312</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>549</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2115</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2067</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>467</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1530</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2424</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2486</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2666</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1444</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2139</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2314</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2284</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1321</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>381</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>687</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2943</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1008</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>410</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1783</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1550</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2654</th>\n",
       "      <td>1.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1025</th>\n",
       "      <td>1.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2194</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2079</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2026</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3007</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1480</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1607</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>809</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1129</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1899</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1009</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>859</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>800</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>652</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2565</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2888</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2781</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>939</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>402</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1747</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1635</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2130</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1750</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>747</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1745</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2133</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1067</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2626</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1048</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>896</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2886</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2365</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1118</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1497</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1105</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>937</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1018</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>767</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1643</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>856</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>754</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1181</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2354</th>\n",
       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2474</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1481</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2553</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2406</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1608</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1964</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>788</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1933</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2466</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>473</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2903</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>450</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1425</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2905</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>956</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1835</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1822</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1685</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2417</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2241</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1631</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1135</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>526</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2657</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2201</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>411</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2078</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1036</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>916</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2117</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1417</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2109</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1456</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1065</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3009</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2132</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>4.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2111</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>793</th>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>4.0</td>\n",
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       "      <td>7.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>917</th>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2382</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2931</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2170</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2632</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1641</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1365</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2838</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>774</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2662</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1399</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2206</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
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       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1694</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1252</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>961</th>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>1.0</td>\n",
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       "      <td>3.0</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1546</th>\n",
       "      <td>2.0</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2788</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2791</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1597</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>823</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>617</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>619</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1194</th>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2177</th>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      jc13  jc13covid  jc15a  jccov1  jccov2  countfair1  countfair2  \\\n",
       "2714   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2278   2.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "2113   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "826    2.0        NaN    2.0     2.0     NaN         2.0         2.0   \n",
       "2773   2.0        NaN    2.0     2.0     NaN         3.0         2.0   \n",
       "2912   2.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "286    NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "1850   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "1356   2.0        NaN    2.0     2.0     NaN         1.0         2.0   \n",
       "792    NaN        2.0    2.0     NaN     2.0         2.0         NaN   \n",
       "2827   2.0        NaN    2.0     2.0     NaN         2.0         1.0   \n",
       "988    NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1429   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "2330   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "1960   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "355    2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "855    NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1819   2.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "2530   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "315    2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "1301   2.0        NaN    2.0     NaN     2.0         2.0         2.0   \n",
       "446    2.0        NaN    2.0     NaN     NaN         NaN         NaN   \n",
       "2265   NaN        2.0    2.0     1.0     NaN         2.0         2.0   \n",
       "2967   2.0        NaN    NaN     1.0     NaN         1.0         2.0   \n",
       "2152   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "1588   2.0        NaN    2.0     NaN     2.0         1.0         2.0   \n",
       "2896   2.0        NaN    2.0     2.0     NaN         2.0         2.0   \n",
       "48     NaN        2.0    2.0     NaN     2.0         2.0         1.0   \n",
       "2583   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "468    2.0        NaN    2.0     NaN     2.0         2.0         1.0   \n",
       "1099   NaN        2.0    2.0     1.0     NaN         NaN         NaN   \n",
       "1500   NaN        2.0    2.0     2.0     NaN         1.0         2.0   \n",
       "1381   NaN        2.0    1.0     1.0     NaN         1.0         2.0   \n",
       "2646   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "1511   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2521   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "8      NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1140   2.0        NaN    NaN     2.0     NaN         NaN         NaN   \n",
       "2321   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "220    2.0        NaN    2.0     NaN     2.0         1.0         3.0   \n",
       "955    NaN        2.0    2.0     NaN     2.0         NaN         2.0   \n",
       "2361   2.0        NaN    2.0     2.0     NaN         1.0         2.0   \n",
       "2116   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2159   2.0        NaN    2.0     NaN     2.0         1.0         1.0   \n",
       "542    NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2478   NaN        2.0    2.0     2.0     NaN         2.0         2.0   \n",
       "2624   NaN        2.0    2.0     2.0     NaN         2.0         1.0   \n",
       "2000   1.0        NaN    1.0     NaN     2.0         2.0         2.0   \n",
       "1360   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "2418   2.0        NaN    2.0     NaN     2.0         1.0         2.0   \n",
       "118    NaN        2.0    2.0     NaN     2.0         3.0         2.0   \n",
       "2280   NaN        2.0    2.0     1.0     NaN         2.0         2.0   \n",
       "2825   NaN        2.0    2.0     2.0     NaN         2.0         3.0   \n",
       "868    NaN        2.0    2.0     1.0     NaN         2.0         2.0   \n",
       "2744   NaN        2.0    2.0     NaN     2.0         1.0         3.0   \n",
       "474    2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1369   2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "1418   NaN        2.0    2.0     NaN     1.0         NaN         NaN   \n",
       "1060   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1280   NaN        1.0    2.0     NaN     2.0         2.0         1.0   \n",
       "1437   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "600    NaN        2.0    2.0     2.0     NaN         2.0         2.0   \n",
       "1577   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1470   NaN        2.0    2.0     NaN     1.0         2.0         1.0   \n",
       "1504   NaN        2.0    2.0     NaN     2.0         2.0         NaN   \n",
       "313    2.0        NaN    2.0     NaN     2.0         2.0         3.0   \n",
       "2928   NaN        2.0    2.0     1.0     NaN         2.0         2.0   \n",
       "456    NaN        2.0    2.0     NaN     2.0         1.0         2.0   \n",
       "1032   NaN        2.0    1.0     1.0     NaN         NaN         NaN   \n",
       "884    NaN        2.0    2.0     NaN     2.0         2.0         3.0   \n",
       "1283   2.0        NaN    2.0     2.0     NaN         2.0         2.0   \n",
       "1753   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "742    2.0        NaN    2.0     NaN     1.0         2.0         2.0   \n",
       "1201   NaN        2.0    2.0     2.0     NaN         NaN         3.0   \n",
       "2442   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "480    1.0        NaN    1.0     NaN     2.0         2.0         2.0   \n",
