violinplot.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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>TransactionID</th>\n",
       "      <th>isFraud</th>\n",
       "      <th>TransactionDT</th>\n",
       "      <th>TransactionAmt</th>\n",
       "      <th>ProductCD</th>\n",
       "      <th>card1</th>\n",
       "      <th>card2</th>\n",
       "      <th>card3</th>\n",
       "      <th>card4</th>\n",
       "      <th>card5</th>\n",
       "      <th>...</th>\n",
       "      <th>V330</th>\n",
       "      <th>V331</th>\n",
       "      <th>V332</th>\n",
       "      <th>V333</th>\n",
       "      <th>V334</th>\n",
       "      <th>V335</th>\n",
       "      <th>V336</th>\n",
       "      <th>V337</th>\n",
       "      <th>V338</th>\n",
       "      <th>V339</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2987000</td>\n",
       "      <td>0</td>\n",
       "      <td>86400</td>\n",
       "      <td>68.5</td>\n",
       "      <td>W</td>\n",
       "      <td>13926</td>\n",
       "      <td>NaN</td>\n",
       "      <td>150.0</td>\n",
       "      <td>discover</td>\n",
       "      <td>142.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2987001</td>\n",
       "      <td>0</td>\n",
       "      <td>86401</td>\n",
       "      <td>29.0</td>\n",
       "      <td>W</td>\n",
       "      <td>2755</td>\n",
       "      <td>404.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>102.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2987002</td>\n",
       "      <td>0</td>\n",
       "      <td>86469</td>\n",
       "      <td>59.0</td>\n",
       "      <td>W</td>\n",
       "      <td>4663</td>\n",
       "      <td>490.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>visa</td>\n",
       "      <td>166.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2987003</td>\n",
       "      <td>0</td>\n",
       "      <td>86499</td>\n",
       "      <td>50.0</td>\n",
       "      <td>W</td>\n",
       "      <td>18132</td>\n",
       "      <td>567.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>117.0</td>\n",
       "      <td>...</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>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2987004</td>\n",
       "      <td>0</td>\n",
       "      <td>86506</td>\n",
       "      <td>50.0</td>\n",
       "      <td>H</td>\n",
       "      <td>4497</td>\n",
       "      <td>514.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>102.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 394 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   TransactionID  isFraud  TransactionDT  TransactionAmt ProductCD  card1  \\\n",
       "0        2987000        0          86400            68.5         W  13926   \n",
       "1        2987001        0          86401            29.0         W   2755   \n",
       "2        2987002        0          86469            59.0         W   4663   \n",
       "3        2987003        0          86499            50.0         W  18132   \n",
       "4        2987004        0          86506            50.0         H   4497   \n",
       "\n",
       "   card2  card3       card4  card5  ... V330  V331  V332  V333  V334 V335  \\\n",
       "0    NaN  150.0    discover  142.0  ...  NaN   NaN   NaN   NaN   NaN  NaN   \n",
       "1  404.0  150.0  mastercard  102.0  ...  NaN   NaN   NaN   NaN   NaN  NaN   \n",
       "2  490.0  150.0        visa  166.0  ...  NaN   NaN   NaN   NaN   NaN  NaN   \n",
       "3  567.0  150.0  mastercard  117.0  ...  NaN   NaN   NaN   NaN   NaN  NaN   \n",
       "4  514.0  150.0  mastercard  102.0  ...  0.0   0.0   0.0   0.0   0.0  0.0   \n",
       "\n",
       "  V336  V337  V338  V339  \n",
       "0  NaN   NaN   NaN   NaN  \n",
       "1  NaN   NaN   NaN   NaN  \n",
       "2  NaN   NaN   NaN   NaN  \n",
       "3  NaN   NaN   NaN   NaN  \n",
       "4  0.0   0.0   0.0   0.0  \n",
       "\n",
       "[5 rows x 394 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transaccions = pd.read_csv('csv/train_transaction.csv')\n",
    "transaccions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>TransactionID</th>\n",
       "      <th>id_01</th>\n",
       "      <th>id_02</th>\n",
       "      <th>id_03</th>\n",
       "      <th>id_04</th>\n",
       "      <th>id_05</th>\n",
       "      <th>id_06</th>\n",
       "      <th>id_07</th>\n",
       "      <th>id_08</th>\n",
       "      <th>id_09</th>\n",
       "      <th>...</th>\n",
       "      <th>id_31</th>\n",
       "      <th>id_32</th>\n",
       "      <th>id_33</th>\n",
       "      <th>id_34</th>\n",
       "      <th>id_35</th>\n",
       "      <th>id_36</th>\n",
       "      <th>id_37</th>\n",
       "      <th>id_38</th>\n",
       "      <th>DeviceType</th>\n",
