S8_clase1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5853d483",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "59b9fe16",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/jamc88/TSMCI-Analisis-de-datos-con-Python/main/Datos/deuda_2022.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2e47ba5a",
   "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",
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       "\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>anio</th>\n",
       "      <th>trimestre</th>\n",
       "      <th>mes</th>\n",
       "      <th>no_registro</th>\n",
       "      <th>tipo_deuda</th>\n",
       "      <th>detalle_tipo_deuda</th>\n",
       "      <th>acreedor</th>\n",
       "      <th>concepto</th>\n",
       "      <th>inicio_credito</th>\n",
       "      <th>fin_credito</th>\n",
       "      <th>...</th>\n",
       "      <th>disposicion_inicial_credito</th>\n",
       "      <th>colocacion_periodo</th>\n",
       "      <th>amortizaciones_periodo</th>\n",
       "      <th>intereses_periodo</th>\n",
       "      <th>pago_servicio_deuda</th>\n",
       "      <th>saldo_periodo</th>\n",
       "      <th>endeudamiento_periodo</th>\n",
       "      <th>tasa</th>\n",
       "      <th>sobretasa</th>\n",
       "      <th>tasa_final</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>145/2010</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>CI BANCO</td>\n",
       "      <td>BONO GDFCB 10-2</td>\n",
       "      <td>25/06/10</td>\n",
       "      <td>12/06/20</td>\n",
       "      <td>...</td>\n",
       "      <td>2.520951e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.013680e+08</td>\n",
       "      <td>2.013680e+08</td>\n",
       "      <td>2.520951e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>224/2007</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca Comercial</td>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>BANCOMER 3,457</td>\n",
       "      <td>30/08/07</td>\n",
       "      <td>27/07/37</td>\n",
       "      <td>...</td>\n",
       "      <td>3.457974e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>14809395.11</td>\n",
       "      <td>2.860966e+08</td>\n",
       "      <td>3.009060e+08</td>\n",
       "      <td>3.389146e+09</td>\n",
       "      <td>-1.480940e+07</td>\n",
       "      <td>TIIE</td>\n",
       "      <td>0.35</td>\n",
       "      <td>TIIE+0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>225/2007</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca Comercial</td>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>BANCOMER 7000</td>\n",
       "      <td>31/08/07</td>\n",
       "      <td>27/08/40</td>\n",
       "      <td>...</td>\n",
       "      <td>7.000000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>108919450.9</td>\n",
       "      <td>5.809492e+08</td>\n",
       "      <td>6.898686e+08</td>\n",
       "      <td>6.371209e+09</td>\n",
       "      <td>-1.089195e+08</td>\n",
       "      <td>8.91</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>226/2007</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca Comercial</td>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>BANCOMER 4,700</td>\n",
       "      <td>31/08/07</td>\n",
       "      <td>27/07/37</td>\n",
       "      <td>...</td>\n",
       "      <td>4.700000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>20128593.44</td>\n",
       "      <td>4.018697e+08</td>\n",
       "      <td>4.219983e+08</td>\n",
       "      <td>4.606450e+09</td>\n",
       "      <td>-2.012859e+07</td>\n",
       "      <td>8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>513/2008</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca de Desarrollo</td>\n",
       "      <td>BANOBRAS</td>\n",
       "      <td>BANOBRAS  1,914</td>\n",
       "      <td>26/12/08</td>\n",
       "      <td>25/10/19</td>\n",
       "      <td>...</td>\n",
       "      <td>1.914681e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>320373500.5</td>\n",
       "      <td>2.445093e+07</td>\n",
       "      <td>3.448244e+08</td>\n",
       "      <td>1.277433e+08</td>\n",
       "      <td>-3.203735e+08</td>\n",
       "      <td>TIIE</td>\n",
       "      <td>0.97</td>\n",
       "      <td>TIIE+0.97</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",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>665</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-1014157</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GDFECB 14</td>\n",
       "      <td>1414972800</td>\n",
       "      <td>1729468800</td>\n",
       "      <td>...</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.114167e+07</td>\n",
       "      <td>8.114167e+07</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>666</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-0915121</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GDFECB 15-2</td>\n",
       "      <td>1443139200</td>\n",
       "      <td>1757635200</td>\n",
       "      <td>...</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>667</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-0917056</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GCDMXCB 17X</td>\n",
       "      <td>1505779200</td>\n",
       "      <td>1.84E+09</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>668</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-1118104</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GCDMXCB 18V</td>\n",
       "      <td>1542758400</td>\n",
       "      <td>1857254400</td>\n",
       "      <td>...</td>\n",
       "      <td>1.100000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.522183e+07</td>\n",
       "      <td>5.522183e+07</td>\n",
       "      <td>1.100000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>669</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>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>1751561280</td>\n",
       "      <td>1.918811e+09</td>\n",
       "      <td>3.670372e+09</td>\n",
       "      <td>9.101621e+10</td>\n",
       "      <td>-1.751561e+09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>670 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       anio  trimestre        mes  no_registro   tipo_deuda   \n",
       "0    2018.0        4.0  Diciembre     145/2010  Largo Plazo  \\\n",
       "1    2018.0        4.0  Diciembre     224/2007  Largo Plazo   \n",
       "2    2018.0        4.0  Diciembre     225/2007  Largo Plazo   \n",
       "3    2018.0        4.0  Diciembre     226/2007  Largo Plazo   \n",
       "4    2018.0        4.0  Diciembre     513/2008  Largo Plazo   \n",
       "..      ...        ...        ...          ...          ...   \n",
       "665  2022.0        2.0      Junio  P09-1014157  Largo Plazo   \n",
       "666  2022.0        2.0      Junio  P09-0915121  Largo Plazo   \n",