       "1463   2.0        NaN    2.0     NaN     2.0         1.0         3.0   \n",
       "231    2.0        NaN    2.0     NaN     1.0         NaN         NaN   \n",
       "1326   2.0        NaN    2.0     NaN     1.0         NaN         NaN   \n",
       "1388   NaN        1.0    NaN     NaN     2.0         2.0         2.0   \n",
       "2075   1.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "502    2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "1693   2.0        NaN    2.0     2.0     NaN         2.0         1.0   \n",
       "1275   2.0        NaN    2.0     NaN     NaN         NaN         NaN   \n",
       "878    NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1967   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "2107   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "885    NaN        2.0    2.0     NaN     2.0         1.0         3.0   \n",
       "890    2.0        NaN    1.0     2.0     NaN         NaN         NaN   \n",
       "1660   2.0        NaN    2.0     NaN     2.0         3.0         3.0   \n",
       "1203   2.0        NaN    2.0     1.0     NaN         2.0         3.0   \n",
       "519    NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "2002   2.0        NaN    2.0     NaN     2.0         2.0         1.0   \n",
       "678    NaN        2.0    2.0     2.0     NaN         1.0         2.0   \n",
       "377    2.0        NaN    2.0     NaN     2.0         2.0         3.0   \n",
       "1076   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2977   NaN        2.0    2.0     1.0     NaN         1.0         3.0   \n",
       "2105   NaN        2.0    2.0     2.0     NaN         2.0         2.0   \n",
       "2204   NaN        2.0    2.0     2.0     NaN         2.0         2.0   \n",
       "669    2.0        NaN    2.0     NaN     2.0         2.0         3.0   \n",
       "684    2.0        NaN    2.0     2.0     NaN         2.0         2.0   \n",
       "392    NaN        2.0    1.0     NaN     1.0         2.0         2.0   \n",
       "1362   NaN        2.0    2.0     2.0     NaN         1.0         3.0   \n",
       "752    2.0        NaN    2.0     2.0     NaN         1.0         2.0   \n",
       "2070   2.0        NaN    2.0     NaN     1.0         1.0         3.0   \n",
       "1615   NaN        NaN    NaN     NaN     NaN         NaN         NaN   \n",
       "1359   NaN        2.0    2.0     NaN     NaN         NaN         NaN   \n",
       "1953   NaN        2.0    2.0     NaN     2.0         2.0         NaN   \n",
       "960    NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "1581   1.0        NaN    2.0     1.0     NaN         2.0         NaN   \n",
       "2659   NaN        2.0    NaN     2.0     NaN         NaN         NaN   \n",
       "852    NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "701    2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1880   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "147    2.0        NaN    2.0     NaN     2.0         2.0         2.0   \n",
       "2200   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "534    1.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "545    2.0        NaN    2.0     NaN     2.0         1.0         2.0   \n",
       "166    2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "946    1.0        NaN    NaN     1.0     NaN         2.0         2.0   \n",
       "2639   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2084   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1565   NaN        2.0    2.0     2.0     NaN         2.0         2.0   \n",
       "1725   2.0        NaN    2.0     NaN     2.0         1.0         3.0   \n",
       "1582   2.0        NaN    2.0     NaN     1.0         2.0         2.0   \n",
       "2209   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2156   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "2086   2.0        NaN    2.0     NaN     1.0         NaN         1.0   \n",
       "2022   2.0        NaN    2.0     NaN     2.0         2.0         1.0   \n",
       "2023   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2048   2.0        NaN    2.0     1.0     NaN         1.0         2.0   \n",
       "1260   NaN        2.0    2.0     2.0     NaN         1.0         3.0   \n",
       "1156   NaN        2.0    1.0     2.0     NaN         NaN         NaN   \n",
       "1145   NaN        2.0    2.0     2.0     NaN         2.0         2.0   \n",
       "1448   NaN        2.0    2.0     1.0     NaN         2.0         2.0   \n",
       "436    2.0        NaN    2.0     NaN     2.0         2.0         2.0   \n",
       "2818   NaN        NaN    2.0     NaN     NaN         2.0         2.0   \n",
       "132    NaN        2.0    2.0     NaN     1.0         1.0         2.0   \n",
       "131    NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "373    2.0        NaN    2.0     NaN     2.0         2.0         2.0   \n",
       "52     2.0        NaN    2.0     NaN     2.0         2.0         3.0   \n",
       "1894   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "1985   NaN        2.0    2.0     NaN     1.0         2.0         1.0   \n",
       "2399   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "1937   NaN        1.0    2.0     1.0     NaN         NaN         NaN   \n",
       "177    2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1050   NaN        2.0    1.0     NaN     1.0         2.0         3.0   \n",
       "1762   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "2722   NaN        1.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2974   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "1963   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1897   NaN        2.0    2.0     1.0     NaN         NaN         NaN   \n",
       "1630   NaN        2.0    2.0     1.0     NaN         NaN         NaN   \n",
       "645    NaN        2.0    2.0     1.0     NaN         NaN         NaN   \n",
       "692    1.0        NaN    1.0     NaN     2.0         2.0         2.0   \n",
       "427    NaN        2.0    2.0     NaN     1.0         NaN         NaN   \n",
       "2174   NaN        2.0    2.0     2.0     NaN         1.0         3.0   \n",
       "2600   1.0        NaN    2.0     2.0     NaN         2.0         2.0   \n",
       "312    1.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "549    NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "514    1.0        NaN    2.0     NaN     1.0         2.0         2.0   \n",
       "2115   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2067   2.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "467    1.0        NaN    1.0     NaN     1.0         NaN         NaN   \n",
       "1530   2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "2040   NaN        2.0    2.0     1.0     NaN         1.0         2.0   \n",
       "2424   2.0        NaN    2.0     NaN     1.0         2.0         2.0   \n",
       "2486   NaN        2.0    2.0     NaN     2.0         1.0         3.0   \n",
       "2666   2.0        NaN    2.0     1.0     NaN         2.0         3.0   \n",
       "1444   NaN        2.0    2.0     NaN     1.0         NaN         NaN   \n",
       "2139   NaN        2.0    NaN     NaN     2.0         NaN         NaN   \n",
       "2314   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2284   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1321   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "381    NaN        NaN    2.0     NaN     2.0         2.0         NaN   \n",
       "687    2.0        NaN    2.0     2.0     NaN         1.0         3.0   \n",
       "2943   1.0        NaN    2.0     2.0     NaN         2.0         2.0   \n",
       "1008   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "410    NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1783   1.0        NaN    NaN     NaN     NaN         2.0         1.0   \n",
       "1550   2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "2654   1.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "1025   1.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2194   2.0        NaN    2.0     NaN     2.0         2.0         1.0   \n",
       "2079   NaN        2.0    NaN     NaN     NaN         1.0         2.0   \n",
       "2026   NaN        2.0    2.0     NaN     1.0         NaN         NaN   \n",
       "3007   NaN        2.0    2.0     NaN     1.0         1.0         2.0   \n",
       "1480   NaN        2.0    2.0     2.0     NaN         2.0         1.0   \n",
       "1607   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "809    2.0        NaN    2.0     1.0     NaN         2.0         3.0   \n",
       "1129   2.0        NaN    2.0     2.0     NaN         2.0         2.0   \n",
       "62     2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "1899   NaN        1.0    2.0     2.0     NaN         2.0         2.0   \n",
       "1009   NaN        2.0    2.0     1.0     NaN         2.0         2.0   \n",
       "859    NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "800    NaN        2.0    2.0     2.0     NaN         2.0         2.0   \n",
       "652    2.0        NaN    2.0     1.0     NaN         1.0         NaN   \n",
       "2565   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "2888   2.0        NaN    2.0     NaN     2.0         2.0         2.0   \n",
       "362    NaN        2.0    2.0     1.0     NaN         2.0         1.0   \n",
       "2781   1.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "939    NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "402    NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "1747   1.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1635   2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "2130   NaN        2.0    2.0     NaN     1.0         2.0         2.0   \n",
       "1750   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "747    2.0        NaN    1.0     NaN     2.0         NaN         NaN   \n",
       "107    2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "1745   NaN        1.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2133   2.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "1067   NaN        2.0    1.0     NaN     2.0         2.0         3.0   \n",
       "2626   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "1048   2.0        NaN    2.0     2.0     NaN         2.0         3.0   \n",
       "896    2.0        NaN    2.0     NaN     2.0         2.0         3.0   \n",
       "2886   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "2365   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1118   NaN        2.0    1.0     1.0     NaN         2.0         2.0   \n",
       "116    NaN        1.0    2.0     NaN     2.0         3.0         2.0   \n",
       "1497   2.0        NaN    2.0     NaN     1.0         NaN         NaN   \n",
       "1105   NaN        2.0    2.0     NaN     2.0         3.0         3.0   \n",
       "937    NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1018   NaN        2.0    1.0     1.0     NaN         NaN         NaN   \n",
       "767    2.0        NaN    1.0     NaN     1.0         NaN         NaN   \n",
       "1643   NaN        2.0    2.0     1.0     NaN         NaN         NaN   \n",
       "856    NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "754    2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1181   NaN        2.0    1.0     1.0     NaN         NaN         NaN   \n",
       "2      NaN        2.0    1.0     2.0     NaN         NaN         NaN   \n",
       "2354   1.0        NaN    1.0     1.0     NaN         NaN         NaN   \n",
       "2474   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1481   NaN        2.0    2.0     1.0     NaN         2.0         2.0   \n",
       "2553   2.0        NaN    2.0     NaN     2.0         2.0         3.0   \n",
       "2406   NaN        1.0    2.0     2.0     NaN         1.0         1.0   \n",
       "1608   2.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "1964   2.0        NaN    2.0     NaN     1.0         NaN         NaN   \n",
       "788    2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "26     1.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "1982   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "1933   1.0        NaN    1.0     NaN     1.0         NaN         NaN   \n",
       "2466   NaN        2.0    2.0     1.0     NaN         NaN         NaN   \n",
       "488    NaN        2.0    1.0     1.0     NaN         NaN         NaN   \n",
       "66     2.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "473    2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2903   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "450    NaN        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "1425   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2905   NaN        2.0    2.0     NaN     NaN         2.0         2.0   \n",
       "956    2.0        NaN    2.0     2.0     NaN         3.0         2.0   \n",
       "1835   2.0        NaN    2.0     NaN     NaN         NaN         NaN   \n",
       "1822   NaN        2.0    2.0     1.0     NaN         2.0         1.0   \n",
       "1685   2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2417   2.0        NaN    2.0     NaN     NaN         1.0         2.0   \n",
       "2241   2.0        NaN    2.0     NaN     2.0         2.0         1.0   \n",
       "1631   2.0        NaN    2.0     NaN     2.0         2.0         1.0   \n",
       "58     2.0        NaN    2.0     2.0     NaN         3.0         2.0   \n",
       "531    NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "1135   2.0        NaN    2.0     1.0     NaN         3.0         1.0   \n",