       "      <th>DeviceInfo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2987004</td>\n",
       "      <td>0.0</td>\n",
       "      <td>70787.0</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>...</td>\n",
       "      <td>samsung browser 6.2</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2220x1080</td>\n",
       "      <td>match_status:2</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>mobile</td>\n",
       "      <td>SAMSUNG SM-G892A Build/NRD90M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2987008</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>98945.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>mobile safari 11.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1334x750</td>\n",
       "      <td>match_status:1</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>mobile</td>\n",
       "      <td>iOS Device</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2987010</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>191631.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>desktop</td>\n",
       "      <td>Windows</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2987011</td>\n",
       "      <td>-5.0</td>\n",
       "      <td>221832.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-6.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>desktop</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2987016</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7460.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 62.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1280x800</td>\n",
       "      <td>match_status:2</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>desktop</td>\n",
       "      <td>MacOS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   TransactionID  id_01     id_02  id_03  id_04  id_05  id_06  id_07  id_08  \\\n",
       "0        2987004    0.0   70787.0    NaN    NaN    NaN    NaN    NaN    NaN   \n",
       "1        2987008   -5.0   98945.0    NaN    NaN    0.0   -5.0    NaN    NaN   \n",
       "2        2987010   -5.0  191631.0    0.0    0.0    0.0    0.0    NaN    NaN   \n",
       "3        2987011   -5.0  221832.0    NaN    NaN    0.0   -6.0    NaN    NaN   \n",
       "4        2987016    0.0    7460.0    0.0    0.0    1.0    0.0    NaN    NaN   \n",
       "\n",
       "   id_09  ...                id_31  id_32      id_33           id_34  id_35  \\\n",
       "0    NaN  ...  samsung browser 6.2   32.0  2220x1080  match_status:2      T   \n",
       "1    NaN  ...   mobile safari 11.0   32.0   1334x750  match_status:1      T   \n",
       "2    0.0  ...          chrome 62.0    NaN        NaN             NaN      F   \n",
       "3    NaN  ...          chrome 62.0    NaN        NaN             NaN      F   \n",
       "4    0.0  ...          chrome 62.0   24.0   1280x800  match_status:2      T   \n",
       "\n",
       "  id_36 id_37  id_38  DeviceType                     DeviceInfo  \n",
       "0     F     T      T      mobile  SAMSUNG SM-G892A Build/NRD90M  \n",
       "1     F     F      T      mobile                     iOS Device  \n",
       "2     F     T      T     desktop                        Windows  \n",
       "3     F     T      T     desktop                            NaN  \n",
       "4     F     T      T     desktop                          MacOS  \n",
       "\n",
       "[5 rows x 41 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "identity = pd.read_csv('csv/train_identity.csv')\n",
    "identity.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "columna TransactionID \n",
      "\n",
      "3153916    1\n",
      "3548654    1\n",
      "3079669    1\n",
      "3077620    1\n",
      "3067379    1\n",
      "          ..\n",
      "3250108    1\n",
      "3146453    1\n",
      "3412695    1\n",
      "3177178    1\n",
      "3147777    1\n",
      "Name: TransactionID, Length: 144233, dtype: int64\n",
      "columna id_01 \n",
      "\n",
      "-5.0     82170\n",
      " 0.0     19555\n",
      "-10.0    11257\n",
      "-20.0    11211\n",
      "-15.0     5674\n",
      "         ...  \n",
      "-47.0        1\n",
      "-54.0        1\n",
      "-86.0        1\n",
      "-28.0        1\n",
      "-57.0        1\n",
      "Name: id_01, Length: 77, dtype: int64\n",
      "columna id_02 \n",
      "\n",
      "1102.0      11\n",
      "696.0       10\n",
      "1116.0       9\n",
      "1117.0       9\n",
      "1120.0       9\n",
      "            ..\n",
      "171228.0     1\n",
      "342457.0     1\n",
      "128226.0     1\n",
      "118383.0     1\n",
      "24576.0      1\n",
      "Name: id_02, Length: 115655, dtype: int64\n",
      "columna id_03 \n",
      "\n",
      " 0.0     63903\n",
      " 1.0       863\n",
      " 3.0       668\n",
      " 2.0       421\n",