       "667  2022.0        2.0      Junio  P09-0917056  Largo Plazo   \n",
       "668  2022.0        2.0      Junio  P09-1118104  Largo Plazo   \n",
       "669     NaN        NaN        NaN          NaN          NaN   \n",
       "\n",
       "       detalle_tipo_deuda  acreedor          concepto inicio_credito   \n",
       "0    Mercado de Capitales  CI BANCO   BONO GDFCB 10-2       25/06/10  \\\n",
       "1         Banca Comercial  BANCOMER    BANCOMER 3,457       30/08/07   \n",
       "2         Banca Comercial  BANCOMER     BANCOMER 7000       31/08/07   \n",
       "3         Banca Comercial  BANCOMER    BANCOMER 4,700       31/08/07   \n",
       "4     Banca de Desarrollo  BANOBRAS   BANOBRAS  1,914       26/12/08   \n",
       "..                    ...       ...               ...            ...   \n",
       "665  Mercado de Capitales  EVERCORE    BONO GDFECB 14     1414972800   \n",
       "666  Mercado de Capitales  EVERCORE  BONO GDFECB 15-2     1443139200   \n",
       "667  Mercado de Capitales  EVERCORE  BONO GCDMXCB 17X     1505779200   \n",
       "668  Mercado de Capitales  EVERCORE  BONO GCDMXCB 18V     1542758400   \n",
       "669                   NaN       NaN               NaN            NaN   \n",
       "\n",
       "    fin_credito  ...  disposicion_inicial_credito  colocacion_periodo   \n",
       "0      12/06/20  ...                 2.520951e+09                   0  \\\n",
       "1      27/07/37  ...                 3.457974e+09                   0   \n",
       "2      27/08/40  ...                 7.000000e+09                   0   \n",
       "3      27/07/37  ...                 4.700000e+09                   0   \n",
       "4      25/10/19  ...                 1.914681e+09                   0   \n",
       "..          ...  ...                          ...                 ...   \n",
       "665  1729468800  ...                 2.500000e+09                   0   \n",
       "666  1757635200  ...                 2.500000e+09                   0   \n",
       "667    1.84E+09  ...                 2.000000e+09                   0   \n",
       "668  1857254400  ...                 1.100000e+09                   0   \n",
       "669         NaN  ...                          NaN                   0   \n",
       "\n",
       "     amortizaciones_periodo  intereses_periodo pago_servicio_deuda   \n",
       "0                         0       2.013680e+08        2.013680e+08  \\\n",
       "1               14809395.11       2.860966e+08        3.009060e+08   \n",
       "2               108919450.9       5.809492e+08        6.898686e+08   \n",
       "3               20128593.44       4.018697e+08        4.219983e+08   \n",
       "4               320373500.5       2.445093e+07        3.448244e+08   \n",
       "..                      ...                ...                 ...   \n",
       "665                       0       8.114167e+07        8.114167e+07   \n",
       "666                       0       0.000000e+00        0.000000e+00   \n",
       "667                       0       0.000000e+00        0.000000e+00   \n",
       "668                       0       5.522183e+07        5.522183e+07   \n",
       "669              1751561280       1.918811e+09        3.670372e+09   \n",
       "\n",
       "     saldo_periodo  endeudamiento_periodo  tasa  sobretasa tasa_final  \n",
       "0     2.520951e+09           0.000000e+00   7.9        NaN        7.9  \n",
       "1     3.389146e+09          -1.480940e+07  TIIE       0.35  TIIE+0.35  \n",
       "2     6.371209e+09          -1.089195e+08  8.91        NaN       8.91  \n",
       "3     4.606450e+09          -2.012859e+07   8.8        NaN        8.8  \n",
       "4     1.277433e+08          -3.203735e+08  TIIE       0.97  TIIE+0.97  \n",
       "..             ...                    ...   ...        ...        ...  \n",
       "665   2.500000e+09           0.000000e+00  6.42        NaN       6.42  \n",
       "666   2.500000e+09           0.000000e+00   6.7        NaN        6.7  \n",
       "667   2.000000e+09           0.000000e+00   7.6        NaN        7.6  \n",
       "668   1.100000e+09           0.000000e+00  9.93        NaN       9.93  \n",
       "669   9.101621e+10          -1.751561e+09   NaN        NaN        NaN  \n",
       "\n",
       "[670 rows x 22 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7f52ccb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.drop(669)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8e455fb0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 669 entries, 0 to 668\n",
      "Data columns (total 22 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   anio                         669 non-null    float64\n",
      " 1   trimestre                    669 non-null    float64\n",
      " 2   mes                          669 non-null    object \n",
      " 3   no_registro                  669 non-null    object \n",
      " 4   tipo_deuda                   669 non-null    object \n",
      " 5   detalle_tipo_deuda           669 non-null    object \n",
      " 6   acreedor                     669 non-null    object \n",
      " 7   concepto                     669 non-null    object \n",
      " 8   inicio_credito               669 non-null    object \n",
      " 9   fin_credito                  669 non-null    object \n",
      " 10  dias_contrato                669 non-null    float64\n",
      " 11  dias_restantes_contrato      669 non-null    int64  \n",
      " 12  disposicion_inicial_credito  669 non-null    float64\n",
      " 13  colocacion_periodo           669 non-null    int64  \n",
      " 14  amortizaciones_periodo       669 non-null    object \n",
      " 15  intereses_periodo            669 non-null    float64\n",
      " 16  pago_servicio_deuda          669 non-null    float64\n",
      " 17  saldo_periodo                669 non-null    float64\n",
      " 18  endeudamiento_periodo        669 non-null    float64\n",
      " 19  tasa                         669 non-null    object \n",
      " 20  sobretasa                    354 non-null    object \n",
      " 21  tasa_final                   669 non-null    object \n",
      "dtypes: float64(8), int64(2), object(12)\n",
      "memory usage: 115.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "bcbe069b",
   "metadata": {},
   "outputs": [],
   "source": [
    "periods = pd.PeriodIndex(year=df.pop('anio'),\n",
    "                         quarter=df.pop('trimestre'),\n",
    "                         name='Fecha')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6cc7445e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PeriodIndex(['2018Q4', '2018Q4', '2018Q4', '2018Q4', '2018Q4', '2018Q4',\n",
       "             '2018Q4', '2018Q4', '2018Q4', '2018Q4',\n",
       "             ...\n",
       "             '2022Q2', '2022Q2', '2022Q2', '2022Q2', '2022Q2', '2022Q2',\n",