       "526    2.0        NaN    2.0     NaN     1.0         NaN         NaN   \n",
       "2657   NaN        2.0    NaN     NaN     2.0         NaN         NaN   \n",
       "12     1.0        NaN    1.0     NaN     1.0         2.0         2.0   \n",
       "2201   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "411    2.0        NaN    2.0     NaN     NaN         1.0         2.0   \n",
       "2078   NaN        2.0    2.0     NaN     2.0         1.0         NaN   \n",
       "1036   NaN        2.0    2.0     NaN     2.0         2.0         2.0   \n",
       "916    NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "2117   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "1417   2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "2109   NaN        2.0    2.0     1.0     NaN         NaN         NaN   \n",
       "1456   1.0        NaN    2.0     NaN     2.0         2.0         2.0   \n",
       "1065   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "979    NaN        1.0    2.0     1.0     NaN         NaN         NaN   \n",
       "3009   2.0        NaN    2.0     1.0     NaN         NaN         NaN   \n",
       "2132   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "2111   NaN        2.0    1.0     NaN     1.0         NaN         NaN   \n",
       "793    NaN        2.0    2.0     NaN     2.0         1.0         2.0   \n",
       "917    2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "2382   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2931   NaN        2.0    2.0     2.0     NaN         NaN         NaN   \n",
       "2170   2.0        NaN    2.0     NaN     2.0         2.0         1.0   \n",
       "2632   NaN        2.0    2.0     NaN     1.0         2.0         1.0   \n",
       "866    NaN        2.0    2.0     1.0     NaN         NaN         NaN   \n",
       "1641   NaN        2.0    2.0     NaN     2.0         NaN         NaN   \n",
       "1365   2.0        NaN    2.0     2.0     NaN         1.0         1.0   \n",
       "2838   NaN        2.0    NaN     NaN     2.0         1.0         3.0   \n",
       "774    2.0        NaN    2.0     NaN     2.0         2.0         2.0   \n",
       "2662   2.0        NaN    2.0     2.0     NaN         1.0         2.0   \n",
       "1399   2.0        NaN    1.0     NaN     2.0         2.0         2.0   \n",
       "2206   NaN        2.0    1.0     NaN     1.0         2.0         2.0   \n",
       "1694   2.0        NaN    2.0     NaN     1.0         2.0         2.0   \n",
       "1252   NaN        2.0    2.0     1.0     NaN         1.0         2.0   \n",
       "961    2.0        NaN    2.0     2.0     NaN         1.0         3.0   \n",
       "1546   2.0        NaN    2.0     NaN     1.0         2.0         2.0   \n",
       "2788   NaN        2.0    2.0     NaN     2.0         1.0         2.0   \n",
       "2791   2.0        NaN    2.0     1.0     NaN         2.0         2.0   \n",
       "1597   2.0        NaN    1.0     NaN     1.0         1.0         2.0   \n",
       "823    2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "617    NaN        2.0    2.0     NaN     1.0         NaN         NaN   \n",
       "619    2.0        NaN    2.0     NaN     2.0         NaN         NaN   \n",
       "1194   NaN        2.0    2.0     NaN     2.0         1.0         1.0   \n",
       "2177   2.0        NaN    2.0     2.0     NaN         NaN         NaN   \n",
       "\n",
       "      countfair3  countfair4  wvsi2  wvsi3  chm1bn  chm2bn  cses6n   b2   b3  \\\n",
       "2714         3.0         2.0    NaN    1.0     1.0     NaN     4.0  3.0  5.0   \n",
       "2278         3.0         2.0    NaN    2.0     NaN     1.0     4.0  6.0  5.0   \n",
       "2113         1.0         2.0    2.0    NaN     NaN     NaN     3.0  7.0  5.0   \n",
       "826          NaN         NaN    NaN    1.0     1.0     NaN     2.0  5.0  3.0   \n",
       "2773         NaN         NaN    1.0    NaN     NaN     2.0     5.0  5.0  5.0   \n",
       "2912         3.0         2.0    NaN    2.0     1.0     NaN     2.0  5.0  4.0   \n",
       "286          2.0         2.0    1.0    NaN     2.0     NaN     3.0  6.0  3.0   \n",
       "1850         NaN         NaN    2.0    NaN     NaN     1.0     3.0  5.0  4.0   \n",
       "1356         NaN         NaN    1.0    NaN     2.0     NaN     3.0  5.0  4.0   \n",
       "792          NaN         NaN    NaN    1.0     NaN     NaN     4.0  7.0  5.0   \n",
       "2827         NaN         NaN    NaN    1.0     2.0     NaN     3.0  7.0  5.0   \n",
       "988          1.0         2.0    2.0    NaN     2.0     NaN     3.0  5.0  5.0   \n",
       "1429         NaN         NaN    2.0    NaN     NaN     2.0     4.0  4.0  4.0   \n",
       "2330         NaN         NaN    NaN    2.0     NaN     2.0     3.0  5.0  3.0   \n",
       "1960         3.0         3.0    1.0    NaN     2.0     NaN     3.0  5.0  3.0   \n",
       "355          NaN         NaN    2.0    NaN     NaN     2.0     3.0  4.0  2.0   \n",
       "855          3.0         2.0    1.0    NaN     NaN     NaN     3.0  5.0  4.0   \n",
       "1819         2.0         2.0    2.0    NaN     NaN     2.0     3.0  5.0  4.0   \n",
       "2530         1.0         2.0    2.0    NaN     2.0     NaN     4.0  5.0  4.0   \n",
       "315          NaN         NaN    1.0    NaN     1.0     NaN     3.0  4.0  3.0   \n",
       "1301         NaN         NaN    NaN    2.0     NaN     2.0     4.0  6.0  4.0   \n",
       "446          NaN         1.0    2.0    NaN     2.0     NaN     2.0  4.0  5.0   \n",
       "2265         NaN         NaN    2.0    NaN     1.0     NaN     3.0  7.0  4.0   \n",
       "2967         NaN         NaN    NaN    1.0     1.0     NaN     2.0  6.0  5.0   \n",
       "2152         NaN         NaN    1.0    NaN     NaN     2.0     4.0  5.0  5.0   \n",
       "1588         NaN         NaN    NaN    1.0     1.0     NaN     3.0  6.0  5.0   \n",
       "2896         NaN         NaN    2.0    NaN     NaN     2.0     3.0  7.0  2.0   \n",
       "48           NaN         NaN    NaN    2.0     2.0     NaN     4.0  6.0  4.0   \n",
       "2583         3.0         3.0    1.0    NaN     NaN     2.0     4.0  3.0  5.0   \n",
       "468          NaN         NaN    1.0    NaN     1.0     NaN     4.0  7.0  4.0   \n",
       "1099         1.0         2.0    2.0    NaN     NaN     2.0     3.0  5.0  4.0   \n",
       "1500         NaN         NaN    1.0    NaN     2.0     NaN     4.0  6.0  5.0   \n",
       "1381         NaN         NaN    2.0    NaN     NaN     2.0     3.0  5.0  5.0   \n",
       "2646         2.0         2.0    1.0    NaN     2.0     NaN     3.0  5.0  3.0   \n",
       "1511         3.0         2.0    NaN    1.0     2.0     NaN     2.0  5.0  5.0   \n",
       "2521         2.0         2.0    NaN    1.0     NaN     2.0     3.0  7.0  4.0   \n",
       "8            2.0         2.0    NaN    1.0     NaN     1.0     2.0  4.0  4.0   \n",
       "1140         2.0         2.0    2.0    NaN     NaN     2.0     3.0  6.0  5.0   \n",
       "2321         2.0         2.0    1.0    NaN     2.0     NaN     2.0  6.0  5.0   \n",
       "220          NaN         NaN    1.0    NaN     NaN     2.0     3.0  6.0  5.0   \n",
       "955          NaN         NaN    NaN    1.0     NaN     2.0     3.0  3.0  4.0   \n",
       "2361         NaN         NaN    NaN    1.0     2.0     NaN     5.0  5.0  4.0   \n",
       "2116         2.0         2.0    2.0    NaN     1.0     NaN     4.0  4.0  2.0   \n",
       "2159         NaN         NaN    NaN    2.0     1.0     NaN     3.0  5.0  5.0   \n",
       "542          2.0         2.0    1.0    NaN     NaN     2.0     3.0  6.0  4.0   \n",
       "2478         NaN         NaN    1.0    NaN     NaN     2.0     4.0  4.0  3.0   \n",
       "2624         NaN         NaN    2.0    NaN     NaN     2.0     5.0  3.0  3.0   \n",
       "2000         NaN         NaN    NaN    2.0     2.0     NaN     3.0  7.0  5.0   \n",
       "1360         3.0         2.0    1.0    NaN     NaN     2.0     3.0  7.0  5.0   \n",
       "2418         NaN         NaN    NaN    2.0     2.0     NaN     3.0  6.0  4.0   \n",
       "118          NaN         NaN    1.0    NaN     NaN     2.0     3.0  5.0  3.0   \n",
       "2280         NaN         NaN    NaN    1.0     1.0     NaN     3.0  6.0  7.0   \n",
       "2825         NaN         NaN    NaN    2.0     NaN     2.0     1.0  6.0  4.0   \n",
       "868          NaN         NaN    NaN    1.0     NaN     2.0     2.0  5.0  5.0   \n",
       "2744         NaN         NaN    NaN    2.0     1.0     NaN     2.0  5.0  5.0   \n",
       "474          3.0         2.0    NaN    NaN     NaN     NaN     3.0  5.0  3.0   \n",
       "1369         NaN         NaN    1.0    NaN     NaN     2.0     2.0  2.0  4.0   \n",
       "1418         NaN         3.0    NaN    2.0     NaN     2.0     2.0  5.0  5.0   \n",
       "1060         3.0         2.0    2.0    NaN     NaN     2.0     4.0  5.0  3.0   \n",
       "1280         NaN         NaN    NaN    1.0     2.0     NaN     5.0  5.0  5.0   \n",
       "1437         2.0         2.0    NaN    2.0     NaN     2.0     4.0  3.0  5.0   \n",
       "600          NaN         NaN    1.0    NaN     1.0     NaN     3.0  7.0  4.0   \n",
       "1577         3.0         NaN    1.0    NaN     2.0     NaN     3.0  6.0  2.0   \n",
       "1470         NaN         NaN    1.0    NaN     NaN     2.0     2.0  4.0  6.0   \n",
       "1504         NaN         NaN    2.0    NaN     NaN     1.0     3.0  5.0  4.0   \n",
       "313          NaN         NaN    1.0    NaN     2.0     NaN     3.0  6.0  5.0   \n",
       "2928         NaN         NaN    1.0    NaN     NaN     1.0     3.0  6.0  6.0   \n",
       "456          NaN         NaN    NaN    1.0     1.0     NaN     3.0  5.0  5.0   \n",
       "1032         1.0         2.0    NaN    1.0     NaN     2.0     3.0  6.0  4.0   \n",
       "884          NaN         NaN    NaN    2.0     1.0     NaN     5.0  5.0  4.0   \n",
       "1283         NaN         NaN    NaN    1.0     2.0     NaN     4.0  4.0  3.0   \n",
       "1753         NaN         NaN    NaN    2.0     NaN     1.0     3.0  7.0  5.0   \n",
       "742          NaN         NaN    1.0    NaN     NaN     2.0     4.0  7.0  5.0   \n",
       "1201         NaN         NaN    NaN    2.0     NaN     2.0     5.0  4.0  3.0   \n",
       "2442         2.0         2.0    1.0    NaN     NaN     2.0     5.0  6.0  5.0   \n",
       "480          NaN         NaN    2.0    NaN     NaN     2.0     2.0  6.0  5.0   \n",
       "1463         NaN         NaN    1.0    NaN     NaN     2.0     3.0  5.0  6.0   \n",
       "231          2.0         2.0    1.0    NaN     1.0     NaN     3.0  7.0  5.0   \n",
       "1326         NaN         2.0    2.0    NaN     NaN     NaN     4.0  5.0  5.0   \n",
       "1388         NaN         NaN    2.0    NaN     2.0     NaN     3.0  5.0  3.0   \n",
       "2075         3.0         2.0    NaN    1.0     NaN     1.0     4.0  5.0  1.0   \n",
       "502          NaN         2.0    NaN    1.0     2.0     NaN     3.0  7.0  5.0   \n",
       "1693         NaN         NaN    NaN    2.0     2.0     NaN     4.0  5.0  4.0   \n",
       "1275         2.0         NaN    2.0    NaN     NaN     2.0     3.0  6.0  5.0   \n",
       "878          3.0         2.0    NaN    2.0     1.0     NaN     3.0  7.0  4.0   \n",
       "1967         2.0         3.0    NaN    1.0     NaN     2.0     3.0  6.0  3.0   \n",
       "2107         3.0         3.0    1.0    NaN     NaN     2.0     2.0  6.0  5.0   \n",
       "885          NaN         NaN    1.0    NaN     NaN     2.0     5.0  6.0  6.0   \n",
       "890          2.0         2.0    NaN    2.0     NaN     NaN     2.0  5.0  4.0   \n",
       "1660         NaN         NaN    NaN    1.0     2.0     NaN     3.0  7.0  4.0   \n",
       "1203         NaN         NaN    NaN    2.0     2.0     NaN     4.0  6.0  5.0   \n",
       "519          2.0         2.0    2.0    NaN     NaN     2.0     3.0  4.0  2.0   \n",
       "2002         NaN         NaN    2.0    NaN     NaN     1.0     2.0  5.0  5.0   \n",
       "678          NaN         NaN    NaN    1.0     NaN     2.0     2.0  4.0  2.0   \n",
       "377          NaN         NaN    1.0    NaN     NaN     2.0     3.0  7.0  4.0   \n",
       "1076         1.0         1.0    NaN    2.0     NaN     2.0     4.0  5.0  5.0   \n",
       "2977         NaN         NaN    NaN    2.0     2.0     NaN     4.0  7.0  5.0   \n",
       "2105         NaN         NaN    NaN    2.0     NaN     2.0     5.0  5.0  6.0   \n",
       "2204         NaN         NaN    NaN    2.0     2.0     NaN     3.0  5.0  2.0   \n",
       "669          NaN         NaN    2.0    NaN     2.0     NaN     2.0  7.0  4.0   \n",
       "684          NaN         NaN    1.0    NaN     NaN     2.0     4.0  4.0  2.0   \n",
       "392          NaN         NaN    NaN    2.0     NaN     1.0     3.0  6.0  3.0   \n",
       "1362         NaN         NaN    NaN    NaN     2.0     NaN     3.0  7.0  5.0   \n",
       "752          NaN         NaN    1.0    NaN     2.0     NaN     5.0  6.0  4.0   \n",
       "2070         NaN         NaN    NaN    NaN     NaN     2.0     4.0  6.0  4.0   \n",
       "1615         NaN         NaN    1.0    NaN     1.0     NaN     3.0  7.0  5.0   \n",
       "1359         NaN         NaN    NaN    1.0     NaN     NaN     3.0  5.0  6.0   \n",
       "1953         NaN         NaN    1.0    NaN     NaN     NaN     2.0  5.0  1.0   \n",
       "960          NaN         NaN    NaN    2.0     NaN     1.0     4.0  5.0  3.0   \n",
       "1581         NaN         NaN    NaN    2.0     1.0     NaN     3.0  7.0  5.0   \n",
       "2659         3.0         2.0    2.0    NaN     NaN     2.0     4.0  7.0  4.0   \n",
       "852          3.0         2.0    NaN    2.0     2.0     NaN     1.0  4.0  7.0   \n",