      " 5.0       109\n",
      " 4.0       100\n",
      " 6.0        64\n",
      "-5.0        33\n",
      "-6.0        31\n",
      "-4.0        21\n",
      "-7.0        21\n",
      "-10.0       17\n",
      "-8.0        14\n",
      "-1.0        12\n",
      "-2.0        12\n",
      "-3.0         8\n",
      "-11.0        6\n",
      "-9.0         6\n",
      " 7.0         4\n",
      "-13.0        3\n",
      "-12.0        3\n",
      " 9.0         3\n",
      " 8.0         1\n",
      " 10.0        1\n",
      "Name: id_03, dtype: int64\n",
      "columna id_04 \n",
      "\n",
      " 0.0     65739\n",
      "-5.0       132\n",
      "-6.0        98\n",
      "-8.0        64\n",
      "-4.0        51\n",
      "-1.0        43\n",
      "-11.0       35\n",
      "-12.0       34\n",
      "-10.0       30\n",
      "-9.0        26\n",
      "-13.0       24\n",
      "-7.0        21\n",
      "-2.0        15\n",
      "-3.0        10\n",
      "-28.0        2\n",
      "Name: id_04, dtype: int64\n",
      "columna id_05 \n",
      "\n",
      " 0.0     92743\n",
      " 1.0      8293\n",
      " 2.0      4937\n",
      " 3.0      3854\n",
      " 4.0      2941\n",
      "         ...  \n",
      "-35.0        1\n",
      "-34.0        1\n",
      "-38.0        1\n",
      " 48.0        1\n",
      "-39.0        1\n",
      "Name: id_05, Length: 93, dtype: int64\n",
      "columna id_06 \n",
      "\n",
      " 0.0     91325\n",
      "-1.0      4687\n",
      "-5.0      3849\n",
      "-6.0      3257\n",
      "-9.0      2634\n",
      "         ...  \n",
      "-93.0        4\n",
      "-95.0        2\n",
      "-80.0        2\n",
      "-99.0        1\n",
      "-89.0        1\n",
      "Name: id_06, Length: 101, dtype: int64\n",
      "columna id_07 \n",
      "\n",
      " 0.0     409\n",
      " 16.0    245\n",
      " 14.0    228\n",
      " 12.0    208\n",
      " 15.0    186\n",
      "        ... \n",
      "-15.0      1\n",
      " 51.0      1\n",
      " 52.0      1\n",
      "-33.0      1\n",
      " 61.0      1\n",
      "Name: id_07, Length: 84, dtype: int64\n",
      "columna id_08 \n",
      "\n",
      "-100.0    500\n",
      " 0.0      261\n",
      "-34.0     257\n",
      "-33.0     209\n",
      "-32.0     185\n",
      "         ... \n",
      "-98.0       1\n",
      "-65.0       1\n",
      "-90.0       1\n",
      "-97.0       1\n",
      "-93.0       1\n",
      "Name: id_08, Length: 94, dtype: int64\n",
      "columna id_09 \n",
      "\n",
      " 0.0     70378\n",
      " 1.0      1616\n",
      " 3.0       966\n",
      " 2.0       773\n",
      " 4.0       270\n",
      " 5.0       207\n",
      " 6.0       145\n",
      "-6.0        66\n",
      "-5.0        60\n",
      "-4.0        42\n",
      "-10.0       39\n",
      "-7.0        39\n",
      "-1.0        38\n",
      "-8.0        37\n",
      " 7.0        33\n",
      "-3.0        31\n",
      "-2.0        27\n",
      "-9.0        27\n",
      " 8.0        23\n",
      "-11.0       18\n",
      " 9.0        16\n",
      " 10.0       11\n",
      " 11.0        6\n",
      " 12.0        6\n",
      "-17.0        4\n",
      "-12.0        4\n",
      "-23.0        4\n",
      "-22.0        4\n",
      " 13.0        4\n",
      "-13.0        4\n",
      "-21.0        3\n",
      " 16.0        3\n",
      " 15.0        3\n",
      "-31.0        3\n",
      "-19.0        2\n",
      "-15.0        2\n",
      "-26.0        2\n",
      "-18.0        2\n",
      " 17.0        1\n",
      " 25.0        1\n",
      " 14.0        1\n",
      "-30.0        1\n",
      "-14.0        1\n",
      "-24.0        1\n",
      "-20.0        1\n",
      "-36.0        1\n",
      "Name: id_09, dtype: int64\n",
      "columna id_10 \n",
      "\n",
      " 0.0     72879\n",
      "-6.0       295\n",
      "-5.0       247\n",
      "-1.0       200\n",
      "-8.0       147\n",
      "         ...  \n",
      "-58.0        1\n",
      "-51.0        1\n",
      "-59.0        1\n",
      "-50.0        1\n",
      "-53.0        1\n",
      "Name: id_10, Length: 62, dtype: int64\n",
      "columna id_11 \n",
      "\n",
      "100.000000    133162\n",
      "95.080002       1231\n",
      "95.160004        754\n",
      "97.120003        440\n",
      "96.669998        333\n",
      "               ...  \n",
      "97.870003          1\n",
      "97.660004          1\n",
      "95.040001          1\n",
      "91.949997          1\n",
      "94.169998          1\n",
      "Name: id_11, Length: 365, dtype: int64\n",
      "columna id_12 \n",
      "\n",
      "NotFound    123025\n",
      "Found        21208\n",
      "Name: id_12, dtype: int64\n",
      "columna id_13 \n",
      "\n",
      "52.0    58099\n",
      "49.0    26365\n",