       "             '2022Q2', '2022Q2', '2022Q2', '2022Q2'],\n",
       "            dtype='period[Q-DEC]', name='Fecha', length=669)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "periods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c316d7e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.index = periods.to_timestamp('D')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d862bff9",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>mes</th>\n",
       "      <th>no_registro</th>\n",
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       "      <th>Fecha</th>\n",
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       "      <th>2018-10-01</th>\n",
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       "      <td>145/2010</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
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       "      <td>BONO GDFCB 10-2</td>\n",
       "      <td>25/06/10</td>\n",
       "      <td>12/06/20</td>\n",
       "      <td>3640.0</td>\n",
       "      <td>529</td>\n",
       "      <td>2.520951e+09</td>\n",
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       "      <th>2018-10-01</th>\n",
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       "      <td>14809395.11</td>\n",
       "      <td>2.860966e+08</td>\n",
       "      <td>3.009060e+08</td>\n",
       "      <td>3.389146e+09</td>\n",
       "      <td>-1.480940e+07</td>\n",
       "      <td>TIIE</td>\n",
       "      <td>0.35</td>\n",
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       "      <th>2018-10-01</th>\n",
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       "      <th>2018-10-01</th>\n",
       "      <td>Diciembre</td>\n",
       "      <td>226/2007</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca Comercial</td>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>BANCOMER 4,700</td>\n",
       "      <td>31/08/07</td>\n",
       "      <td>27/07/37</td>\n",
       "      <td>10923.0</td>\n",
       "      <td>6783</td>\n",
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       "      <th>2018-10-01</th>\n",
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       "      <th>2022-04-01</th>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-1113146</td>\n",
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       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
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       "      <td>1385596800</td>\n",
       "      <td>1700092800</td>\n",
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       "      <td>504</td>\n",
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       "      <td>0.000000e+00</td>\n",
       "      <td>7.05</td>\n",
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       "      <td>P09-1014157</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
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       "      <td>844</td>\n",
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       "      <td>2.500000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.42</td>\n",
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       "    <tr>\n",
       "      <th>2022-04-01</th>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-0915121</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
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       "      <td>1443139200</td>\n",
       "      <td>1757635200</td>\n",
       "      <td>3640.0</td>\n",
       "      <td>1170</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0.000000e+00</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.7</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2022-04-01</th>\n",
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       "      <td>P09-0917056</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GCDMXCB 17X</td>\n",
       "      <td>1505779200</td>\n",
       "      <td>1.84E+09</td>\n",
       "      <td>3822.0</td>\n",
       "      <td>2077</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.6</td>\n",
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       "    <tr>\n",
       "      <th>2022-04-01</th>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-1118104</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GCDMXCB 18V</td>\n",
       "      <td>1542758400</td>\n",
       "      <td>1857254400</td>\n",
       "      <td>3640.0</td>\n",
       "      <td>2323</td>\n",
       "      <td>1.100000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>5.522183e+07</td>\n",
       "      <td>1.100000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.93</td>\n",
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      ],
      "text/plain": [
       "                  mes  no_registro   tipo_deuda    detalle_tipo_deuda   \n",
       "Fecha                                                                   \n",
       "2018-10-01  Diciembre     145/2010  Largo Plazo  Mercado de Capitales  \\\n",
       "2018-10-01  Diciembre     224/2007  Largo Plazo       Banca Comercial   \n",
       "2018-10-01  Diciembre     225/2007  Largo Plazo       Banca Comercial   \n",
       "2018-10-01  Diciembre     226/2007  Largo Plazo       Banca Comercial   \n",
       "2018-10-01  Diciembre     513/2008  Largo Plazo   Banca de Desarrollo   \n",
       "...               ...          ...          ...                   ...   \n",
       "2022-04-01      Junio  P09-1113146  Largo Plazo  Mercado de Capitales   \n",
       "2022-04-01      Junio  P09-1014157  Largo Plazo  Mercado de Capitales   \n",
       "2022-04-01      Junio  P09-0915121  Largo Plazo  Mercado de Capitales   \n",
       "2022-04-01      Junio  P09-0917056  Largo Plazo  Mercado de Capitales   \n",
       "2022-04-01      Junio  P09-1118104  Largo Plazo  Mercado de Capitales   \n",
       "\n",
       "            acreedor          concepto inicio_credito fin_credito   \n",
       "Fecha                                                               \n",
       "2018-10-01  CI BANCO   BONO GDFCB 10-2       25/06/10    12/06/20  \\\n",
       "2018-10-01  BANCOMER    BANCOMER 3,457       30/08/07    27/07/37   \n",
       "2018-10-01  BANCOMER     BANCOMER 7000       31/08/07    27/08/40   \n",
       "2018-10-01  BANCOMER    BANCOMER 4,700       31/08/07    27/07/37   \n",
       "2018-10-01  BANOBRAS   BANOBRAS  1,914       26/12/08    25/10/19   \n",
       "...              ...               ...            ...         ...   \n",
       "2022-04-01  EVERCORE    BONO GDFECB 13     1385596800  1700092800   \n",
       "2022-04-01  EVERCORE    BONO GDFECB 14     1414972800  1729468800   \n",
       "2022-04-01  EVERCORE  BONO GDFECB 15-2     1443139200  1757635200   \n",
       "2022-04-01  EVERCORE  BONO GCDMXCB 17X     1505779200    1.84E+09   \n",
       "2022-04-01  EVERCORE  BONO GCDMXCB 18V     1542758400  1857254400   \n",
       "\n",
       "            dias_contrato  dias_restantes_contrato   \n",