       "701          NaN         2.0    2.0    NaN     2.0     NaN     5.0  7.0  5.0   \n",
       "1880         NaN         3.0    1.0    NaN     NaN     2.0     2.0  7.0  5.0   \n",
       "147          NaN         NaN    2.0    NaN     NaN     2.0     3.0  2.0  1.0   \n",
       "2200         3.0         2.0    1.0    NaN     2.0     NaN     3.0  6.0  3.0   \n",
       "534          3.0         3.0    NaN    1.0     NaN     2.0     3.0  5.0  3.0   \n",
       "545          NaN         NaN    NaN    2.0     NaN     2.0     3.0  7.0  4.0   \n",
       "166          2.0         2.0    2.0    NaN     NaN     2.0     4.0  3.0  2.0   \n",
       "946          NaN         NaN    NaN    1.0     1.0     NaN     3.0  3.0  4.0   \n",
       "2639         1.0         2.0    NaN    1.0     2.0     NaN     3.0  3.0  4.0   \n",
       "2084         2.0         2.0    1.0    NaN     NaN     NaN     4.0  7.0  5.0   \n",
       "1565         NaN         NaN    NaN    2.0     NaN     2.0     4.0  7.0  5.0   \n",
       "1725         NaN         NaN    2.0    NaN     NaN     2.0     2.0  7.0  3.0   \n",
       "1582         NaN         NaN    NaN    2.0     2.0     NaN     3.0  5.0  2.0   \n",
       "2209         2.0         2.0    NaN    2.0     2.0     NaN     3.0  6.0  4.0   \n",
       "2156         NaN         NaN    2.0    NaN     NaN     2.0     4.0  7.0  3.0   \n",
       "2086         NaN         NaN    2.0    NaN     NaN     NaN     2.0  3.0  6.0   \n",
       "2022         NaN         NaN    NaN    1.0     NaN     2.0     3.0  6.0  4.0   \n",
       "2023         2.0         3.0    1.0    NaN     NaN     NaN     3.0  5.0  5.0   \n",
       "2048         NaN         NaN    NaN    2.0     NaN     1.0     2.0  6.0  5.0   \n",
       "1260         NaN         NaN    NaN    1.0     NaN     2.0     4.0  6.0  4.0   \n",
       "1156         2.0         2.0    2.0    NaN     NaN     2.0     2.0  7.0  4.0   \n",
       "1145         NaN         NaN    2.0    NaN     2.0     NaN     2.0  7.0  5.0   \n",
       "1448         NaN         NaN    1.0    NaN     NaN     1.0     3.0  7.0  5.0   \n",
       "436          NaN         NaN    NaN    1.0     NaN     2.0     3.0  5.0  3.0   \n",
       "2818         NaN         NaN    NaN    1.0     1.0     NaN     4.0  4.0  3.0   \n",
       "132          NaN         NaN    1.0    NaN     1.0     NaN     4.0  7.0  5.0   \n",
       "131          NaN         NaN    1.0    NaN     NaN     NaN     NaN  NaN  5.0   \n",
       "373          NaN         NaN    2.0    NaN     1.0     NaN     3.0  7.0  3.0   \n",
       "52           NaN         NaN    1.0    NaN     2.0     NaN     4.0  7.0  5.0   \n",
       "1894         2.0         2.0    1.0    NaN     NaN     NaN     4.0  5.0  2.0   \n",
       "1985         NaN         NaN    NaN    2.0     2.0     NaN     3.0  6.0  4.0   \n",
       "2399         NaN         NaN    1.0    NaN     2.0     NaN     5.0  7.0  5.0   \n",
       "1937         3.0         3.0    2.0    NaN     2.0     NaN     4.0  7.0  4.0   \n",
       "177          2.0         2.0    2.0    NaN     NaN     2.0     3.0  4.0  3.0   \n",
       "1050         NaN         NaN    2.0    NaN     2.0     NaN     4.0  5.0  5.0   \n",
       "1762         1.0         2.0    2.0    NaN     1.0     NaN     3.0  5.0  6.0   \n",
       "2722         2.0         2.0    2.0    NaN     2.0     NaN     2.0  6.0  4.0   \n",
       "2974         2.0         2.0    NaN    2.0     2.0     NaN     4.0  5.0  3.0   \n",
       "1963         3.0         3.0    NaN    1.0     1.0     NaN     4.0  4.0  5.0   \n",
       "1897         3.0         2.0    NaN    2.0     1.0     NaN     3.0  6.0  6.0   \n",
       "1630         1.0         2.0    NaN    1.0     NaN     2.0     3.0  5.0  4.0   \n",
       "645          2.0         2.0    1.0    NaN     NaN     NaN     4.0  7.0  5.0   \n",
       "692          NaN         NaN    NaN    2.0     NaN     2.0     4.0  5.0  4.0   \n",
       "427          1.0         1.0    NaN    1.0     NaN     NaN     4.0  4.0  3.0   \n",
       "2174         NaN         NaN    NaN    2.0     1.0     NaN     3.0  5.0  5.0   \n",
       "2600         NaN         NaN    NaN    2.0     NaN     2.0     3.0  4.0  4.0   \n",
       "312          2.0         2.0    NaN    1.0     NaN     2.0     3.0  5.0  3.0   \n",
       "549          2.0         3.0    1.0    NaN     NaN     2.0     4.0  5.0  4.0   \n",
       "514          NaN         NaN    2.0    NaN     1.0     NaN     3.0  6.0  3.0   \n",
       "2115         2.0         1.0    NaN    2.0     2.0     NaN     4.0  5.0  5.0   \n",
       "2067         1.0         3.0    2.0    NaN     1.0     NaN     3.0  7.0  4.0   \n",
       "467          2.0         2.0    NaN    1.0     NaN     NaN     3.0  7.0  5.0   \n",
       "1530         NaN         NaN    1.0    NaN     2.0     NaN     4.0  5.0  5.0   \n",
       "2040         NaN         NaN    1.0    NaN     NaN     2.0     4.0  3.0  4.0   \n",
       "2424         NaN         NaN    2.0    NaN     NaN     1.0     3.0  5.0  3.0   \n",
       "2486         NaN         NaN    NaN    2.0     NaN     NaN     4.0  6.0  4.0   \n",
       "2666         NaN         NaN    NaN    2.0     NaN     2.0     2.0  7.0  5.0   \n",
       "1444         NaN         1.0    1.0    NaN     NaN     NaN     3.0  6.0  5.0   \n",
       "2139         2.0         2.0    2.0    NaN     NaN     2.0     4.0  4.0  4.0   \n",
       "2314         1.0         1.0    NaN    1.0     2.0     NaN     3.0  4.0  4.0   \n",
       "2284         3.0         2.0    NaN    2.0     NaN     NaN     5.0  5.0  3.0   \n",
       "1321         2.0         1.0    1.0    NaN     NaN     NaN     NaN  5.0  5.0   \n",
       "381          NaN         NaN    2.0    NaN     2.0     NaN     2.0  6.0  4.0   \n",
       "687          NaN         NaN    NaN    1.0     2.0     NaN     4.0  7.0  5.0   \n",
       "2943         NaN         NaN    NaN    2.0     NaN     1.0     3.0  4.0  6.0   \n",
       "1008         2.0         3.0    NaN    2.0     2.0     NaN     3.0  4.0  3.0   \n",
       "410          2.0         2.0    NaN    1.0     2.0     NaN     4.0  5.0  1.0   \n",
       "1783         NaN         NaN    NaN    2.0     NaN     1.0     2.0  5.0  5.0   \n",
       "1550         NaN         NaN    1.0    NaN     NaN     1.0     2.0  5.0  5.0   \n",
       "2654         1.0         1.0    NaN    1.0     2.0     NaN     3.0  7.0  5.0   \n",
       "1025         3.0         2.0    2.0    NaN     NaN     2.0     4.0  NaN  2.0   \n",
       "2194         NaN         NaN    2.0    NaN     NaN     2.0     3.0  6.0  5.0   \n",
       "2079         NaN         NaN    1.0    NaN     NaN     NaN     3.0  7.0  5.0   \n",
       "2026         2.0         2.0    NaN    2.0     1.0     NaN     3.0  4.0  2.0   \n",
       "3007         NaN         NaN    NaN    1.0     1.0     NaN     2.0  5.0  4.0   \n",
       "1480         NaN         NaN    1.0    NaN     NaN     NaN     4.0  7.0  3.0   \n",
       "1607         1.0         3.0    2.0    NaN     NaN     2.0     3.0  4.0  3.0   \n",
       "809          NaN         NaN    NaN    2.0     NaN     NaN     3.0  6.0  4.0   \n",
       "1129         NaN         NaN    NaN    1.0     NaN     2.0     4.0  7.0  4.0   \n",
       "62           2.0         3.0    NaN    2.0     1.0     NaN     4.0  5.0  4.0   \n",
       "1899         NaN         NaN    NaN    1.0     NaN     2.0     1.0  5.0  3.0   \n",
       "1009         NaN         NaN    NaN    1.0     NaN     2.0     2.0  7.0  3.0   \n",
       "859          2.0         2.0    1.0    NaN     NaN     2.0     5.0  4.0  7.0   \n",
       "800          NaN         NaN    NaN    1.0     2.0     NaN     3.0  6.0  4.0   \n",
       "652          NaN         NaN    1.0    NaN     2.0     NaN     4.0  4.0  7.0   \n",
       "2565         3.0         3.0    NaN    2.0     NaN     2.0     2.0  6.0  6.0   \n",
       "2888         NaN         NaN    2.0    NaN     NaN     2.0     4.0  7.0  2.0   \n",
       "362          NaN         NaN    2.0    NaN     NaN     1.0     2.0  5.0  4.0   \n",
       "2781         2.0         3.0    NaN    2.0     NaN     2.0     3.0  5.0  5.0   \n",
       "939          2.0         2.0    2.0    NaN     NaN     2.0     3.0  6.0  4.0   \n",
       "402          3.0         2.0    NaN    2.0     NaN     2.0     4.0  3.0  2.0   \n",
       "1747         1.0         2.0    NaN    1.0     2.0     NaN     3.0  4.0  3.0   \n",
       "1635         NaN         NaN    NaN    2.0     NaN     2.0     2.0  7.0  4.0   \n",
       "2130         NaN         NaN    NaN    2.0     1.0     NaN     3.0  6.0  5.0   \n",
       "1750         2.0         3.0    NaN    1.0     2.0     NaN     4.0  7.0  5.0   \n",
       "747          2.0         2.0    2.0    NaN     2.0     NaN     4.0  5.0  5.0   \n",
       "107          NaN         NaN    NaN    2.0     2.0     NaN     4.0  6.0  5.0   \n",
       "1745         2.0         3.0    NaN    2.0     1.0     NaN     3.0  5.0  7.0   \n",
       "2133         NaN         NaN    1.0    NaN     2.0     NaN     4.0  7.0  NaN   \n",
       "1067         NaN         NaN    1.0    NaN     NaN     1.0     3.0  6.0  5.0   \n",
       "2626         3.0         3.0    2.0    NaN     NaN     2.0     2.0  3.0  3.0   \n",
       "1048         NaN         NaN    2.0    NaN     NaN     NaN     4.0  5.0  2.0   \n",
       "896          NaN         NaN    1.0    NaN     NaN     2.0     5.0  4.0  4.0   \n",
       "2886         NaN         NaN    1.0    NaN     NaN     2.0     2.0  3.0  4.0   \n",
       "2365         2.0         3.0    1.0    NaN     NaN     NaN     3.0  6.0  6.0   \n",
       "1118         NaN         NaN    1.0    NaN     NaN     2.0     2.0  7.0  4.0   \n",
       "116          NaN         NaN    NaN    2.0     NaN     2.0     2.0  5.0  2.0   \n",
       "1497         1.0         1.0    2.0    NaN     NaN     2.0     3.0  4.0  2.0   \n",
       "1105         NaN         NaN    1.0    NaN     NaN     2.0     4.0  7.0  3.0   \n",
       "937          3.0         1.0    2.0    NaN     1.0     NaN     5.0  4.0  2.0   \n",
       "1018         2.0         2.0    2.0    NaN     1.0     NaN     1.0  5.0  6.0   \n",
       "767          2.0         2.0    NaN    2.0     1.0     NaN     5.0  5.0  3.0   \n",
       "1643         3.0         2.0    1.0    NaN     NaN     NaN     3.0  7.0  6.0   \n",
       "856          1.0         1.0    NaN    1.0     2.0     NaN     3.0  6.0  5.0   \n",
       "754          2.0         3.0    1.0    NaN     2.0     NaN     3.0  7.0  5.0   \n",
       "1181         2.0         2.0    NaN    2.0     2.0     NaN     4.0  7.0  4.0   \n",
       "2            2.0         3.0    NaN    1.0     2.0     NaN     3.0  4.0  3.0   \n",
       "2354         2.0         2.0    2.0    NaN     NaN     2.0     5.0  6.0  3.0   \n",
       "2474         3.0         2.0    NaN    2.0     2.0     NaN     3.0  6.0  7.0   \n",
       "1481         NaN         NaN    NaN    2.0     2.0     NaN     3.0  7.0  4.0   \n",
       "2553         NaN         NaN    2.0    NaN     2.0     NaN     4.0  3.0  2.0   \n",
       "2406         NaN         NaN    NaN    2.0     NaN     2.0     3.0  5.0  4.0   \n",
       "1608         2.0         2.0    NaN    1.0     1.0     NaN     3.0  6.0  5.0   \n",
       "1964         2.0         2.0    2.0    NaN     NaN     1.0     3.0  7.0  4.0   \n",
       "788          NaN         NaN    2.0    NaN     NaN     2.0     3.0  6.0  3.0   \n",
       "26           2.0         2.0    2.0    NaN     NaN     2.0     2.0  5.0  5.0   \n",
       "1982         3.0         2.0    NaN    1.0     2.0     NaN     5.0  6.0  4.0   \n",
       "1933         1.0         2.0    NaN    1.0     2.0     NaN     5.0  5.0  4.0   \n",
       "2466         3.0         2.0    NaN    2.0     NaN     1.0     3.0  6.0  4.0   \n",
       "488          1.0         3.0    1.0    NaN     2.0     NaN     2.0  5.0  4.0   \n",
       "66           3.0         2.0    2.0    NaN     1.0     NaN     4.0  5.0  5.0   \n",
       "473          2.0         2.0    1.0    NaN     2.0     NaN     4.0  3.0  4.0   \n",
       "2903         NaN         NaN    NaN    1.0     NaN     2.0     1.0  6.0  7.0   \n",
       "450          1.0         2.0    NaN    2.0     1.0     NaN     3.0  6.0  7.0   \n",
       "1425         NaN         2.0    NaN    2.0     2.0     NaN     1.0  7.0  5.0   \n",
       "2905         NaN         NaN    NaN    2.0     NaN     NaN     3.0  7.0  4.0   \n",
       "956          NaN         NaN    2.0    NaN     2.0     NaN     3.0  7.0  4.0   \n",
       "1835         3.0         2.0    1.0    NaN     1.0     NaN     3.0  6.0  4.0   \n",
       "1822         NaN         NaN    2.0    NaN     NaN     2.0     4.0  5.0  1.0   \n",
       "1685         3.0         3.0    NaN    NaN     NaN     NaN     4.0  7.0  4.0   \n",
       "2417         NaN         NaN    1.0    NaN     NaN     2.0     3.0  5.0  2.0   \n",
       "2241         NaN         NaN    2.0    NaN     1.0     NaN     2.0  6.0  3.0   \n",
       "1631         NaN         NaN    NaN    2.0     NaN     2.0     3.0  6.0  6.0   \n",
       "58           NaN         NaN    2.0    NaN     2.0     NaN     3.0  5.0  3.0   \n",
       "531          3.0         3.0    NaN    1.0     2.0     NaN     2.0  3.0  5.0   \n",
       "1135         NaN         NaN    NaN    1.0     1.0     NaN     4.0  4.0  3.0   \n",
       "526          1.0         2.0    1.0    NaN     1.0     NaN     3.0  7.0  7.0   \n",
       "2657         3.0         3.0    2.0    NaN     1.0     NaN     4.0  7.0  4.0   \n",
       "12           NaN         NaN    2.0    NaN     NaN     1.0     3.0  7.0  4.0   \n",