      "64.0    14429\n",
      "33.0    10048\n",
      "27.0     3666\n",
      "20.0     2878\n",
      "14.0     2499\n",
      "63.0     1468\n",
      "19.0     1147\n",
      "25.0     1066\n",
      "43.0      842\n",
      "62.0      813\n",
      "18.0      688\n",
      "41.0      654\n",
      "55.0      523\n",
      "11.0      373\n",
      "15.0      372\n",
      "24.0      318\n",
      "35.0      317\n",
      "51.0      196\n",
      "61.0      108\n",
      "44.0       85\n",
      "54.0       67\n",
      "28.0       59\n",
      "39.0       34\n",
      "31.0       29\n",
      "45.0       26\n",
      "38.0       22\n",
      "13.0       21\n",
      "58.0       17\n",
      "36.0       15\n",
      "32.0       10\n",
      "48.0       10\n",
      "56.0        9\n",
      "30.0        7\n",
      "22.0        5\n",
      "53.0        4\n",
      "47.0        3\n",
      "60.0        3\n",
      "17.0        3\n",
      "21.0        3\n",
      "57.0        3\n",
      "46.0        3\n",
      "26.0        2\n",
      "12.0        2\n",
      "23.0        1\n",
      "40.0        1\n",
      "42.0        1\n",
      "34.0        1\n",
      "37.0        1\n",
      "10.0        1\n",
      "59.0        1\n",
      "29.0        1\n",
      "50.0        1\n",
      "Name: id_13, dtype: int64\n",
      "columna id_14 \n",
      "\n",
      "-300.0    44121\n",
      "-360.0    16661\n",
      "-480.0    12891\n",
      "-420.0     4542\n",
      "-600.0      498\n",
      " 60.0       369\n",
      " 0.0        192\n",
      "-240.0      159\n",
      "-180.0      126\n",
      "-540.0      111\n",
      " 480.0       80\n",
      " 540.0       64\n",
      " 600.0       62\n",
      " 120.0       41\n",
      " 180.0       37\n",
      " 420.0       19\n",
      " 330.0       17\n",
      " 270.0       15\n",
      " 240.0       13\n",
      " 300.0       12\n",
      " 720.0        9\n",
      "-660.0        2\n",
      "-120.0        1\n",
      "-210.0        1\n",
      " 360.0        1\n",
      "Name: id_14, dtype: int64\n",
      "columna id_15 \n",
      "\n",
      "Found      67728\n",
      "New        61612\n",
      "Unknown    11645\n",
      "Name: id_15, dtype: int64\n",
      "columna id_16 \n",
      "\n",
      "Found       66324\n",
      "NotFound    63016\n",
      "Name: id_16, dtype: int64\n",
      "columna id_17 \n",
      "\n",
      "166.0    78631\n",
      "225.0    56968\n",
      "102.0      689\n",
      "159.0      352\n",
      "100.0      336\n",
      "         ...  \n",
      "188.0        1\n",
      "154.0        1\n",
      "105.0        1\n",
      "219.0        1\n",
      "125.0        1\n",
      "Name: id_17, Length: 104, dtype: int64\n",
      "columna id_18 \n",
      "\n",
      "15.0    25489\n",
      "13.0    13439\n",
      "12.0     4656\n",
      "18.0      650\n",
      "20.0      339\n",
      "17.0      233\n",
      "26.0       89\n",
      "21.0       78\n",
      "24.0       52\n",
      "11.0       36\n",
      "27.0       32\n",
      "29.0        9\n",
      "23.0        4\n",
      "14.0        3\n",
      "16.0        1\n",
      "28.0        1\n",
      "10.0        1\n",
      "25.0        1\n",
      "Name: id_18, dtype: int64\n",
      "columna id_19 \n",
      "\n",
      "266.0    19849\n",
      "410.0    11318\n",
      "427.0     8808\n",
      "529.0     8122\n",
      "312.0     6227\n",
      "         ...  \n",
      "363.0        1\n",
      "174.0        1\n",
      "386.0        1\n",
      "179.0        1\n",
      "425.0        1\n",
      "Name: id_19, Length: 522, dtype: int64\n",
      "columna id_20 \n",
      "\n",
      "507.0    22311\n",
      "222.0    11065\n",
      "325.0     8133\n",
      "533.0     6611\n",
      "214.0     5664\n",
      "         ...  \n",
      "426.0        1\n",
      "459.0        1\n",
      "221.0        1\n",
      "109.0        1\n",
      "486.0        1\n",
      "Name: id_20, Length: 394, dtype: int64\n",
      "columna id_21 \n",
      "\n",
      "252.0    2542\n",
      "228.0     239\n",
      "255.0     109\n",
      "596.0     103\n",
      "576.0     101\n",
      "         ... \n",
      "431.0       1\n",
      "648.0       1\n",
      "635.0       1\n",
      "637.0       1\n",
      "540.0       1\n",
      "Name: id_21, Length: 490, dtype: int64\n",
      "columna id_22 \n",
      "\n",
      "14.0    4736\n",
      "41.0     321\n",
      "33.0      38\n",
      "17.0       7\n",
      "21.0       7\n",
      "39.0       6\n",
      "35.0       5\n",
      "36.0       5\n",
      "31.0       5\n",
      "12.0       5\n",
      "22.0       5\n",
      "20.0       4\n",
      "26.0       4\n",
      "24.0       4\n",
      "28.0       3\n",
      "42.0       3\n",