       "Fecha                                                \n",
       "2018-10-01         3640.0                      529  \\\n",
       "2018-10-01        10924.0                     6783   \n",
       "2018-10-01        12050.0                     7910   \n",
       "2018-10-01        10923.0                     6783   \n",
       "2018-10-01         3955.0                      298   \n",
       "...                   ...                      ...   \n",
       "2022-04-01         3640.0                      504   \n",
       "2022-04-01         3640.0                      844   \n",
       "2022-04-01         3640.0                     1170   \n",
       "2022-04-01         3822.0                     2077   \n",
       "2022-04-01         3640.0                     2323   \n",
       "\n",
       "            disposicion_inicial_credito  colocacion_periodo   \n",
       "Fecha                                                         \n",
       "2018-10-01                 2.520951e+09                   0  \\\n",
       "2018-10-01                 3.457974e+09                   0   \n",
       "2018-10-01                 7.000000e+09                   0   \n",
       "2018-10-01                 4.700000e+09                   0   \n",
       "2018-10-01                 1.914681e+09                   0   \n",
       "...                                 ...                 ...   \n",
       "2022-04-01                 2.126875e+09                   0   \n",
       "2022-04-01                 2.500000e+09                   0   \n",
       "2022-04-01                 2.500000e+09                   0   \n",
       "2022-04-01                 2.000000e+09                   0   \n",
       "2022-04-01                 1.100000e+09                   0   \n",
       "\n",
       "           amortizaciones_periodo  intereses_periodo  pago_servicio_deuda   \n",
       "Fecha                                                                       \n",
       "2018-10-01                      0       2.013680e+08         2.013680e+08  \\\n",
       "2018-10-01            14809395.11       2.860966e+08         3.009060e+08   \n",
       "2018-10-01            108919450.9       5.809492e+08         6.898686e+08   \n",
       "2018-10-01            20128593.44       4.018697e+08         4.219983e+08   \n",
       "2018-10-01            320373500.5       2.445093e+07         3.448244e+08   \n",
       "...                           ...                ...                  ...   \n",
       "2022-04-01                      0       7.580537e+07         7.580537e+07   \n",
       "2022-04-01                      0       8.114167e+07         8.114167e+07   \n",
       "2022-04-01                      0       0.000000e+00         0.000000e+00   \n",
       "2022-04-01                      0       0.000000e+00         0.000000e+00   \n",
       "2022-04-01                      0       5.522183e+07         5.522183e+07   \n",
       "\n",
       "            saldo_periodo  endeudamiento_periodo  tasa sobretasa tasa_final  \n",
       "Fecha                                                                        \n",
       "2018-10-01   2.520951e+09           0.000000e+00   7.9       NaN        7.9  \n",
       "2018-10-01   3.389146e+09          -1.480940e+07  TIIE      0.35  TIIE+0.35  \n",
       "2018-10-01   6.371209e+09          -1.089195e+08  8.91       NaN       8.91  \n",
       "2018-10-01   4.606450e+09          -2.012859e+07   8.8       NaN        8.8  \n",
       "2018-10-01   1.277433e+08          -3.203735e+08  TIIE      0.97  TIIE+0.97  \n",
       "...                   ...                    ...   ...       ...        ...  \n",
       "2022-04-01   2.126875e+09           0.000000e+00  7.05       NaN       7.05  \n",
       "2022-04-01   2.500000e+09           0.000000e+00  6.42       NaN       6.42  \n",
       "2022-04-01   2.500000e+09           0.000000e+00   6.7       NaN        6.7  \n",
       "2022-04-01   2.000000e+09           0.000000e+00   7.6       NaN        7.6  \n",
       "2022-04-01   1.100000e+09           0.000000e+00  9.93       NaN       9.93  \n",
       "\n",
       "[669 rows x 20 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "72b6c142",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>no_registro</th>\n",
       "      <th>tipo_deuda</th>\n",
       "      <th>detalle_tipo_deuda</th>\n",
       "      <th>acreedor</th>\n",
       "      <th>concepto</th>\n",
       "      <th>inicio_credito</th>\n",
       "      <th>fin_credito</th>\n",
       "      <th>dias_contrato</th>\n",
       "      <th>dias_restantes_contrato</th>\n",
       "      <th>disposicion_inicial_credito</th>\n",
       "      <th>colocacion_periodo</th>\n",
       "      <th>amortizaciones_periodo</th>\n",
       "      <th>intereses_periodo</th>\n",
       "      <th>pago_servicio_deuda</th>\n",
       "      <th>saldo_periodo</th>\n",
       "      <th>endeudamiento_periodo</th>\n",
       "      <th>tasa</th>\n",
       "      <th>sobretasa</th>\n",
       "      <th>tasa_final</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mes</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Diciembre</th>\n",
       "      <td>145/2010224/2007225/2007226/2007513/2008562/20...</td>\n",
       "      <td>Largo PlazoLargo PlazoLargo PlazoLargo PlazoLa...</td>\n",
       "      <td>Mercado de CapitalesBanca ComercialBanca Comer...</td>\n",
       "      <td>CI BANCOBANCOMERBANCOMERBANCOMERBANOBRASBANOBR...</td>\n",
       "      <td>BONO GDFCB 10-2BANCOMER 3,457BANCOMER 7000BANC...</td>\n",
       "      <td>25/06/1030/08/0731/08/0731/08/0726/12/0828/12/...</td>\n",
       "      <td>12/06/2027/07/3727/08/4027/07/3725/10/1925/10/...</td>\n",
       "      <td>1028363.0</td>\n",
       "      <td>627896</td>\n",
       "      <td>4.282913e+11</td>\n",
       "      <td>37980211028</td>\n",
       "      <td>014809395.11108919450.920128593.44320373500.59...</td>\n",
       "      <td>2.557587e+10</td>\n",
       "      <td>4.708851e+10</td>\n",
       "      <td>3.564528e+11</td>\n",
       "      <td>1.659503e+10</td>\n",
       "      <td>7.9TIIE8.918.8TIIE9.137.67.097.055.745.75TIIE8...</td>\n",
       "      <td>0.350.970.880.380.340.530.350.120.880.320.420....</td>\n",
       "      <td>7.9TIIE+0.358.918.8TIIE+0.979.137.67.977.055.7...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Junio</th>\n",
       "      <td>225/2007226/2007233/2007262/2007721/2011P09-09...</td>\n",
       "      <td>Largo PlazoLargo PlazoLargo PlazoLargo PlazoLa...</td>\n",
       "      <td>Banca ComercialBanca ComercialBanca ComercialB...</td>\n",
       "      <td>BANCOMERBANCOMERHSBCBANOBRASBANAMEXEVERCOREEVE...</td>\n",
       "      <td>BANCOMER 7000BANCOMER 4,700HSBC 7,000BANOBRAS ...</td>\n",
       "      <td>31/08/0731/08/0707/09/0717/10/0729/12/1125/09/...</td>\n",