       "2201         2.0         2.0    NaN    1.0     NaN     1.0     3.0  5.0  3.0   \n",
       "411          NaN         NaN    NaN    1.0     NaN     2.0     3.0  7.0  4.0   \n",
       "2078         NaN         NaN    NaN    2.0     NaN     2.0     3.0  1.0  7.0   \n",
       "1036         NaN         NaN    1.0    NaN     NaN     2.0     3.0  7.0  2.0   \n",
       "916          NaN         NaN    NaN    NaN     NaN     NaN     4.0  7.0  3.0   \n",
       "2117         3.0         2.0    NaN    1.0     2.0     NaN     4.0  3.0  5.0   \n",
       "1417         NaN         NaN    1.0    NaN     2.0     NaN     3.0  6.0  7.0   \n",
       "2109         1.0         1.0    2.0    NaN     NaN     2.0     3.0  3.0  5.0   \n",
       "1456         NaN         NaN    1.0    NaN     2.0     NaN     4.0  7.0  4.0   \n",
       "1065         2.0         2.0    1.0    NaN     NaN     2.0     2.0  6.0  4.0   \n",
       "979          3.0         3.0    1.0    NaN     1.0     NaN     3.0  6.0  5.0   \n",
       "3009         3.0         2.0    1.0    NaN     NaN     NaN     4.0  6.0  5.0   \n",
       "2132         NaN         NaN    NaN    1.0     NaN     2.0     4.0  6.0  5.0   \n",
       "2111         2.0         2.0    1.0    NaN     NaN     1.0     4.0  4.0  4.0   \n",
       "793          NaN         NaN    2.0    NaN     NaN     1.0     4.0  3.0  3.0   \n",
       "917          3.0         2.0    1.0    NaN     NaN     NaN     2.0  6.0  3.0   \n",
       "2382         1.0         3.0    NaN    1.0     2.0     NaN     3.0  7.0  3.0   \n",
       "2931         2.0         1.0    NaN    2.0     NaN     2.0     3.0  7.0  5.0   \n",
       "2170         NaN         NaN    NaN    1.0     NaN     NaN     4.0  7.0  5.0   \n",
       "2632         NaN         NaN    NaN    2.0     NaN     2.0     3.0  7.0  5.0   \n",
       "866          3.0         3.0    1.0    NaN     1.0     NaN     4.0  7.0  4.0   \n",
       "1641         3.0         1.0    1.0    NaN     2.0     NaN     4.0  7.0  5.0   \n",
       "1365         NaN         NaN    1.0    NaN     NaN     2.0     2.0  6.0  3.0   \n",
       "2838         NaN         NaN    NaN    2.0     2.0     NaN     5.0  5.0  5.0   \n",
       "774          NaN         NaN    NaN    2.0     2.0     NaN     2.0  5.0  5.0   \n",
       "2662         NaN         NaN    1.0    NaN     NaN     2.0     2.0  3.0  1.0   \n",
       "1399         NaN         NaN    NaN    1.0     NaN     2.0     3.0  2.0  1.0   \n",
       "2206         NaN         NaN    1.0    NaN     NaN     2.0     3.0  7.0  6.0   \n",
       "1694         NaN         NaN    1.0    NaN     NaN     1.0     4.0  5.0  2.0   \n",
       "1252         NaN         NaN    NaN    1.0     NaN     NaN     5.0  5.0  3.0   \n",
       "961          NaN         NaN    NaN    2.0     NaN     2.0     NaN  4.0  4.0   \n",
       "1546         NaN         NaN    NaN    1.0     2.0     NaN     4.0  6.0  5.0   \n",
       "2788         NaN         NaN    NaN    1.0     2.0     NaN     NaN  7.0  4.0   \n",
       "2791         NaN         NaN    NaN    1.0     NaN     1.0     2.0  5.0  4.0   \n",
       "1597         NaN         NaN    2.0    NaN     NaN     2.0     1.0  5.0  5.0   \n",
       "823          2.0         2.0    1.0    NaN     2.0     NaN     3.0  4.0  4.0   \n",
       "617          2.0         1.0    NaN    1.0     NaN     2.0     3.0  6.0  5.0   \n",
       "619          3.0         2.0    NaN    1.0     2.0     NaN     5.0  3.0  3.0   \n",
       "1194         NaN         NaN    NaN    2.0     NaN     2.0     5.0  7.0  6.0   \n",
       "2177         NaN         3.0    NaN    2.0     NaN     NaN     5.0  6.0  5.0   \n",
       "\n",
       "       b6  dst1bn  drk1c   m1  ing4  anestg  mil10a  mil10e  ccch1  ccus1  \\\n",
       "2714  4.0     1.0    3.0  3.0   5.0     2.0     3.0     2.0    1.0    NaN   \n",
       "2278  5.0     2.0    3.0  3.0   5.0     2.0     2.0     3.0    2.0    NaN   \n",
       "2113  5.0     1.0    3.0  3.0   7.0     2.0     NaN     NaN    NaN    1.0   \n",
       "826   5.0     2.0    4.0  3.0   6.0     2.0     NaN     NaN    2.0    NaN   \n",
       "2773  5.0     3.0    3.0  2.0   6.0     2.0     2.0     2.0    2.0    NaN   \n",
       "2912  5.0     2.0    3.0  2.0   7.0     2.0     2.0     2.0    1.0    NaN   \n",
       "286   5.0     2.0    3.0  2.0   6.0     2.0     2.0     2.0    NaN    1.0   \n",
       "1850  6.0     2.0    2.0  2.0   5.0     2.0     NaN     1.0    2.0    NaN   \n",
       "1356  5.0     1.0    2.0  4.0   6.0     3.0     NaN     3.0    2.0    NaN   \n",
       "792   5.0     3.0    3.0  3.0   5.0     2.0     NaN     3.0    NaN    2.0   \n",
       "2827  5.0     1.0    2.0  3.0   6.0     4.0     NaN     NaN    2.0    NaN   \n",
       "988   5.0     4.0    3.0  3.0   6.0     2.0     NaN     NaN    NaN    1.0   \n",
       "1429  5.0     2.0    3.0  3.0   5.0     3.0     NaN     NaN    NaN    3.0   \n",
       "2330  5.0     2.0    4.0  3.0   5.0     2.0     3.0     3.0    NaN    1.0   \n",
       "1960  6.0     3.0    3.0  3.0   6.0     3.0     2.0     2.0    NaN    1.0   \n",
       "355   5.0     2.0    3.0  2.0   7.0     2.0     2.0     3.0    2.0    NaN   \n",
       "855   3.0     2.0    4.0  3.0   7.0     2.0     2.0     2.0    1.0    NaN   \n",
       "1819  5.0     2.0    3.0  2.0   6.0     2.0     2.0     2.0    NaN    2.0   \n",
       "2530  5.0     1.0    3.0  3.0   7.0     2.0     2.0     3.0    NaN    1.0   \n",
       "315   5.0     2.0    2.0  2.0   5.0     2.0     NaN     3.0    3.0    NaN   \n",
       "1301  6.0     1.0    4.0  4.0   6.0     3.0     NaN     2.0    NaN    2.0   \n",
       "446   5.0     2.0    NaN  3.0   5.0     2.0     NaN     NaN    NaN    1.0   \n",
       "2265  NaN     2.0    3.0  3.0   5.0     2.0     NaN     NaN    2.0    NaN   \n",
       "2967  5.0     1.0    3.0  3.0   6.0     2.0     NaN     NaN    NaN    2.0   \n",
       "2152  5.0     4.0    4.0  3.0   5.0     2.0     3.0     2.0    NaN    2.0   \n",
       "1588  6.0     1.0    4.0  3.0   6.0     2.0     3.0     3.0    1.0    NaN   \n",
       "2896  6.0     2.0    3.0  4.0   6.0     3.0     2.0     2.0    2.0    NaN   \n",
       "48    6.0     2.0    3.0  2.0   6.0     2.0     2.0     2.0    NaN    1.0   \n",
       "2583  6.0     3.0    3.0  3.0   5.0     2.0     3.0     2.0    1.0    NaN   \n",
       "468   4.0     1.0    3.0  3.0   7.0     2.0     2.0     2.0    1.0    NaN   \n",
       "1099  7.0     1.0    3.0  3.0   7.0     2.0     NaN     NaN    NaN    1.0   \n",
       "1500  6.0     2.0    3.0  3.0   6.0     2.0     NaN     2.0    NaN    1.0   \n",
       "1381  6.0     1.0    4.0  2.0   7.0     2.0     NaN     2.0    1.0    NaN   \n",
       "2646  4.0     3.0    2.0  3.0   6.0     3.0     NaN     3.0    NaN    2.0   \n",
       "1511  5.0     4.0    3.0  3.0   6.0     3.0     NaN     4.0    2.0    NaN   \n",
       "2521  4.0     2.0    3.0  3.0   5.0     3.0     2.0     NaN    2.0    NaN   \n",
       "8     3.0     2.0    3.0  4.0   7.0     3.0     NaN     2.0    1.0    NaN   \n",
       "1140  5.0     2.0    4.0  4.0   5.0     3.0     3.0     2.0    2.0    NaN   \n",
       "2321  5.0     2.0    4.0  4.0   7.0     3.0     NaN     2.0    NaN    2.0   \n",
       "220   5.0     3.0    3.0  3.0   4.0     2.0     NaN     NaN    NaN    NaN   \n",
       "955   3.0     1.0    3.0  4.0   4.0     3.0     NaN     NaN    2.0    NaN   \n",
       "2361  4.0     2.0    3.0  2.0   5.0     2.0     2.0     2.0    2.0    NaN   \n",
       "2116  5.0     2.0    3.0  4.0   5.0     3.0     2.0     3.0    NaN    2.0   \n",
       "2159  5.0     3.0    4.0  2.0   6.0     2.0     1.0     2.0    NaN    1.0   \n",
       "542   5.0     2.0    4.0  2.0   6.0     1.0     2.0     3.0    NaN    1.0   \n",
       "2478  6.0     2.0    4.0  4.0   7.0     2.0     3.0     2.0    NaN    1.0   \n",
       "2624  4.0     1.0    4.0  2.0   6.0     2.0     2.0     2.0    NaN    1.0   \n",
       "2000  5.0     1.0    2.0  2.0   5.0     2.0     3.0     2.0    1.0    NaN   \n",
       "1360  7.0     2.0    3.0  3.0   7.0     3.0     2.0     4.0    NaN    2.0   \n",
       "2418  5.0     2.0    2.0  3.0   7.0     2.0     3.0     4.0    NaN    3.0   \n",
       "118   5.0     2.0    3.0  3.0   6.0     2.0     3.0     2.0    1.0    NaN   \n",
       "2280  6.0     1.0    3.0  3.0   6.0     2.0     4.0     2.0    2.0    NaN   \n",
       "2825  4.0     1.0    3.0  3.0   6.0     3.0     4.0     1.0    NaN    2.0   \n",
       "868   5.0     2.0    4.0  3.0   4.0     2.0     NaN     NaN    2.0    NaN   \n",
       "2744  5.0     2.0    3.0  3.0   7.0     2.0     NaN     NaN    4.0    NaN   \n",
       "474   5.0     4.0    3.0  2.0   7.0     2.0     NaN     3.0    2.0    NaN   \n",
       "1369  5.0     3.0    3.0  3.0   5.0     3.0     NaN     NaN    2.0    NaN   \n",
       "1418  4.0     2.0    2.0  3.0   7.0     2.0     NaN     1.0    2.0    NaN   \n",
       "1060  5.0     1.0    3.0  3.0   5.0     3.0     NaN     NaN    NaN    2.0   \n",
       "1280  5.0     2.0    3.0  2.0   5.0     2.0     NaN     NaN    NaN    2.0   \n",
       "1437  4.0     2.0    2.0  2.0   6.0     3.0     NaN     NaN    NaN    2.0   \n",
       "600   5.0     1.0    2.0  3.0   5.0     3.0     NaN     NaN    NaN    1.0   \n",
       "1577  5.0     3.0    3.0  4.0   6.0     3.0     NaN     2.0    3.0    NaN   \n",
       "1470  5.0     3.0    4.0  3.0   5.0     2.0     NaN     NaN    1.0    NaN   \n",
       "1504  6.0     3.0    3.0  2.0   5.0     2.0     NaN     3.0    2.0    NaN   \n",
       "313   5.0     2.0    3.0  2.0   7.0     2.0     NaN     NaN    NaN    1.0   \n",
       "2928  5.0     1.0    4.0  2.0   5.0     2.0     NaN     NaN    NaN    2.0   \n",
       "456   5.0     1.0    2.0  2.0   5.0     NaN     NaN     NaN    NaN    NaN   \n",
       "1032  5.0     1.0    3.0  3.0   5.0     2.0     NaN     2.0    NaN    3.0   \n",
       "884   4.0     1.0    4.0  3.0   5.0     2.0     NaN     3.0    3.0    NaN   \n",
       "1283  5.0     2.0    4.0  5.0   7.0     4.0     NaN     2.0    NaN    2.0   \n",
       "1753  6.0     NaN    3.0  1.0   7.0     1.0     2.0     2.0    NaN    1.0   \n",
       "742   5.0     2.0    3.0  2.0   6.0     2.0     2.0     NaN    1.0    NaN   \n",
       "1201  5.0     2.0    3.0  4.0   7.0     3.0     3.0     2.0    1.0    NaN   \n",
       "2442  7.0     1.0    2.0  2.0   7.0     2.0     NaN     2.0    3.0    NaN   \n",
       "480   6.0     2.0    3.0  2.0   6.0     1.0     NaN     2.0    2.0    NaN   \n",
       "1463  6.0     3.0    2.0  3.0   7.0     2.0     NaN     3.0    NaN    1.0   \n",
       "231   5.0     2.0    3.0  5.0   5.0     3.0     NaN     2.0    NaN    1.0   \n",
       "1326  3.0     1.0    4.0  3.0   6.0     2.0     4.0     NaN    NaN    NaN   \n",
       "1388  4.0     1.0    3.0  3.0   4.0     2.0     NaN     NaN    NaN    2.0   \n",
       "2075  5.0     1.0    NaN  3.0   6.0     2.0     NaN     NaN    NaN    1.0   \n",
       "502   4.0     3.0    2.0  2.0   7.0     2.0     NaN     NaN    2.0    NaN   \n",
       "1693  7.0     NaN    NaN  4.0   6.0     3.0     3.0     2.0    NaN    2.0   \n",
       "1275  6.0     2.0    4.0  2.0   6.0     1.0     NaN     3.0    NaN    2.0   \n",
       "878   6.0     NaN    4.0  2.0   7.0     2.0     NaN     NaN    NaN    1.0   \n",
       "1967  7.0     1.0    3.0  NaN   6.0     2.0     NaN     NaN    NaN    1.0   \n",
       "2107  6.0     4.0    3.0  2.0   7.0     2.0     2.0     3.0    NaN    1.0   \n",
       "885   7.0     2.0    2.0  2.0   6.0     2.0     2.0     2.0    2.0    NaN   \n",
       "890   4.0     2.0    4.0  2.0   7.0     2.0     2.0     3.0    1.0    NaN   \n",
       "1660  6.0     1.0    3.0  2.0   7.0     1.0     2.0     2.0    NaN    1.0   \n",
       "1203  6.0     2.0    2.0  2.0   7.0     2.0     3.0     2.0    2.0    NaN   \n",
       "519   6.0     2.0    3.0  2.0   7.0     2.0     3.0     3.0    NaN    1.0   \n",
       "2002  1.0     2.0    3.0  2.0   7.0     2.0     2.0     3.0    NaN    1.0   \n",
       "678   2.0     1.0    2.0  4.0   6.0     3.0     3.0     2.0    NaN    2.0   \n",
       "377   5.0     2.0    4.0  4.0   7.0     3.0     3.0     3.0    NaN    2.0   \n",
       "1076  5.0     4.0    2.0  3.0   5.0     2.0     2.0     2.0    2.0    NaN   \n",
       "2977  6.0     2.0    4.0  2.0   7.0     2.0     2.0     2.0    2.0    NaN   \n",
       "2105  4.0     3.0    3.0  4.0   7.0     3.0     3.0     2.0    NaN    2.0   \n",
       "2204  4.0     4.0    3.0  3.0   6.0     2.0     3.0     3.0    NaN    2.0   \n",
       "669   4.0     4.0    3.0  3.0   7.0     2.0     2.0     2.0    NaN    2.0   \n",
       "684   4.0     2.0    4.0  3.0   7.0     3.0     3.0     3.0    2.0    NaN   \n",
       "392   5.0     1.0    3.0  3.0   7.0     2.0     2.0     3.0    2.0    NaN   \n",
       "1362  6.0     2.0    2.0  4.0   7.0     2.0     3.0     1.0    2.0    NaN   \n",
       "752   6.0     2.0    3.0  2.0   6.0     1.0     3.0     3.0    NaN    2.0   \n",
       "2070  4.0     1.0    4.0  3.0   7.0     2.0     2.0     2.0    NaN    1.0   \n",
       "1615  5.0     2.0    3.0  3.0   7.0     2.0     NaN     NaN    NaN    2.0   \n",
       "1359  6.0     2.0    2.0  2.0   6.0     3.0     NaN     NaN    3.0    NaN   \n",
       "1953  5.0     2.0    3.0  5.0   6.0     3.0     NaN     2.0    1.0    NaN   \n",
       "960   7.0     2.0    3.0  2.0   6.0     2.0     NaN     NaN    NaN    2.0   \n",
       "1581  4.0     2.0    3.0  3.0   7.0     2.0     NaN     2.0    NaN    1.0   \n",
       "2659  5.0     3.0    3.0  3.0   6.0     2.0     NaN     3.0    NaN    1.0   \n",
       "852   5.0     2.0    4.0  1.0   4.0     2.0     NaN     NaN    2.0    NaN   \n",