      "38.0       2\n",
      "19.0       2\n",
      "40.0       1\n",
      "43.0       1\n",
      "37.0       1\n",
      "23.0       1\n",
      "10.0       1\n",
      "44.0       1\n",
      "18.0       1\n",
      "Name: id_22, dtype: int64\n",
      "columna id_23 \n",
      "\n",
      "IP_PROXY:TRANSPARENT    3489\n",
      "IP_PROXY:ANONYMOUS      1071\n",
      "IP_PROXY:HIDDEN          609\n",
      "Name: id_23, dtype: int64\n",
      "columna id_24 \n",
      "\n",
      "11.0    2817\n",
      "15.0    1594\n",
      "16.0     220\n",
      "18.0      37\n",
      "21.0      33\n",
      "24.0      12\n",
      "17.0       9\n",
      "26.0       8\n",
      "25.0       7\n",
      "19.0       5\n",
      "12.0       4\n",
      "23.0       1\n",
      "Name: id_24, dtype: int64\n",
      "columna id_25 \n",
      "\n",
      "321.0    2494\n",
      "205.0     301\n",
      "426.0     236\n",
      "501.0     103\n",
      "371.0      83\n",
      "         ... \n",
      "543.0       1\n",
      "398.0       1\n",
      "467.0       1\n",
      "342.0       1\n",
      "392.0       1\n",
      "Name: id_25, Length: 341, dtype: int64\n",
      "columna id_26 \n",
      "\n",
      "161.0    824\n",
      "184.0    582\n",
      "142.0    528\n",
      "102.0    451\n",
      "100.0    433\n",
      "        ... \n",
      "101.0      1\n",
      "198.0      1\n",
      "178.0      1\n",
      "115.0      1\n",
      "127.0      1\n",
      "Name: id_26, Length: 95, dtype: int64\n",
      "columna id_27 \n",
      "\n",
      "Found       5155\n",
      "NotFound      14\n",
      "Name: id_27, dtype: int64\n",
      "columna id_28 \n",
      "\n",
      "Found    76232\n",
      "New      64746\n",
      "Name: id_28, dtype: int64\n",
      "columna id_29 \n",
      "\n",
      "Found       74926\n",
      "NotFound    66052\n",
      "Name: id_29, dtype: int64\n",
      "columna id_30 \n",
      "\n",
      "Windows 10          21155\n",
      "Windows 7           13110\n",
      "iOS 11.2.1           3722\n",
      "iOS 11.1.2           3699\n",
      "Android 7.0          2871\n",
      "                    ...  \n",
      "func                   10\n",
      "iOS 11.4.0              5\n",
      "Mac OS X 10_13_5        4\n",
      "Windows                 3\n",
      "iOS 11.4.1              1\n",
      "Name: id_30, Length: 75, dtype: int64\n",
      "columna id_31 \n",
      "\n",
      "chrome 63.0              22000\n",
      "mobile safari 11.0       13423\n",
      "mobile safari generic    11474\n",
      "ie 11.0 for desktop       9030\n",
      "safari generic            8195\n",
      "                         ...  \n",
      "chromium                     1\n",
      "cyberfox                     1\n",
      "seamonkey                    1\n",
      "Inco/Minion                  1\n",
      "M4Tel/M4                     1\n",
      "Name: id_31, Length: 130, dtype: int64\n",
      "columna id_32 \n",
      "\n",
      "24.0    53071\n",
      "32.0    24428\n",
      "16.0       81\n",
      "0.0         6\n",
      "Name: id_32, dtype: int64\n",
      "columna id_33 \n",
      "\n",
      "1920x1080    16874\n",
      "1366x768      8605\n",
      "1334x750      6447\n",
      "2208x1242     4900\n",
      "1440x900      4384\n",
      "             ...  \n",
      "2048x1080        1\n",
      "1062x630         1\n",
      "768x576          1\n",
      "1638x922         1\n",
      "1776x1080        1\n",
      "Name: id_33, Length: 260, dtype: int64\n",
      "columna id_34 \n",
      "\n",
      "match_status:2     60011\n",
      "match_status:1     17376\n",
      "match_status:0       415\n",
      "match_status:-1        3\n",
      "Name: id_34, dtype: int64\n",
      "columna id_35 \n",
      "\n",
      "T    77814\n",
      "F    63171\n",
      "Name: id_35, dtype: int64\n",
      "columna id_36 \n",
      "\n",
      "F    134066\n",
      "T      6919\n",
      "Name: id_36, dtype: int64\n",
      "columna id_37 \n",
      "\n",
      "T    110452\n",
      "F     30533\n",
      "Name: id_37, dtype: int64\n",
      "columna id_38 \n",
      "\n",
      "F    73922\n",
      "T    67063\n",
      "Name: id_38, dtype: int64\n",
      "columna DeviceType \n",
      "\n",
      "desktop    85165\n",
      "mobile     55645\n",
      "Name: DeviceType, dtype: int64\n",
      "columna DeviceInfo \n",
      "\n",
      "Windows                   47722\n",
      "iOS Device                19782\n",
      "MacOS                     12573\n",
      "Trident/7.0                7440\n",
      "rv:11.0                    1901\n",
      "                          ...  \n",
      "NXA8QC116                     1\n",
      "SM-G901F                      1\n",
      "DOMOS                         1\n",