       "      <td>27/08/4027/07/3725/09/4725/10/4728/12/2618/09/...</td>\n",
       "      <td>1017128.0</td>\n",
       "      <td>596015</td>\n",
       "      <td>4.214736e+11</td>\n",
       "      <td>0</td>\n",
       "      <td>29119959.165996937.340020209581230333333.30000...</td>\n",
       "      <td>1.012902e+10</td>\n",
       "      <td>1.982505e+10</td>\n",
       "      <td>3.442059e+11</td>\n",
       "      <td>-9.636694e+09</td>\n",
       "      <td>8.918.8TIIETIIETIIETIIE6.77.77.097.026.855.745...</td>\n",
       "      <td>0.530.53TIIE-1.8150.120.880.880.880.410.420.35...</td>\n",
       "      <td>8.918.8TIIE+0.53TIIE+0.53TIIE+TIIE-1.815TIIE+0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Marzo</th>\n",
       "      <td>226/2007260/2007261/2007P09-0915121P09-1012161...</td>\n",
       "      <td>Largo PlazoLargo PlazoLargo PlazoLargo PlazoLa...</td>\n",
       "      <td>Banca ComercialBanca de DesarrolloBanca de Des...</td>\n",
       "      <td>BANCOMERBANOBRASBANOBRASEVERCOREBANOBRASEVERCO...</td>\n",
       "      <td>BANCOMER 4,700BANOBRAS  4,806BANOBRAS  4,459BO...</td>\n",
       "      <td>31/08/0717/10/0717/10/0725/09/1507/11/1303/11/...</td>\n",
       "      <td>27/07/3726/10/3725/10/4018/09/2025/11/3221/10/...</td>\n",
       "      <td>1011668.0</td>\n",
       "      <td>612001</td>\n",
       "      <td>4.175707e+11</td>\n",
       "      <td>0</td>\n",
       "      <td>5701204.945529106.058424811.2300002618681.8837...</td>\n",
       "      <td>6.059882e+09</td>\n",
       "      <td>1.126779e+10</td>\n",
       "      <td>3.512472e+11</td>\n",
       "      <td>-5.205636e+09</td>\n",
       "      <td>8.8TIIETIIETIIE7.76.426.855.96TIIETIIETIIE7.63...</td>\n",
       "      <td>0.350.350.120.880.910.360.410.420.970.35TIIE-1...</td>\n",
       "      <td>8.8TIIE+0.35TIIE+0.35TIIE+0.128.586.426.856.87...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Septiembre</th>\n",
       "      <td>145/2010224/2007226/2007329/2007513/2008562/20...</td>\n",
       "      <td>Largo PlazoLargo PlazoLargo PlazoLargo PlazoLa...</td>\n",
       "      <td>Mercado de CapitalesBanca ComercialBanca Comer...</td>\n",
       "      <td>CI BANCOBANCOMERBANCOMERCI BANCOBANOBRASBANOBR...</td>\n",
       "      <td>BONO GDFCB 10-2BANCOMER 3,457BANCOMER 4,700BON...</td>\n",
       "      <td>25/06/1030/08/0731/08/0717/12/0726/12/0828/12/...</td>\n",
       "      <td>12/06/2027/07/3727/07/3722/11/2725/10/1925/10/...</td>\n",
       "      <td>754796.0</td>\n",
       "      <td>445594</td>\n",
       "      <td>3.134070e+11</td>\n",
       "      <td>8796288493</td>\n",
       "      <td>04641050.166308009.96051097322.019027777.90035...</td>\n",
       "      <td>1.072750e+10</td>\n",
       "      <td>2.228598e+10</td>\n",
       "      <td>2.572368e+11</td>\n",
       "      <td>-2.702309e+09</td>\n",
       "      <td>7.9TIIE8.88.65TIIE9.137.69.935.975.96TIIE5.745...</td>\n",
       "      <td>0.350.970.910.910.320.410.380.340.530.350.53TI...</td>\n",
       "      <td>7.9TIIE+0.358.88.65TIIE+0.979.137.69.936.886.8...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  no_registro   \n",
       "mes                                                             \n",
       "Diciembre   145/2010224/2007225/2007226/2007513/2008562/20...  \\\n",
       "Junio       225/2007226/2007233/2007262/2007721/2011P09-09...   \n",
       "Marzo       226/2007260/2007261/2007P09-0915121P09-1012161...   \n",
       "Septiembre  145/2010224/2007226/2007329/2007513/2008562/20...   \n",
       "\n",
       "                                                   tipo_deuda   \n",
       "mes                                                             \n",
       "Diciembre   Largo PlazoLargo PlazoLargo PlazoLargo PlazoLa...  \\\n",
       "Junio       Largo PlazoLargo PlazoLargo PlazoLargo PlazoLa...   \n",
       "Marzo       Largo PlazoLargo PlazoLargo PlazoLargo PlazoLa...   \n",
       "Septiembre  Largo PlazoLargo PlazoLargo PlazoLargo PlazoLa...   \n",
       "\n",
       "                                           detalle_tipo_deuda   \n",
       "mes                                                             \n",
       "Diciembre   Mercado de CapitalesBanca ComercialBanca Comer...  \\\n",
       "Junio       Banca ComercialBanca ComercialBanca ComercialB...   \n",
       "Marzo       Banca ComercialBanca de DesarrolloBanca de Des...   \n",
       "Septiembre  Mercado de CapitalesBanca ComercialBanca Comer...   \n",
       "\n",
       "                                                     acreedor   \n",
       "mes                                                             \n",
       "Diciembre   CI BANCOBANCOMERBANCOMERBANCOMERBANOBRASBANOBR...  \\\n",
       "Junio       BANCOMERBANCOMERHSBCBANOBRASBANAMEXEVERCOREEVE...   \n",
       "Marzo       BANCOMERBANOBRASBANOBRASEVERCOREBANOBRASEVERCO...   \n",
       "Septiembre  CI BANCOBANCOMERBANCOMERCI BANCOBANOBRASBANOBR...   \n",
       "\n",
       "                                                     concepto   \n",
       "mes                                                             \n",
       "Diciembre   BONO GDFCB 10-2BANCOMER 3,457BANCOMER 7000BANC...  \\\n",
       "Junio       BANCOMER 7000BANCOMER 4,700HSBC 7,000BANOBRAS ...   \n",
       "Marzo       BANCOMER 4,700BANOBRAS  4,806BANOBRAS  4,459BO...   \n",
       "Septiembre  BONO GDFCB 10-2BANCOMER 3,457BANCOMER 4,700BON...   \n",
       "\n",
       "                                               inicio_credito   \n",
       "mes                                                             \n",
       "Diciembre   25/06/1030/08/0731/08/0731/08/0726/12/0828/12/...  \\\n",
       "Junio       31/08/0731/08/0707/09/0717/10/0729/12/1125/09/...   \n",
       "Marzo       31/08/0717/10/0717/10/0725/09/1507/11/1303/11/...   \n",
       "Septiembre  25/06/1030/08/0731/08/0717/12/0726/12/0828/12/...   \n",
       "\n",
       "                                                  fin_credito  dias_contrato   \n",
       "mes                                                                            \n",
       "Diciembre   12/06/2027/07/3727/08/4027/07/3725/10/1925/10/...      1028363.0  \\\n",
       "Junio       27/08/4027/07/3725/09/4725/10/4728/12/2618/09/...      1017128.0   \n",
       "Marzo       27/07/3726/10/3725/10/4018/09/2025/11/3221/10/...      1011668.0   \n",
       "Septiembre  12/06/2027/07/3727/07/3722/11/2725/10/1925/10/...       754796.0   \n",
       "\n",
       "            dias_restantes_contrato  disposicion_inicial_credito   \n",
       "mes                                                                \n",
       "Diciembre                    627896                 4.282913e+11  \\\n",
       "Junio                        596015                 4.214736e+11   \n",
       "Marzo                        612001                 4.175707e+11   \n",