       "701   5.0     2.0    2.0  3.0   6.0     3.0     NaN     3.0    1.0    NaN   \n",
       "1880  6.0     2.0    3.0  1.0   7.0     2.0     NaN     2.0    NaN    1.0   \n",
       "147   6.0     2.0    3.0  3.0   6.0     2.0     NaN     NaN    NaN    1.0   \n",
       "2200  7.0     1.0    4.0  3.0   7.0     3.0     NaN     1.0    NaN    NaN   \n",
       "534   5.0     1.0    4.0  3.0   5.0     3.0     NaN     NaN    NaN    3.0   \n",
       "545   7.0     2.0    4.0  3.0   6.0     2.0     NaN     NaN    2.0    NaN   \n",
       "166   3.0     2.0    3.0  3.0   6.0     3.0     NaN     NaN    NaN    2.0   \n",
       "946   4.0     2.0    3.0  3.0   5.0     3.0     2.0     3.0    NaN    2.0   \n",
       "2639  7.0     1.0    3.0  3.0   7.0     2.0     NaN     3.0    1.0    NaN   \n",
       "2084  7.0     2.0    3.0  2.0   7.0     1.0     NaN     2.0    NaN    2.0   \n",
       "1565  6.0     4.0    3.0  3.0   5.0     2.0     NaN     2.0    NaN    1.0   \n",
       "1725  5.0     2.0    2.0  3.0   5.0     2.0     2.0     3.0    NaN    NaN   \n",
       "1582  3.0     2.0    3.0  2.0   5.0     2.0     NaN     3.0    2.0    NaN   \n",
       "2209  7.0     3.0    3.0  3.0   7.0     2.0     NaN     3.0    NaN    1.0   \n",
       "2156  4.0     3.0    2.0  3.0   6.0     2.0     NaN     3.0    2.0    NaN   \n",
       "2086  5.0     2.0    2.0  2.0   7.0     2.0     2.0     3.0    1.0    NaN   \n",
       "2022  6.0     1.0    3.0  2.0   7.0     2.0     NaN     3.0    NaN    1.0   \n",
       "2023  7.0     3.0    NaN  2.0   7.0     1.0     NaN     NaN    NaN    NaN   \n",
       "2048  5.0     4.0    3.0  2.0   5.0     1.0     2.0     NaN    NaN    2.0   \n",
       "1260  7.0     1.0    2.0  3.0   7.0     2.0     NaN     2.0    1.0    NaN   \n",
       "1156  5.0     2.0    3.0  2.0   7.0     2.0     NaN     2.0    1.0    NaN   \n",
       "1145  7.0     2.0    3.0  2.0   6.0     2.0     NaN     4.0    2.0    NaN   \n",
       "1448  5.0     2.0    3.0  2.0   7.0     2.0     NaN     4.0    NaN    1.0   \n",
       "436   5.0     4.0    3.0  5.0   7.0     2.0     NaN     NaN    NaN    NaN   \n",
       "2818  3.0     2.0    NaN  3.0   4.0     3.0     NaN     2.0    2.0    NaN   \n",
       "132   6.0     2.0    3.0  1.0   6.0     1.0     NaN     3.0    2.0    NaN   \n",
       "131   6.0     3.0    3.0  2.0   7.0     2.0     NaN     4.0    NaN    1.0   \n",
       "373   5.0     4.0    3.0  2.0   7.0     2.0     NaN     2.0    NaN    1.0   \n",
       "52    7.0     3.0    3.0  2.0   7.0     1.0     NaN     2.0    NaN    2.0   \n",
       "1894  3.0     2.0    3.0  3.0   6.0     2.0     3.0     3.0    NaN    1.0   \n",
       "1985  5.0     2.0    4.0  2.0   6.0     2.0     3.0     3.0    4.0    NaN   \n",
       "2399  6.0     3.0    3.0  1.0   6.0     1.0     2.0     3.0    NaN    2.0   \n",
       "1937  5.0     2.0    3.0  3.0   5.0     3.0     2.0     3.0    NaN    3.0   \n",
       "177   4.0     4.0    3.0  3.0   7.0     2.0     3.0     3.0    2.0    NaN   \n",
       "1050  5.0     2.0    4.0  2.0   6.0     2.0     3.0     4.0    2.0    NaN   \n",
       "1762  6.0     2.0    4.0  2.0   5.0     2.0     2.0     3.0    1.0    NaN   \n",
       "2722  5.0     2.0    4.0  3.0   7.0     3.0     3.0     2.0    3.0    NaN   \n",
       "2974  6.0     1.0    3.0  2.0   7.0     2.0     3.0     4.0    1.0    NaN   \n",
       "1963  5.0     2.0    4.0  3.0   3.0     2.0     3.0     3.0    NaN    3.0   \n",
       "1897  7.0     1.0    3.0  2.0   7.0     1.0     2.0     4.0    NaN    2.0   \n",
       "1630  5.0     1.0    1.0  3.0   6.0     1.0     3.0     2.0    NaN    3.0   \n",
       "645   7.0     2.0    3.0  1.0   7.0     2.0     2.0     2.0    2.0    NaN   \n",
       "692   5.0     2.0    3.0  3.0   2.0     2.0     3.0     3.0    NaN    1.0   \n",
       "427   5.0     2.0    3.0  2.0   6.0     2.0     2.0     4.0    1.0    NaN   \n",
       "2174  4.0     4.0    2.0  3.0   6.0     3.0     3.0     4.0    NaN    1.0   \n",
       "2600  7.0     2.0    3.0  5.0   7.0     3.0     3.0     2.0    NaN    1.0   \n",
       "312   4.0     4.0    3.0  3.0   7.0     2.0     3.0     3.0    NaN    2.0   \n",
       "549   7.0     1.0    3.0  4.0   7.0     2.0     3.0     2.0    NaN    1.0   \n",
       "514   4.0     1.0    3.0  3.0   4.0     2.0     2.0     2.0    1.0    NaN   \n",
       "2115  7.0     2.0    3.0  2.0   7.0     1.0     2.0     4.0    2.0    NaN   \n",
       "2067  5.0     3.0    2.0  3.0   7.0     2.0     2.0     1.0    NaN    2.0   \n",
       "467   7.0     1.0    3.0  2.0   5.0     2.0     2.0     2.0    1.0    NaN   \n",
       "1530  5.0     2.0    3.0  2.0   4.0     3.0     3.0     1.0    1.0    NaN   \n",
       "2040  4.0     2.0    4.0  3.0   7.0     3.0     3.0     2.0    NaN    1.0   \n",
       "2424  5.0     4.0    4.0  3.0   4.0     3.0     2.0     2.0    1.0    NaN   \n",
       "2486  5.0     1.0    2.0  3.0   7.0     3.0     2.0     1.0    3.0    NaN   \n",
       "2666  5.0     2.0    3.0  2.0   6.0     2.0     4.0     3.0    NaN    1.0   \n",
       "1444  4.0     2.0    4.0  2.0   7.0     2.0     NaN     NaN    2.0    NaN   \n",
       "2139  4.0     5.0    3.0  3.0   4.0     2.0     NaN     NaN    NaN    2.0   \n",
       "2314  4.0     2.0    2.0  4.0   7.0     3.0     NaN     NaN    2.0    NaN   \n",
       "2284  7.0     3.0    3.0  3.0   6.0     2.0     NaN     NaN    NaN    NaN   \n",
       "1321  5.0     1.0    4.0  2.0   7.0     2.0     4.0     4.0    NaN    1.0   \n",
       "381   5.0     4.0    3.0  4.0   6.0     4.0     3.0     2.0    2.0    NaN   \n",
       "687   7.0     1.0    3.0  3.0   7.0     2.0     NaN     NaN    NaN    4.0   \n",
       "2943  7.0     1.0    4.0  1.0   5.0     1.0     NaN     NaN    1.0    NaN   \n",
       "1008  6.0     4.0    3.0  3.0   7.0     2.0     NaN     NaN    NaN    1.0   \n",
       "410   5.0     4.0    3.0  4.0   7.0     2.0     NaN     2.0    NaN    NaN   \n",
       "1783  5.0     1.0    2.0  2.0   4.0     2.0     3.0     4.0    NaN    1.0   \n",
       "1550  7.0     1.0    3.0  2.0   5.0     2.0     NaN     NaN    NaN    1.0   \n",
       "2654  5.0     1.0    4.0  3.0   6.0     3.0     NaN     NaN    1.0    NaN   \n",
       "1025  3.0     1.0    4.0  3.0   5.0     2.0     NaN     3.0    1.0    NaN   \n",
       "2194  6.0     NaN    4.0  2.0   7.0     2.0     3.0     4.0    2.0    NaN   \n",
       "2079  3.0     2.0    3.0  3.0   5.0     2.0     NaN     3.0    NaN    NaN   \n",
       "2026  5.0     1.0    3.0  5.0   5.0     2.0     3.0     NaN    1.0    NaN   \n",
       "3007  6.0     2.0    4.0  2.0   4.0     2.0     NaN     3.0    2.0    NaN   \n",
       "1480  5.0     1.0    4.0  1.0   6.0     1.0     NaN     4.0    2.0    NaN   \n",
       "1607  7.0     4.0    3.0  2.0   6.0     2.0     NaN     4.0    2.0    NaN   \n",
       "809   5.0     4.0    3.0  2.0   7.0     1.0     NaN     2.0    NaN    1.0   \n",
       "1129  7.0     2.0    3.0  5.0   7.0     3.0     NaN     2.0    NaN    2.0   \n",
       "62    5.0     3.0    3.0  2.0   7.0     2.0     NaN     2.0    1.0    NaN   \n",
       "1899  5.0     5.0    3.0  3.0   6.0     2.0     NaN     1.0    1.0    NaN   \n",
       "1009  5.0     4.0    3.0  3.0   6.0     3.0     NaN     3.0    1.0    NaN   \n",
       "859   7.0     1.0    3.0  5.0   7.0     4.0     NaN     2.0    2.0    NaN   \n",
       "800   6.0     2.0    2.0  2.0   5.0     3.0     NaN     2.0    NaN    1.0   \n",
       "652   7.0     1.0    2.0  2.0   7.0     1.0     2.0     4.0    2.0    NaN   \n",
       "2565  7.0     1.0    3.0  2.0   7.0     1.0     NaN     3.0    3.0    NaN   \n",
       "2888  NaN     2.0    3.0  5.0   7.0     3.0     3.0     2.0    2.0    NaN   \n",
       "362   5.0     1.0    4.0  1.0   6.0     1.0     NaN     3.0    NaN    1.0   \n",
       "2781  5.0     1.0    4.0  2.0   7.0     3.0     NaN     1.0    NaN    4.0   \n",
       "939   3.0     2.0    3.0  2.0   6.0     2.0     NaN     3.0    4.0    NaN   \n",
       "402   4.0     4.0    3.0  4.0   6.0     3.0     NaN     2.0    NaN    3.0   \n",
       "1747  6.0     1.0    4.0  3.0   7.0     3.0     NaN     4.0    NaN    2.0   \n",
       "1635  7.0     2.0    3.0  2.0   7.0     1.0     NaN     3.0    2.0    NaN   \n",
       "2130  6.0     2.0    2.0  3.0   5.0     3.0     NaN     3.0    NaN    1.0   \n",
       "1750  6.0     3.0    3.0  2.0   7.0     2.0     NaN     1.0    2.0    NaN   \n",
       "747   5.0     2.0    1.0  2.0   4.0     2.0     NaN     3.0    NaN    2.0   \n",
       "107   4.0     3.0    3.0  2.0   7.0     2.0     NaN     3.0    NaN    1.0   \n",
       "1745  5.0     2.0    3.0  3.0   7.0     4.0     NaN     3.0    2.0    NaN   \n",
       "2133  6.0     1.0    3.0  2.0   7.0     1.0     NaN     3.0    NaN    2.0   \n",
       "1067  5.0     1.0    4.0  2.0   5.0     2.0     3.0     3.0    3.0    NaN   \n",
       "2626  6.0     4.0    3.0  4.0   7.0     2.0     2.0     2.0    3.0    NaN   \n",
       "1048  5.0     3.0    2.0  3.0   6.0     3.0     4.0     4.0    NaN    2.0   \n",
       "896   7.0     2.0    1.0  4.0   6.0     4.0     3.0     2.0    2.0    NaN   \n",
       "2886  5.0     2.0    2.0  5.0   4.0     3.0     2.0     1.0    4.0    NaN   \n",
       "2365  7.0     2.0    4.0  2.0   7.0     1.0     2.0     2.0    3.0    NaN   \n",
       "1118  7.0     1.0    4.0  2.0   5.0     2.0     2.0     2.0    NaN    2.0   \n",
       "116   3.0     1.0    3.0  5.0   7.0     3.0     2.0     2.0    NaN    2.0   \n",
       "1497  5.0     3.0    3.0  4.0   6.0     3.0     2.0     3.0    NaN    1.0   \n",
       "1105  7.0     2.0    3.0  2.0   7.0     2.0     2.0     2.0    2.0    NaN   \n",
       "937   4.0     2.0    3.0  4.0   3.0     3.0     2.0     2.0    NaN    2.0   \n",
       "1018  6.0     1.0    3.0  2.0   7.0     1.0     3.0     3.0    1.0    NaN   \n",
       "767   5.0     2.0    3.0  2.0   4.0     2.0     2.0     2.0    4.0    NaN   \n",
       "1643  7.0     2.0    4.0  1.0   7.0     1.0     2.0     3.0    2.0    NaN   \n",
       "856   5.0     2.0    4.0  4.0   7.0     3.0     3.0     2.0    1.0    NaN   \n",
       "754   7.0     1.0    3.0  2.0   7.0     3.0     1.0     1.0    NaN    1.0   \n",
       "1181  5.0     1.0    1.0  3.0   7.0     3.0     2.0     3.0    2.0    NaN   \n",
       "2     4.0     3.0    3.0  3.0   3.0     2.0     3.0     2.0    2.0    NaN   \n",
       "2354  5.0     3.0    3.0  3.0   6.0     2.0     2.0     2.0    2.0    NaN   \n",
       "2474  7.0     1.0    3.0  1.0   7.0     1.0     1.0     4.0    3.0    NaN   \n",
       "1481  6.0     3.0    4.0  3.0   7.0     3.0     3.0     2.0    1.0    NaN   \n",
       "2553  3.0     3.0    3.0  3.0   5.0     3.0     2.0     3.0    NaN    1.0   \n",
       "2406  6.0     2.0    4.0  2.0   7.0     1.0     3.0     2.0    1.0    NaN   \n",
       "1608  6.0     2.0    3.0  2.0   5.0     2.0     4.0     2.0    4.0    NaN   \n",
       "1964  4.0     3.0    4.0  3.0   7.0     2.0     3.0     2.0    NaN    1.0   \n",
       "788   5.0     3.0    2.0  3.0   5.0     2.0     3.0     3.0    NaN    1.0   \n",
       "26    4.0     4.0    4.0  2.0   5.0     2.0     2.0     2.0    NaN    1.0   \n",
       "1982  2.0     2.0    4.0  3.0   6.0     3.0     3.0     2.0    NaN    2.0   \n",
       "1933  5.0     2.0    4.0  3.0   6.0     2.0     2.0     3.0    1.0    NaN   \n",
       "2466  7.0     1.0    3.0  1.0   7.0     1.0     2.0     3.0    3.0    NaN   \n",
       "488   5.0     2.0    2.0  3.0   7.0     2.0     2.0     4.0    NaN    1.0   \n",
       "66    6.0     4.0    1.0  2.0   7.0     1.0     2.0     3.0    1.0    NaN   \n",
       "473   4.0     5.0    3.0  3.0   7.0     3.0     3.0     3.0    2.0    NaN   \n",
       "2903  7.0     1.0    NaN  1.0   7.0     2.0     2.0     2.0    2.0    NaN   \n",
       "450   5.0     1.0    3.0  1.0   5.0     1.0     NaN     NaN    3.0    NaN   \n",
       "1425  7.0     3.0    3.0  2.0   7.0     1.0     NaN     NaN    2.0    NaN   \n",
       "2905  5.0     5.0    4.0  4.0   6.0     4.0     NaN     NaN    NaN    2.0   \n",
       "956   4.0     4.0    3.0  3.0   7.0     2.0     NaN     NaN    NaN    NaN   \n",
       "1835  7.0     2.0    3.0  1.0   7.0     1.0     NaN     NaN    2.0    NaN   \n",
       "1822  5.0     2.0    3.0  3.0   7.0     4.0     NaN     NaN    NaN    NaN   \n",
       "1685  7.0     2.0    3.0  2.0   7.0     2.0     NaN     NaN    NaN    2.0   \n",
       "2417  5.0     2.0    4.0  3.0   5.0     3.0     2.0     4.0    1.0    NaN   \n",
       "2241  4.0     1.0    4.0  2.0   6.0     1.0     NaN     NaN    NaN    1.0   \n",
       "1631  7.0     2.0    2.0  2.0   6.0     3.0     NaN     NaN    2.0    NaN   \n",
       "58    4.0     3.0    4.0  4.0   7.0     4.0     NaN     NaN    NaN    1.0   \n",
       "531   7.0     3.0    3.0  5.0   7.0     3.0     NaN     2.0    NaN    NaN   \n",
       "1135  6.0     1.0    3.0  3.0   4.0     3.0     NaN     NaN    3.0    NaN   \n",
       "526   7.0     1.0    3.0  3.0   6.0     1.0     NaN     NaN    2.0    NaN   \n",
       "2657  5.0     2.0    2.0  2.0   4.0     2.0     NaN     3.0    1.0    NaN   \n",
       "12    5.0     1.0    4.0  3.0   7.0     3.0     NaN     NaN    2.0    NaN   \n",
       "2201  5.0     3.0    2.0  3.0   7.0     2.0     NaN     NaN    NaN    4.0   \n",
       "411   4.0     1.0    3.0  1.0   7.0     1.0     NaN     4.0    2.0    NaN   \n",
       "2078  7.0     2.0    3.0  2.0   5.0     1.0     NaN     3.0    2.0    NaN   \n",
       "1036  6.0     3.0    3.0  3.0   5.0     3.0     NaN     NaN    2.0    NaN   \n",
       "916   6.0     2.0    3.0  3.0   7.0     3.0     2.0     3.0    NaN    1.0   \n",
       "2117  1.0     3.0    3.0  4.0   5.0     3.0     NaN     NaN    3.0    NaN   \n",