      "LG-V700                       1\n",
      "SM-J330FN Build/NRD90M        1\n",
      "Name: DeviceInfo, Length: 1786, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "for c in identity.columns:\n",
    "    print (\"columna %s \\n\" % c)\n",
    "    print(identity[c].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IP_PROXY:TRANSPARENT    3489\n",
       "IP_PROXY:ANONYMOUS      1071\n",
       "IP_PROXY:HIDDEN          609\n",
       "Name: id_23, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "identity['id_23'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>TransactionID</th>\n",
       "      <th>isFraud</th>\n",
       "      <th>TransactionDT</th>\n",
       "      <th>TransactionAmt</th>\n",
       "      <th>ProductCD</th>\n",
       "      <th>card1</th>\n",
       "      <th>card2</th>\n",
       "      <th>card3</th>\n",
       "      <th>card4</th>\n",
       "      <th>card5</th>\n",
       "      <th>...</th>\n",
       "      <th>id_31</th>\n",
       "      <th>id_32</th>\n",
       "      <th>id_33</th>\n",
       "      <th>id_34</th>\n",
       "      <th>id_35</th>\n",
       "      <th>id_36</th>\n",
       "      <th>id_37</th>\n",
       "      <th>id_38</th>\n",
       "      <th>DeviceType</th>\n",
       "      <th>DeviceInfo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2987004</td>\n",
       "      <td>0</td>\n",
       "      <td>86506</td>\n",
       "      <td>50.000</td>\n",
       "      <td>H</td>\n",
       "      <td>4497</td>\n",
       "      <td>514.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>102.0</td>\n",
       "      <td>...</td>\n",
       "      <td>samsung browser 6.2</td>\n",
       "      <td>32.0</td>\n",
       "      <td>2220x1080</td>\n",
       "      <td>match_status:2</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>mobile</td>\n",
       "      <td>SAMSUNG SM-G892A Build/NRD90M</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2987008</td>\n",
       "      <td>0</td>\n",
       "      <td>86535</td>\n",
       "      <td>15.000</td>\n",
       "      <td>H</td>\n",
       "      <td>2803</td>\n",
       "      <td>100.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>visa</td>\n",
       "      <td>226.0</td>\n",
       "      <td>...</td>\n",
       "      <td>mobile safari 11.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>1334x750</td>\n",
       "      <td>match_status:1</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>mobile</td>\n",
       "      <td>iOS Device</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2987010</td>\n",
       "      <td>0</td>\n",
       "      <td>86549</td>\n",
       "      <td>75.887</td>\n",
       "      <td>C</td>\n",
       "      <td>16496</td>\n",
       "      <td>352.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>134.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>desktop</td>\n",
       "      <td>Windows</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2987011</td>\n",
       "      <td>0</td>\n",
       "      <td>86555</td>\n",
       "      <td>16.495</td>\n",
       "      <td>C</td>\n",
       "      <td>4461</td>\n",
       "      <td>375.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>224.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 62.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>desktop</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2987016</td>\n",
       "      <td>0</td>\n",
       "      <td>86620</td>\n",
       "      <td>30.000</td>\n",
       "      <td>H</td>\n",
       "      <td>1790</td>\n",
       "      <td>555.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>visa</td>\n",
       "      <td>226.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 62.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1280x800</td>\n",
       "      <td>match_status:2</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>T</td>\n",
       "      <td>desktop</td>\n",
       "      <td>MacOS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144228</th>\n",
       "      <td>3577521</td>\n",
       "      <td>0</td>\n",
       "      <td>15810802</td>\n",
       "      <td>48.877</td>\n",
       "      <td>C</td>\n",
       "      <td>12019</td>\n",
       "      <td>305.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>224.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 66.0 for android</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>mobile</td>\n",
       "      <td>F3111 Build/33.3.A.1.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144229</th>\n",
       "      <td>3577526</td>\n",
       "      <td>1</td>\n",
       "      <td>15810876</td>\n",
       "      <td>250.000</td>\n",
       "      <td>R</td>\n",
       "      <td>1214</td>\n",