       "Septiembre                   445594                 3.134070e+11   \n",
       "\n",
       "            colocacion_periodo   \n",
       "mes                              \n",
       "Diciembre          37980211028  \\\n",
       "Junio                        0   \n",
       "Marzo                        0   \n",
       "Septiembre          8796288493   \n",
       "\n",
       "                                       amortizaciones_periodo   \n",
       "mes                                                             \n",
       "Diciembre   014809395.11108919450.920128593.44320373500.59...  \\\n",
       "Junio       29119959.165996937.340020209581230333333.30000...   \n",
       "Marzo       5701204.945529106.058424811.2300002618681.8837...   \n",
       "Septiembre  04641050.166308009.96051097322.019027777.90035...   \n",
       "\n",
       "            intereses_periodo  pago_servicio_deuda  saldo_periodo   \n",
       "mes                                                                 \n",
       "Diciembre        2.557587e+10         4.708851e+10   3.564528e+11  \\\n",
       "Junio            1.012902e+10         1.982505e+10   3.442059e+11   \n",
       "Marzo            6.059882e+09         1.126779e+10   3.512472e+11   \n",
       "Septiembre       1.072750e+10         2.228598e+10   2.572368e+11   \n",
       "\n",
       "            endeudamiento_periodo   \n",
       "mes                                 \n",
       "Diciembre            1.659503e+10  \\\n",
       "Junio               -9.636694e+09   \n",
       "Marzo               -5.205636e+09   \n",
       "Septiembre          -2.702309e+09   \n",
       "\n",
       "                                                         tasa   \n",
       "mes                                                             \n",
       "Diciembre   7.9TIIE8.918.8TIIE9.137.67.097.055.745.75TIIE8...  \\\n",
       "Junio       8.918.8TIIETIIETIIETIIE6.77.77.097.026.855.745...   \n",
       "Marzo       8.8TIIETIIETIIE7.76.426.855.96TIIETIIETIIE7.63...   \n",
       "Septiembre  7.9TIIE8.88.65TIIE9.137.69.935.975.96TIIE5.745...   \n",
       "\n",
       "                                                    sobretasa   \n",
       "mes                                                             \n",
       "Diciembre   0.350.970.880.380.340.530.350.120.880.320.420....  \\\n",
       "Junio       0.530.53TIIE-1.8150.120.880.880.880.410.420.35...   \n",
       "Marzo       0.350.350.120.880.910.360.410.420.970.35TIIE-1...   \n",
       "Septiembre  0.350.970.910.910.320.410.380.340.530.350.53TI...   \n",
       "\n",
       "                                                   tasa_final  \n",
       "mes                                                            \n",
       "Diciembre   7.9TIIE+0.358.918.8TIIE+0.979.137.67.977.055.7...  \n",
       "Junio       8.918.8TIIE+0.53TIIE+0.53TIIE+TIIE-1.815TIIE+0...  \n",
       "Marzo       8.8TIIE+0.35TIIE+0.35TIIE+0.128.586.426.856.87...  \n",
       "Septiembre  7.9TIIE+0.358.88.65TIIE+0.979.137.69.936.886.8...  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby('mes').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "ec26722c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def conv(cadena):\n",
    "    if cadena == 'Junio':\n",
    "        return 6\n",
    "    if cadena == 'Diciembre':\n",
    "        return 12\n",
    "    if cadena == 'Marzo':\n",
    "        return 3\n",
    "    if cadena == 'Septiembre':\n",
    "        return 9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4eec1f8c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/jamc88/TSMCI-Analisis-de-datos-con-Python/main/Datos/deuda_2022.csv')\n",
    "df=df.drop(669)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "36a2686e",
   "metadata": {},
   "outputs": [],
   "source": [
    "m=[]\n",
    "for i in range(0,669):\n",
    "    m.append(conv(df['mes'].iloc[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "b4f77a27",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       " 6]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "390d34f7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 669 entries, 0 to 668\n",
      "Data columns (total 22 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   anio                         669 non-null    float64\n",
      " 1   trimestre                    669 non-null    float64\n",
      " 2   mes                          669 non-null    object \n",
      " 3   no_registro                  669 non-null    object \n",
      " 4   tipo_deuda                   669 non-null    object \n",
      " 5   detalle_tipo_deuda           669 non-null    object \n",
      " 6   acreedor                     669 non-null    object \n",
      " 7   concepto                     669 non-null    object \n",
      " 8   inicio_credito               669 non-null    object \n",
      " 9   fin_credito                  669 non-null    object \n",
      " 10  dias_contrato                669 non-null    float64\n",
      " 11  dias_restantes_contrato      669 non-null    int64  \n",
      " 12  disposicion_inicial_credito  669 non-null    float64\n",
      " 13  colocacion_periodo           669 non-null    int64  \n",
      " 14  amortizaciones_periodo       669 non-null    object \n",
      " 15  intereses_periodo            669 non-null    float64\n",
      " 16  pago_servicio_deuda          669 non-null    float64\n",
      " 17  saldo_periodo                669 non-null    float64\n",
      " 18  endeudamiento_periodo        669 non-null    float64\n",
      " 19  tasa                         669 non-null    object \n",
      " 20  sobretasa                    354 non-null    object \n",
      " 21  tasa_final                   669 non-null    object \n",
      "dtypes: float64(8), int64(2), object(12)\n",
      "memory usage: 115.1+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "263a5647",
   "metadata": {},
   "outputs": [],
   "source": [
    "periods = pd.PeriodIndex(year = df['anio'],\n",
    "                         month = m, freq=\"D\",\n",
    "                         name = 'Fecha')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "86917905",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "PeriodIndex(['2018-12-01', '2018-12-01', '2018-12-01', '2018-12-01',\n",
       "             '2018-12-01', '2018-12-01', '2018-12-01', '2018-12-01',\n",
       "             '2018-12-01', '2018-12-01',\n",
       "             ...\n",
       "             '2022-06-01', '2022-06-01', '2022-06-01', '2022-06-01',\n",
       "             '2022-06-01', '2022-06-01', '2022-06-01', '2022-06-01',\n",
       "             '2022-06-01', '2022-06-01'],\n",
       "            dtype='period[D]', name='Fecha', length=669)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "periods"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "10023250",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>anio</th>\n",