       "1417  6.0     2.0    2.0  3.0   4.0     4.0     NaN     NaN    2.0    NaN   \n",
       "2109  5.0     1.0    4.0  3.0   4.0     3.0     NaN     NaN    NaN    4.0   \n",
       "1456  6.0     4.0    2.0  3.0   7.0     2.0     NaN     NaN    2.0    NaN   \n",
       "1065  5.0     4.0    3.0  2.0   7.0     2.0     NaN     NaN    1.0    NaN   \n",
       "979   5.0     2.0    1.0  2.0   4.0     1.0     NaN     NaN    NaN    2.0   \n",
       "3009  4.0     2.0    4.0  3.0   7.0     3.0     NaN     NaN    NaN    1.0   \n",
       "2132  2.0     4.0    3.0  4.0   6.0     2.0     NaN     NaN    NaN    NaN   \n",
       "2111  4.0     1.0    4.0  5.0   7.0     3.0     NaN     3.0    NaN    1.0   \n",
       "793   5.0     2.0    4.0  3.0   7.0     2.0     NaN     3.0    1.0    NaN   \n",
       "917   6.0     3.0    3.0  3.0   7.0     3.0     3.0     1.0    3.0    NaN   \n",
       "2382  5.0     1.0    3.0  3.0   7.0     2.0     NaN     1.0    NaN    1.0   \n",
       "2931  7.0     2.0    3.0  1.0   7.0     1.0     NaN     3.0    2.0    NaN   \n",
       "2170  7.0     1.0    4.0  3.0   7.0     3.0     NaN     1.0    NaN    1.0   \n",
       "2632  7.0     1.0    4.0  3.0   5.0     2.0     4.0     NaN    NaN    3.0   \n",
       "866   7.0     3.0    3.0  3.0   7.0     2.0     NaN     2.0    NaN    1.0   \n",
       "1641  7.0     2.0    3.0  1.0   7.0     1.0     NaN     3.0    3.0    NaN   \n",
       "1365  5.0     4.0    3.0  4.0   5.0     2.0     NaN     3.0    2.0    NaN   \n",
       "2838  7.0     1.0    1.0  2.0   7.0     1.0     2.0     2.0    NaN    3.0   \n",
       "774   7.0     4.0    3.0  2.0   7.0     2.0     NaN     3.0    1.0    NaN   \n",
       "2662  6.0     1.0    NaN  2.0   7.0     1.0     1.0     4.0    NaN    2.0   \n",
       "1399  4.0     1.0    4.0  3.0   7.0     2.0     NaN     2.0    NaN    1.0   \n",
       "2206  7.0     3.0    3.0  1.0   7.0     1.0     NaN     2.0    2.0    NaN   \n",
       "1694  3.0     2.0    4.0  3.0   5.0     3.0     NaN     2.0    3.0    NaN   \n",
       "1252  5.0     2.0    3.0  2.0   6.0     2.0     NaN     3.0    2.0    NaN   \n",
       "961   1.0     1.0    2.0  4.0   7.0     3.0     3.0     2.0    NaN    2.0   \n",
       "1546  4.0     4.0    2.0  4.0   5.0     3.0     NaN     3.0    2.0    NaN   \n",
       "2788  3.0     2.0    3.0  3.0   7.0     3.0     3.0     1.0    1.0    NaN   \n",
       "2791  4.0     5.0    4.0  3.0   5.0     2.0     NaN     3.0    2.0    NaN   \n",
       "1597  6.0     2.0    3.0  1.0   5.0     2.0     NaN     3.0    3.0    NaN   \n",
       "823   7.0     5.0    4.0  1.0   7.0     1.0     NaN     2.0    1.0    NaN   \n",
       "617   6.0     2.0    2.0  2.0   5.0     3.0     3.0     NaN    NaN    1.0   \n",
       "619   4.0     2.0    3.0  5.0   7.0     3.0     NaN     3.0    NaN    1.0   \n",
       "1194  6.0     1.0    3.0  2.0   7.0     2.0     NaN     2.0    1.0    NaN   \n",
       "2177  5.0     4.0    3.0  3.0   7.0     2.0     3.0     3.0    NaN    3.0   \n",
       "\n",
       "      ccch3  ccus3  ctaware  ctspecific1  ctdiffuse1  ctdiffuse2  \n",
       "2714    3.0    NaN      2.0          2.0         4.0         4.0  \n",
       "2278    1.0    NaN      2.0          4.0         2.0         4.0  \n",
       "2113    NaN    3.0      2.0          3.0         2.0         4.0  \n",
       "826     3.0    NaN      3.0          4.0         4.0         4.0  \n",
       "2773    1.0    NaN      2.0          2.0         2.0         5.0  \n",
       "2912    1.0    NaN      2.0          3.0         4.0         4.0  \n",
       "286     NaN    3.0      2.0          2.0         2.0         4.0  \n",
       "1850    1.0    NaN      2.0          2.0         2.0         4.0  \n",
       "1356    2.0    NaN      3.0          NaN         4.0         4.0  \n",
       "792     NaN    3.0      2.0          NaN         3.0         4.0  \n",
       "2827    1.0    NaN      3.0          3.0         4.0         4.0  \n",
       "988     NaN    2.0      3.0          2.0         4.0         4.0  \n",
       "1429    NaN    1.0      4.0          3.0         4.0         4.0  \n",
       "2330    NaN    2.0      2.0          2.0         3.0         4.0  \n",
       "1960    NaN    2.0      2.0          2.0         4.0         4.0  \n",
       "355     2.0    NaN      3.0          2.0         2.0         4.0  \n",
       "855     1.0    NaN      2.0          2.0         5.0         5.0  \n",
       "1819    NaN    1.0      3.0          3.0         2.0         2.0  \n",
       "2530    NaN    2.0      3.0          3.0         3.0         4.0  \n",
       "315     2.0    NaN      2.0          3.0         3.0         4.0  \n",
       "1301    NaN    3.0      1.0          2.0         3.0         4.0  \n",
       "446     NaN    1.0      3.0          4.0         2.0         3.0  \n",
       "2265    NaN    NaN      3.0          3.0         2.0         4.0  \n",
       "2967    NaN    3.0      3.0          NaN         2.0         2.0  \n",
       "2152    NaN    2.0      2.0          2.0         4.0         2.0  \n",
       "1588    2.0    NaN      3.0          3.0         1.0         5.0  \n",
       "2896    2.0    NaN      2.0          2.0         4.0         4.0  \n",
       "48      NaN    3.0      3.0          4.0         4.0         4.0  \n",
       "2583    2.0    NaN      2.0          2.0         3.0         5.0  \n",
       "468     3.0    NaN      2.0          3.0         3.0         3.0  \n",
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       "1500    NaN    3.0      3.0          3.0         3.0         2.0  \n",
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       "2646    NaN    2.0      2.0          3.0         2.0         4.0  \n",
       "1511    2.0    NaN      3.0          2.0         3.0         3.0  \n",
       "2521    2.0    NaN      3.0          2.0         3.0         4.0  \n",
       "8       1.0    NaN      2.0          NaN         4.0         4.0  \n",
       "1140    2.0    NaN      2.0          2.0         3.0         3.0  \n",
       "2321    NaN    2.0      2.0          3.0         3.0         3.0  \n",
       "220     NaN    NaN      2.0          2.0         3.0         3.0  \n",
       "955     3.0    NaN      3.0          3.0         3.0         4.0  \n",
       "2361    1.0    NaN      1.0          3.0         2.0         5.0  \n",
       "2116    NaN    3.0      3.0          3.0         3.0         4.0  \n",
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       "542     NaN    3.0      1.0          3.0         2.0         4.0  \n",
       "2478    NaN    1.0      3.0          3.0         4.0         4.0  \n",
       "2624    NaN    3.0      2.0          3.0         4.0         5.0  \n",
       "2000    1.0    NaN      3.0          2.0         2.0         4.0  \n",
       "1360    NaN    3.0      3.0          2.0         3.0         4.0  \n",
       "2418    NaN    2.0      2.0          2.0         2.0         4.0  \n",
       "118     2.0    NaN      4.0          3.0         1.0         2.0  \n",
       "2280    2.0    NaN      3.0          2.0         4.0         2.0  \n",
       "2825    NaN    1.0      2.0          NaN         4.0         4.0  \n",
       "868     1.0    NaN      3.0          2.0         2.0         2.0  \n",
       "2744    NaN    NaN      2.0          2.0         3.0         2.0  \n",
       "474     NaN    NaN      3.0          NaN         2.0         NaN  \n",
       "1369    2.0    NaN      3.0          3.0         3.0         4.0  \n",
       "1418    2.0    NaN      1.0          1.0         3.0         4.0  \n",
       "1060    NaN    2.0      4.0          NaN         5.0         2.0  \n",
       "1280    NaN    NaN      4.0          3.0         3.0         4.0  \n",
       "1437    NaN    3.0      4.0          2.0         1.0         4.0  \n",
       "600     NaN    3.0      3.0          4.0         3.0         5.0  \n",
       "1577    2.0    NaN      2.0          3.0         4.0         4.0  \n",
       "1470    2.0    NaN      2.0          3.0         2.0         3.0  \n",
       "1504    2.0    NaN      3.0          2.0         3.0         5.0  \n",
       "313     NaN    3.0      3.0          2.0         3.0         2.0  \n",
       "2928    NaN    NaN      3.0          3.0         4.0         2.0  \n",
       "456     NaN    NaN      4.0          2.0         NaN         2.0  \n",
       "1032    NaN    2.0      2.0          2.0         3.0         2.0  \n",
       "884     2.0    NaN      3.0          3.0         2.0         4.0  \n",
       "1283    NaN    1.0      3.0          NaN         5.0         4.0  \n",
       "1753    NaN    2.0      3.0          3.0         2.0         3.0  \n",
       "742     2.0    NaN      3.0          3.0         4.0         2.0  \n",
       "1201    2.0    NaN      2.0          2.0         4.0         4.0  \n",
       "2442    1.0    NaN      2.0          2.0         4.0         4.0  \n",
       "480     3.0    NaN      2.0          2.0         4.0         2.0  \n",
       "1463    NaN    2.0      2.0          4.0         3.0         4.0  \n",
       "231     NaN    2.0      2.0          2.0         3.0         4.0  \n",
       "1326    NaN    NaN      3.0          3.0         3.0         3.0  \n",
       "1388    NaN    3.0      4.0          4.0         3.0         3.0  \n",
       "2075    NaN    3.0      4.0          2.0         2.0         4.0  \n",
       "502     1.0    NaN      2.0          2.0         3.0         3.0  \n",
       "1693    NaN    3.0      NaN          3.0         4.0         5.0  \n",
       "1275    NaN    3.0      2.0          3.0         4.0         3.0  \n",
       "878     NaN    1.0      1.0          2.0         4.0         4.0  \n",
       "1967    NaN    3.0      1.0          3.0         4.0         4.0  \n",
       "2107    NaN    2.0      2.0          2.0         2.0         4.0  \n",
       "885     2.0    NaN      2.0          2.0         4.0         4.0  \n",
       "890     1.0    NaN      2.0          2.0         4.0         4.0  \n",
       "1660    NaN    2.0      2.0          2.0         3.0         3.0  \n",
       "1203    1.0    NaN      3.0          3.0         2.0         4.0  \n",
       "519     NaN    2.0      2.0          3.0         2.0         3.0  \n",
       "2002    NaN    3.0      2.0          2.0         2.0         4.0  \n",
       "678     NaN    3.0      2.0          3.0         2.0         4.0  \n",
       "377     NaN    2.0      2.0          2.0         4.0         4.0  \n",
       "1076    2.0    NaN      4.0          2.0         4.0         4.0  \n",
       "2977    1.0    NaN      2.0          3.0         2.0         4.0  \n",
       "2105    NaN    1.0      2.0          3.0         2.0         5.0  \n",
       "2204    NaN    2.0      2.0          2.0         4.0         2.0  \n",
       "669     NaN    1.0      3.0          2.0         4.0         4.0  \n",
       "684     2.0    NaN      2.0          3.0         5.0         3.0  \n",
       "392     2.0    NaN      4.0          2.0         2.0         2.0  \n",
       "1362    3.0    NaN      2.0          2.0         4.0         4.0  \n",
       "752     NaN    3.0      2.0          2.0         3.0         4.0  \n",
       "2070    NaN    2.0      2.0          2.0         4.0         5.0  \n",
       "1615    NaN    1.0      4.0          2.0         NaN         NaN  \n",
       "1359    1.0    NaN      3.0          2.0         NaN         4.0  \n",
       "1953    1.0    NaN      2.0          2.0         4.0         4.0  \n",
       "960     NaN    3.0      3.0          2.0         3.0         2.0  \n",
       "1581    NaN    2.0      4.0          2.0         3.0         4.0  \n",
       "2659    NaN    3.0      3.0          2.0         2.0         3.0  \n",
       "852     2.0    NaN      2.0          2.0         2.0         3.0  \n",
       "701     2.0    NaN      3.0          2.0         2.0         4.0  \n",
       "1880    NaN    1.0      2.0          3.0         2.0         4.0  \n",
       "147     NaN    3.0      4.0          3.0         4.0         4.0  \n",
       "2200    NaN    NaN      3.0          2.0         4.0         4.0  \n",
       "534     NaN    2.0      3.0          2.0         2.0         3.0  \n",
       "545     2.0    NaN      4.0          2.0         2.0         4.0  \n",
       "166     NaN    3.0      2.0          4.0         3.0         5.0  \n",
       "946     NaN    2.0      4.0          3.0         3.0         3.0  \n",
       "2639    2.0    NaN      3.0          3.0         3.0         2.0  \n",
       "2084    NaN    2.0      3.0          2.0         3.0         4.0  \n",
       "1565    NaN    2.0      3.0          2.0         3.0         5.0  \n",
       "1725    NaN    NaN      2.0          3.0         3.0         4.0  \n",
       "1582    2.0    NaN      3.0          2.0         3.0         4.0  \n",
       "2209    NaN    3.0      3.0          3.0         3.0         4.0  \n",
       "2156    2.0    NaN      3.0          2.0         4.0         4.0  \n",
       "2086    2.0    NaN      3.0          NaN         NaN         4.0  \n",
       "2022    NaN    2.0      3.0          2.0         3.0         2.0  \n",
       "2023    NaN    NaN      2.0          4.0         2.0         4.0  \n",
       "2048    NaN    2.0      3.0          2.0         3.0         4.0  \n",
       "1260    1.0    NaN      3.0          2.0         2.0         4.0  \n",
       "1156    2.0    NaN      3.0          1.0         1.0         4.0  \n",
       "1145    1.0    NaN      4.0          3.0         4.0         4.0  \n",
       "1448    NaN    3.0      2.0          2.0         3.0         2.0  \n",
       "436     NaN    NaN      3.0          NaN         4.0         NaN  \n",