       "      <td>174.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>visa</td>\n",
       "      <td>226.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 55.0 for android</td>\n",
       "      <td>32.0</td>\n",
       "      <td>855x480</td>\n",
       "      <td>match_status:2</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>mobile</td>\n",
       "      <td>A574BL Build/NMF26F</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144230</th>\n",
       "      <td>3577529</td>\n",
       "      <td>0</td>\n",
       "      <td>15810912</td>\n",
       "      <td>73.838</td>\n",
       "      <td>C</td>\n",
       "      <td>5096</td>\n",
       "      <td>555.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>137.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 65.0 for android</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>mobile</td>\n",
       "      <td>Moto E (4) Plus Build/NMA26.42-152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144231</th>\n",
       "      <td>3577531</td>\n",
       "      <td>0</td>\n",
       "      <td>15810935</td>\n",
       "      <td>400.000</td>\n",
       "      <td>R</td>\n",
       "      <td>6019</td>\n",
       "      <td>583.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>visa</td>\n",
       "      <td>226.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 66.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>2560x1600</td>\n",
       "      <td>match_status:2</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>desktop</td>\n",
       "      <td>MacOS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144232</th>\n",
       "      <td>3577534</td>\n",
       "      <td>0</td>\n",
       "      <td>15811030</td>\n",
       "      <td>67.505</td>\n",
       "      <td>C</td>\n",
       "      <td>5812</td>\n",
       "      <td>408.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>mastercard</td>\n",
       "      <td>224.0</td>\n",
       "      <td>...</td>\n",
       "      <td>chrome 66.0 for android</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>F</td>\n",
       "      <td>F</td>\n",
       "      <td>T</td>\n",
       "      <td>F</td>\n",
       "      <td>mobile</td>\n",
       "      <td>RNE-L03 Build/HUAWEIRNE-L03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>144233 rows × 434 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        TransactionID  isFraud  TransactionDT  TransactionAmt ProductCD  \\\n",
       "0             2987004        0          86506          50.000         H   \n",
       "1             2987008        0          86535          15.000         H   \n",
       "2             2987010        0          86549          75.887         C   \n",
       "3             2987011        0          86555          16.495         C   \n",
       "4             2987016        0          86620          30.000         H   \n",
       "...               ...      ...            ...             ...       ...   \n",
       "144228        3577521        0       15810802          48.877         C   \n",
       "144229        3577526        1       15810876         250.000         R   \n",
       "144230        3577529        0       15810912          73.838         C   \n",
       "144231        3577531        0       15810935         400.000         R   \n",
       "144232        3577534        0       15811030          67.505         C   \n",
       "\n",
       "        card1  card2  card3       card4  card5  ...                    id_31  \\\n",
       "0        4497  514.0  150.0  mastercard  102.0  ...      samsung browser 6.2   \n",
       "1        2803  100.0  150.0        visa  226.0  ...       mobile safari 11.0   \n",
       "2       16496  352.0  117.0  mastercard  134.0  ...              chrome 62.0   \n",
       "3        4461  375.0  185.0  mastercard  224.0  ...              chrome 62.0   \n",
       "4        1790  555.0  150.0        visa  226.0  ...              chrome 62.0   \n",
       "...       ...    ...    ...         ...    ...  ...                      ...   \n",
       "144228  12019  305.0  106.0  mastercard  224.0  ...  chrome 66.0 for android   \n",
       "144229   1214  174.0  150.0        visa  226.0  ...  chrome 55.0 for android   \n",
       "144230   5096  555.0  185.0  mastercard  137.0  ...  chrome 65.0 for android   \n",
       "144231   6019  583.0  150.0        visa  226.0  ...              chrome 66.0   \n",
       "144232   5812  408.0  185.0  mastercard  224.0  ...  chrome 66.0 for android   \n",
       "\n",
       "        id_32      id_33           id_34  id_35 id_36 id_37  id_38  \\\n",
       "0        32.0  2220x1080  match_status:2      T     F     T      T   \n",
       "1        32.0   1334x750  match_status:1      T     F     F      T   \n",