       "      <th>trimestre</th>\n",
       "      <th>mes</th>\n",
       "      <th>no_registro</th>\n",
       "      <th>tipo_deuda</th>\n",
       "      <th>detalle_tipo_deuda</th>\n",
       "      <th>acreedor</th>\n",
       "      <th>concepto</th>\n",
       "      <th>inicio_credito</th>\n",
       "      <th>fin_credito</th>\n",
       "      <th>...</th>\n",
       "      <th>disposicion_inicial_credito</th>\n",
       "      <th>colocacion_periodo</th>\n",
       "      <th>amortizaciones_periodo</th>\n",
       "      <th>intereses_periodo</th>\n",
       "      <th>pago_servicio_deuda</th>\n",
       "      <th>saldo_periodo</th>\n",
       "      <th>endeudamiento_periodo</th>\n",
       "      <th>tasa</th>\n",
       "      <th>sobretasa</th>\n",
       "      <th>tasa_final</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fecha</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>145/2010</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>CI BANCO</td>\n",
       "      <td>BONO GDFCB 10-2</td>\n",
       "      <td>25/06/10</td>\n",
       "      <td>12/06/20</td>\n",
       "      <td>...</td>\n",
       "      <td>2.520951e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2.013680e+08</td>\n",
       "      <td>2.013680e+08</td>\n",
       "      <td>2.520951e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>224/2007</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca Comercial</td>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>BANCOMER 3,457</td>\n",
       "      <td>30/08/07</td>\n",
       "      <td>27/07/37</td>\n",
       "      <td>...</td>\n",
       "      <td>3.457974e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>14809395.11</td>\n",
       "      <td>2.860966e+08</td>\n",
       "      <td>3.009060e+08</td>\n",
       "      <td>3.389146e+09</td>\n",
       "      <td>-1.480940e+07</td>\n",
       "      <td>TIIE</td>\n",
       "      <td>0.35</td>\n",
       "      <td>TIIE+0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>225/2007</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca Comercial</td>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>BANCOMER 7000</td>\n",
       "      <td>31/08/07</td>\n",
       "      <td>27/08/40</td>\n",
       "      <td>...</td>\n",
       "      <td>7.000000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>108919450.9</td>\n",
       "      <td>5.809492e+08</td>\n",
       "      <td>6.898686e+08</td>\n",
       "      <td>6.371209e+09</td>\n",
       "      <td>-1.089195e+08</td>\n",
       "      <td>8.91</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>226/2007</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca Comercial</td>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>BANCOMER 4,700</td>\n",
       "      <td>31/08/07</td>\n",
       "      <td>27/07/37</td>\n",
       "      <td>...</td>\n",
       "      <td>4.700000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>20128593.44</td>\n",
       "      <td>4.018697e+08</td>\n",
       "      <td>4.219983e+08</td>\n",
       "      <td>4.606450e+09</td>\n",
       "      <td>-2.012859e+07</td>\n",
       "      <td>8.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Diciembre</td>\n",
       "      <td>513/2008</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Banca de Desarrollo</td>\n",
       "      <td>BANOBRAS</td>\n",
       "      <td>BANOBRAS  1,914</td>\n",
       "      <td>26/12/08</td>\n",
       "      <td>25/10/19</td>\n",
       "      <td>...</td>\n",
       "      <td>1.914681e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>320373500.5</td>\n",
       "      <td>2.445093e+07</td>\n",
       "      <td>3.448244e+08</td>\n",
       "      <td>1.277433e+08</td>\n",
       "      <td>-3.203735e+08</td>\n",
       "      <td>TIIE</td>\n",
       "      <td>0.97</td>\n",
       "      <td>TIIE+0.97</td>\n",
       "    </tr>\n",
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-1113146</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GDFECB 13</td>\n",
       "      <td>1385596800</td>\n",
       "      <td>1700092800</td>\n",
       "      <td>...</td>\n",
       "      <td>2.126875e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.580537e+07</td>\n",
       "      <td>7.580537e+07</td>\n",
       "      <td>2.126875e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-1014157</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GDFECB 14</td>\n",
       "      <td>1414972800</td>\n",
       "      <td>1729468800</td>\n",
       "      <td>...</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.114167e+07</td>\n",
       "      <td>8.114167e+07</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.42</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.42</td>\n",
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       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-0915121</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GDFECB 15-2</td>\n",
       "      <td>1443139200</td>\n",
       "      <td>1757635200</td>\n",
       "      <td>...</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.500000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>6.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-0917056</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GCDMXCB 17X</td>\n",
       "      <td>1505779200</td>\n",
       "      <td>1.84E+09</td>\n",
       "      <td>...</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2.000000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>7.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>2022.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Junio</td>\n",
       "      <td>P09-1118104</td>\n",
       "      <td>Largo Plazo</td>\n",
       "      <td>Mercado de Capitales</td>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>BONO GCDMXCB 18V</td>\n",
       "      <td>1542758400</td>\n",
       "      <td>1857254400</td>\n",
       "      <td>...</td>\n",
       "      <td>1.100000e+09</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5.522183e+07</td>\n",
       "      <td>5.522183e+07</td>\n",
       "      <td>1.100000e+09</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9.93</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.93</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>669 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              anio  trimestre        mes  no_registro   tipo_deuda   \n",
       "Fecha                                                                \n",
       "2018-12-01  2018.0        4.0  Diciembre     145/2010  Largo Plazo  \\\n",
       "2018-12-01  2018.0        4.0  Diciembre     224/2007  Largo Plazo   \n",
       "2018-12-01  2018.0        4.0  Diciembre     225/2007  Largo Plazo   \n",
       "2018-12-01  2018.0        4.0  Diciembre     226/2007  Largo Plazo   \n",