       "2818    NaN    NaN      3.0          NaN         NaN         4.0  \n",
       "132     1.0    NaN      2.0          2.0         3.0         4.0  \n",
       "131     NaN    3.0      4.0          NaN         NaN         NaN  \n",
       "373     NaN    3.0      3.0          2.0         3.0         4.0  \n",
       "52      NaN    1.0      2.0          2.0         4.0         4.0  \n",
       "1894    NaN    2.0      3.0          3.0         4.0         4.0  \n",
       "1985    NaN    NaN      2.0          2.0         2.0         3.0  \n",
       "2399    NaN    3.0      2.0          3.0         1.0         3.0  \n",
       "1937    NaN    2.0      2.0          2.0         2.0         4.0  \n",
       "177     3.0    NaN      3.0          4.0         1.0         2.0  \n",
       "1050    2.0    NaN      2.0          2.0         3.0         2.0  \n",
       "1762    1.0    NaN      3.0          3.0         2.0         3.0  \n",
       "2722    2.0    NaN      2.0          2.0         4.0         5.0  \n",
       "2974    1.0    NaN      3.0          3.0         4.0         4.0  \n",
       "1963    NaN    3.0      4.0          3.0         2.0         5.0  \n",
       "1897    NaN    3.0      2.0          4.0         2.0         2.0  \n",
       "1630    NaN    2.0      3.0          1.0         4.0         2.0  \n",
       "645     2.0    NaN      3.0          NaN         2.0         4.0  \n",
       "692     NaN    2.0      2.0          2.0         3.0         4.0  \n",
       "427     3.0    NaN      3.0          3.0         2.0         4.0  \n",
       "2174    NaN    3.0      2.0          2.0         4.0         4.0  \n",
       "2600    NaN    1.0      3.0          3.0         4.0         3.0  \n",
       "312     NaN    1.0      2.0          2.0         4.0         4.0  \n",
       "549     NaN    2.0      3.0          3.0         5.0         5.0  \n",
       "514     2.0    NaN      4.0          3.0         3.0         3.0  \n",
       "2115    NaN    NaN      2.0          3.0         3.0         3.0  \n",
       "2067    NaN    3.0      2.0          2.0         3.0         4.0  \n",
       "467     1.0    NaN      3.0          NaN         NaN         4.0  \n",
       "1530    2.0    NaN      4.0          2.0         3.0         4.0  \n",
       "2040    NaN    2.0      3.0          NaN         4.0         4.0  \n",
       "2424    1.0    NaN      3.0          3.0         3.0         4.0  \n",
       "2486    1.0    NaN      3.0          NaN         2.0         5.0  \n",
       "2666    NaN    3.0      3.0          2.0         4.0         4.0  \n",
       "1444    2.0    NaN      3.0          2.0         2.0         3.0  \n",
       "2139    NaN    2.0      2.0          3.0         2.0         3.0  \n",
       "2314    2.0    NaN      3.0          NaN         4.0         NaN  \n",
       "2284    NaN    NaN      4.0          4.0         3.0         4.0  \n",
       "1321    NaN    3.0      3.0          3.0         3.0         NaN  \n",
       "381     NaN    NaN      2.0          2.0         4.0         5.0  \n",
       "687     NaN    NaN      3.0          2.0         2.0         4.0  \n",
       "2943    1.0    NaN      3.0          2.0         2.0         5.0  \n",
       "1008    NaN    2.0      3.0          3.0         3.0         3.0  \n",
       "410     NaN    NaN      2.0          2.0         4.0         4.0  \n",
       "1783    NaN    3.0      2.0          3.0         4.0         4.0  \n",
       "1550    NaN    1.0      4.0          2.0         2.0         2.0  \n",
       "2654    3.0    NaN      2.0          1.0         3.0         3.0  \n",
       "1025    3.0    NaN      3.0          3.0         2.0         4.0  \n",
       "2194    NaN    NaN      4.0          3.0         4.0         NaN  \n",
       "2079    NaN    NaN      3.0          3.0         2.0         NaN  \n",
       "2026    2.0    NaN      4.0          2.0         3.0         3.0  \n",
       "3007    3.0    NaN      3.0          2.0         2.0         4.0  \n",
       "1480    1.0    NaN      2.0          4.0         NaN         4.0  \n",
       "1607    2.0    NaN      2.0          3.0         4.0         4.0  \n",
       "809     NaN    3.0      2.0          4.0         1.0         3.0  \n",
       "1129    NaN    2.0      3.0          3.0         1.0         4.0  \n",
       "62      2.0    NaN      3.0          2.0         3.0         2.0  \n",
       "1899    3.0    NaN      2.0          2.0         5.0         5.0  \n",
       "1009    2.0    NaN      2.0          2.0         2.0         4.0  \n",
       "859     2.0    NaN      3.0          3.0         4.0         4.0  \n",
       "800     NaN    1.0      4.0          2.0         NaN         3.0  \n",
       "652     2.0    NaN      2.0          3.0         4.0         4.0  \n",
       "2565    1.0    NaN      3.0          3.0         2.0         4.0  \n",
       "2888    3.0    NaN      2.0          3.0         5.0         4.0  \n",
       "362     NaN    3.0      4.0          4.0         5.0         4.0  \n",
       "2781    NaN    NaN      4.0          NaN         2.0         4.0  \n",
       "939     NaN    NaN      3.0          3.0         4.0         3.0  \n",
       "402     NaN    2.0      3.0          3.0         2.0         4.0  \n",
       "1747    NaN    2.0      3.0          2.0         3.0         3.0  \n",
       "1635    2.0    NaN      2.0          2.0         3.0         4.0  \n",
       "2130    NaN    1.0      3.0          2.0         4.0         2.0  \n",
       "1750    3.0    NaN      3.0          2.0         3.0         4.0  \n",
       "747     NaN    1.0      4.0          2.0         4.0         4.0  \n",
       "107     NaN    3.0      4.0          2.0         4.0         4.0  \n",
       "1745    3.0    NaN      4.0          2.0         2.0         4.0  \n",
       "2133    NaN    3.0      3.0          2.0         4.0         4.0  \n",
       "1067    1.0    NaN      3.0          3.0         1.0         1.0  \n",
       "2626    1.0    NaN      3.0          2.0         2.0         5.0  \n",
       "1048    NaN    2.0      2.0          2.0         4.0         4.0  \n",
       "896     3.0    NaN      3.0          2.0         4.0         4.0  \n",
       "2886    NaN    NaN      2.0          3.0         2.0         3.0  \n",
       "2365    2.0    NaN      2.0          2.0         1.0         3.0  \n",
       "1118    NaN    2.0      3.0          2.0         3.0         3.0  \n",
       "116     NaN    2.0      2.0          3.0         5.0         5.0  \n",
       "1497    NaN    2.0      3.0          2.0         3.0         4.0  \n",
       "1105    1.0    NaN      2.0          3.0         2.0         5.0  \n",
       "937     NaN    3.0      2.0          3.0         4.0         5.0  \n",
       "1018    1.0    NaN      2.0          2.0         2.0         4.0  \n",
       "767     NaN    NaN      2.0          2.0         2.0         4.0  \n",
       "1643    1.0    NaN      2.0          3.0         1.0         4.0  \n",
       "856     1.0    NaN      3.0          3.0         3.0         5.0  \n",
       "754     NaN    2.0      1.0          2.0         1.0         4.0  \n",
       "1181    1.0    NaN      2.0          3.0         4.0         5.0  \n",
       "2       2.0    NaN      4.0          3.0         3.0         4.0  \n",
       "2354    2.0    NaN      2.0          3.0         2.0         2.0  \n",
       "2474    2.0    NaN      2.0          2.0         4.0         4.0  \n",
       "1481    3.0    NaN      3.0          3.0         3.0         4.0  \n",
       "2553    NaN    2.0      2.0          2.0         4.0         4.0  \n",
       "2406    1.0    NaN      1.0          3.0         2.0         4.0  \n",
       "1608    NaN    NaN      4.0          2.0         4.0         4.0  \n",
       "1964    NaN    2.0      3.0          3.0         2.0         4.0  \n",
       "788     NaN    2.0      3.0          3.0         1.0         3.0  \n",
       "26      NaN    2.0      2.0          2.0         4.0         2.0  \n",
       "1982    NaN    1.0      3.0          NaN         4.0         5.0  \n",
       "1933    3.0    NaN      1.0          2.0         4.0         4.0  \n",
       "2466    2.0    NaN      1.0          3.0         1.0         3.0  \n",
       "488     NaN    3.0      2.0          4.0         3.0         4.0  \n",
       "66      1.0    NaN      2.0          3.0         2.0         4.0  \n",
       "473     3.0    NaN      2.0          3.0         NaN         5.0  \n",
       "2903    1.0    NaN      3.0          NaN         4.0         4.0  \n",
       "450     2.0    NaN      2.0          2.0         4.0         4.0  \n",
       "1425    1.0    NaN      2.0          3.0         2.0         4.0  \n",
       "2905    NaN    3.0      2.0          3.0         2.0         4.0  \n",
       "956     NaN    NaN      2.0          3.0         5.0         2.0  \n",
       "1835    2.0    NaN      3.0          3.0         3.0         3.0  \n",
       "1822    NaN    NaN      2.0          3.0         4.0         4.0  \n",
       "1685    NaN    NaN      4.0          NaN         NaN         4.0  \n",
       "2417    2.0    NaN      3.0          2.0         2.0         NaN  \n",
       "2241    NaN    3.0      3.0          2.0         1.0         3.0  \n",
       "1631    1.0    NaN      4.0          2.0         3.0         3.0  \n",
       "58      NaN    2.0      2.0          3.0         3.0         4.0  \n",
       "531     NaN    NaN      4.0          NaN         3.0         4.0  \n",
       "1135    3.0    NaN      3.0          3.0         2.0         3.0  \n",
       "526     3.0    NaN      4.0          1.0         2.0         4.0  \n",
       "2657    2.0    NaN      2.0          2.0         4.0         4.0  \n",
       "12      1.0    NaN      4.0          3.0         3.0         3.0  \n",
       "2201    NaN    NaN      4.0          3.0         3.0         3.0  \n",
       "411     2.0    NaN      1.0          4.0         3.0         4.0  \n",
       "2078    2.0    NaN      2.0          3.0         1.0         4.0  \n",
       "1036    2.0    NaN      4.0          2.0         3.0         4.0  \n",
       "916     NaN    1.0      1.0          2.0         4.0         4.0  \n",
       "2117    2.0    NaN      3.0          2.0         3.0         4.0  \n",
       "1417    3.0    NaN      2.0          2.0         3.0         3.0  \n",
       "2109    NaN    NaN      4.0          2.0         5.0         4.0  \n",
       "1456    2.0    NaN      2.0          2.0         2.0         3.0  \n",
       "1065    1.0    NaN      2.0          NaN         4.0         2.0  \n",
       "979     NaN    2.0      2.0          2.0         3.0         3.0  \n",
       "3009    NaN    2.0      4.0          4.0         3.0         5.0  \n",
       "2132    NaN    NaN      2.0          NaN         3.0         NaN  \n",
       "2111    NaN    2.0      2.0          2.0         2.0         3.0  \n",
       "793     2.0    NaN      4.0          NaN         4.0         2.0  \n",
       "917     2.0    NaN      3.0          NaN         NaN         NaN  \n",
       "2382    NaN    2.0      4.0          2.0         4.0         5.0  \n",
       "2931    1.0    NaN      3.0          3.0         3.0         4.0  \n",
       "2170    NaN    NaN      3.0          3.0         4.0         3.0  \n",
       "2632    NaN    2.0      4.0          2.0         2.0         4.0  \n",
       "866     NaN    2.0      2.0          2.0         4.0         5.0  \n",
       "1641    2.0    NaN      2.0          4.0         4.0         4.0  \n",
       "1365    NaN    NaN      3.0          2.0         4.0         4.0  \n",
       "2838    NaN    1.0      3.0          3.0         2.0         4.0  \n",
       "774     2.0    NaN      3.0          2.0         3.0         2.0  \n",
       "2662    NaN    3.0      2.0          3.0         3.0         4.0  \n",
       "1399    NaN    2.0      4.0          2.0         2.0         3.0  \n",
       "2206    1.0    NaN      2.0          2.0         2.0         4.0  \n",
       "1694    2.0    NaN      3.0          NaN         NaN         4.0  \n",
       "1252    2.0    NaN      4.0          3.0         2.0         2.0  \n",
       "961     NaN    2.0      3.0          NaN         3.0         5.0  \n",
       "1546    3.0    NaN      3.0          2.0         3.0         4.0  \n",
       "2788    1.0    NaN      3.0          2.0         4.0         4.0  \n",
       "2791    NaN    NaN      3.0          3.0         NaN         3.0  \n",
       "1597    1.0    NaN      2.0          2.0         2.0         3.0  \n",
       "823     1.0    NaN      2.0          3.0         3.0         4.0  \n",
       "617     NaN    1.0      3.0          2.0         2.0         4.0  \n",
       "619     NaN    3.0      3.0          3.0         2.0         4.0  \n",
       "1194    2.0    NaN      1.0          3.0         2.0         5.0  \n",
       "2177    NaN    2.0      2.0          2.0         3.0         2.0  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.set_option('display.max_columns', None)  # Show all columns\n",
    "pd.set_option('display.max_rows', None)  # Show all rows\n",
    "lpop = lpop.sort_values(by='bard_distance_norm', ascending=True)\n",
    "\n",
    "# 2. Calcular el número de filas que representa el 10%\n",
    "num_rows_10_percent = int(len(lpop) * 0.1)\n",
    "\n",
    "# 3. Seleccionar las primeras filas correspondientes al 10%\n",
    "lpop[(lpop['bard_num_preg']>5)].head(num_rows_10_percent)[pregs]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a230c7c9-09b8-40af-a790-893a354df4ba",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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