       "2         NaN        NaN             NaN      F     F     T      T   \n",
       "3         NaN        NaN             NaN      F     F     T      T   \n",
       "4        24.0   1280x800  match_status:2      T     F     T      T   \n",
       "...       ...        ...             ...    ...   ...   ...    ...   \n",
       "144228    NaN        NaN             NaN      F     F     T      F   \n",
       "144229   32.0    855x480  match_status:2      T     F     T      F   \n",
       "144230    NaN        NaN             NaN      F     F     T      F   \n",
       "144231   24.0  2560x1600  match_status:2      T     F     T      F   \n",
       "144232    NaN        NaN             NaN      F     F     T      F   \n",
       "\n",
       "        DeviceType                          DeviceInfo  \n",
       "0           mobile       SAMSUNG SM-G892A Build/NRD90M  \n",
       "1           mobile                          iOS Device  \n",
       "2          desktop                             Windows  \n",
       "3          desktop                                 NaN  \n",
       "4          desktop                               MacOS  \n",
       "...            ...                                 ...  \n",
       "144228      mobile             F3111 Build/33.3.A.1.97  \n",
       "144229      mobile                 A574BL Build/NMF26F  \n",
       "144230      mobile  Moto E (4) Plus Build/NMA26.42-152  \n",
       "144231     desktop                               MacOS  \n",
       "144232      mobile         RNE-L03 Build/HUAWEIRNE-L03  \n",
       "\n",
       "[144233 rows x 434 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined = transaccions.merge(identity,on='TransactionID')\n",
    "joined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>id_23</th>\n",
       "      <th>TransactionAmt</th>\n",
       "      <th>isFraud</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>NaN</td>\n",
       "      <td>50.000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>15.000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>NaN</td>\n",
       "      <td>75.887</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>NaN</td>\n",
       "      <td>16.495</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>30.000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144228</th>\n",
       "      <td>NaN</td>\n",
       "      <td>48.877</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144229</th>\n",
       "      <td>NaN</td>\n",
       "      <td>250.000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144230</th>\n",
       "      <td>NaN</td>\n",
       "      <td>73.838</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144231</th>\n",
       "      <td>NaN</td>\n",
       "      <td>400.000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144232</th>\n",
       "      <td>NaN</td>\n",
       "      <td>67.505</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>144233 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       id_23  TransactionAmt  isFraud\n",
       "0        NaN          50.000        0\n",
       "1        NaN          15.000        0\n",
       "2        NaN          75.887        0\n",
       "3        NaN          16.495        0\n",
       "4        NaN          30.000        0\n",
       "...      ...             ...      ...\n",
       "144228   NaN          48.877        0\n",
       "144229   NaN         250.000        1\n",
       "144230   NaN          73.838        0\n",
       "144231   NaN         400.000        0\n",
       "144232   NaN          67.505        0\n",
       "\n",
       "[144233 rows x 3 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Quiero mostrar como se relacionan los amaunts con los ips\n",
    "data = joined[['id_23','TransactionAmt','isFraud']]\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\alejo\\anaconda3\\lib\\site-packages\\pandas\\core\\frame.py:4147: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  return super().fillna(\n"
     ]
    }
   ],
   "source": [
    "data.fillna('IP_PROXY:UNKOWN',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = data.loc[data['TransactionAmt'] < 400]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Tipo de IP')"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3040x1320 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(rc={\"figure.dpi\":200,'figure.figsize':(15.2,6.6)})\n",
    "ax = sns.violinplot(x=\"id_23\", y=\"TransactionAmt\",hue='isFraud', palette='hls',data=data,split=True)\n",
    "ax.set_title(\"Datos estadisticos sobre las cantidades pagadas segun el tipo de IP\",fontsize=15)\n",
    "ax.set_ylabel(\"Cantidad de $USD\",fontsize=14)\n",
    "ax.set_xlabel(\"Tipo de IP\",fontsize=14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}