       "2018-12-01  2018.0        4.0  Diciembre     513/2008  Largo Plazo   \n",
       "...            ...        ...        ...          ...          ...   \n",
       "2022-06-01  2022.0        2.0      Junio  P09-1113146  Largo Plazo   \n",
       "2022-06-01  2022.0        2.0      Junio  P09-1014157  Largo Plazo   \n",
       "2022-06-01  2022.0        2.0      Junio  P09-0915121  Largo Plazo   \n",
       "2022-06-01  2022.0        2.0      Junio  P09-0917056  Largo Plazo   \n",
       "2022-06-01  2022.0        2.0      Junio  P09-1118104  Largo Plazo   \n",
       "\n",
       "              detalle_tipo_deuda  acreedor          concepto inicio_credito   \n",
       "Fecha                                                                         \n",
       "2018-12-01  Mercado de Capitales  CI BANCO   BONO GDFCB 10-2       25/06/10  \\\n",
       "2018-12-01       Banca Comercial  BANCOMER    BANCOMER 3,457       30/08/07   \n",
       "2018-12-01       Banca Comercial  BANCOMER     BANCOMER 7000       31/08/07   \n",
       "2018-12-01       Banca Comercial  BANCOMER    BANCOMER 4,700       31/08/07   \n",
       "2018-12-01   Banca de Desarrollo  BANOBRAS   BANOBRAS  1,914       26/12/08   \n",
       "...                          ...       ...               ...            ...   \n",
       "2022-06-01  Mercado de Capitales  EVERCORE    BONO GDFECB 13     1385596800   \n",
       "2022-06-01  Mercado de Capitales  EVERCORE    BONO GDFECB 14     1414972800   \n",
       "2022-06-01  Mercado de Capitales  EVERCORE  BONO GDFECB 15-2     1443139200   \n",
       "2022-06-01  Mercado de Capitales  EVERCORE  BONO GCDMXCB 17X     1505779200   \n",
       "2022-06-01  Mercado de Capitales  EVERCORE  BONO GCDMXCB 18V     1542758400   \n",
       "\n",
       "           fin_credito  ...  disposicion_inicial_credito  colocacion_periodo   \n",
       "Fecha                   ...                                                    \n",
       "2018-12-01    12/06/20  ...                 2.520951e+09                   0  \\\n",
       "2018-12-01    27/07/37  ...                 3.457974e+09                   0   \n",
       "2018-12-01    27/08/40  ...                 7.000000e+09                   0   \n",
       "2018-12-01    27/07/37  ...                 4.700000e+09                   0   \n",
       "2018-12-01    25/10/19  ...                 1.914681e+09                   0   \n",
       "...                ...  ...                          ...                 ...   \n",
       "2022-06-01  1700092800  ...                 2.126875e+09                   0   \n",
       "2022-06-01  1729468800  ...                 2.500000e+09                   0   \n",
       "2022-06-01  1757635200  ...                 2.500000e+09                   0   \n",
       "2022-06-01    1.84E+09  ...                 2.000000e+09                   0   \n",
       "2022-06-01  1857254400  ...                 1.100000e+09                   0   \n",
       "\n",
       "            amortizaciones_periodo  intereses_periodo pago_servicio_deuda   \n",
       "Fecha                                                                       \n",
       "2018-12-01                       0       2.013680e+08        2.013680e+08  \\\n",
       "2018-12-01             14809395.11       2.860966e+08        3.009060e+08   \n",
       "2018-12-01             108919450.9       5.809492e+08        6.898686e+08   \n",
       "2018-12-01             20128593.44       4.018697e+08        4.219983e+08   \n",
       "2018-12-01             320373500.5       2.445093e+07        3.448244e+08   \n",
       "...                            ...                ...                 ...   \n",
       "2022-06-01                       0       7.580537e+07        7.580537e+07   \n",
       "2022-06-01                       0       8.114167e+07        8.114167e+07   \n",
       "2022-06-01                       0       0.000000e+00        0.000000e+00   \n",
       "2022-06-01                       0       0.000000e+00        0.000000e+00   \n",
       "2022-06-01                       0       5.522183e+07        5.522183e+07   \n",
       "\n",
       "            saldo_periodo  endeudamiento_periodo  tasa  sobretasa tasa_final  \n",
       "Fecha                                                                         \n",
       "2018-12-01   2.520951e+09           0.000000e+00   7.9        NaN        7.9  \n",
       "2018-12-01   3.389146e+09          -1.480940e+07  TIIE       0.35  TIIE+0.35  \n",
       "2018-12-01   6.371209e+09          -1.089195e+08  8.91        NaN       8.91  \n",
       "2018-12-01   4.606450e+09          -2.012859e+07   8.8        NaN        8.8  \n",
       "2018-12-01   1.277433e+08          -3.203735e+08  TIIE       0.97  TIIE+0.97  \n",
       "...                   ...                    ...   ...        ...        ...  \n",
       "2022-06-01   2.126875e+09           0.000000e+00  7.05        NaN       7.05  \n",
       "2022-06-01   2.500000e+09           0.000000e+00  6.42        NaN       6.42  \n",
       "2022-06-01   2.500000e+09           0.000000e+00   6.7        NaN        6.7  \n",
       "2022-06-01   2.000000e+09           0.000000e+00   7.6        NaN        7.6  \n",
       "2022-06-01   1.100000e+09           0.000000e+00  9.93        NaN       9.93  \n",
       "\n",
       "[669 rows x 22 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index = periods.to_timestamp('D')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d554df5b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 669 entries, 2018-12-01 to 2022-06-01\n",
      "Data columns (total 22 columns):\n",
      " #   Column                       Non-Null Count  Dtype  \n",
      "---  ------                       --------------  -----  \n",
      " 0   anio                         669 non-null    float64\n",
      " 1   trimestre                    669 non-null    float64\n",
      " 2   mes                          669 non-null    object \n",
      " 3   no_registro                  669 non-null    object \n",
      " 4   tipo_deuda                   669 non-null    object \n",
      " 5   detalle_tipo_deuda           669 non-null    object \n",
      " 6   acreedor                     669 non-null    object \n",
      " 7   concepto                     669 non-null    object \n",
      " 8   inicio_credito               669 non-null    object \n",
      " 9   fin_credito                  669 non-null    object \n",
      " 10  dias_contrato                669 non-null    float64\n",
      " 11  dias_restantes_contrato      669 non-null    int64  \n",
      " 12  disposicion_inicial_credito  669 non-null    float64\n",
      " 13  colocacion_periodo           669 non-null    int64  \n",
      " 14  amortizaciones_periodo       669 non-null    object \n",
      " 15  intereses_periodo            669 non-null    float64\n",
      " 16  pago_servicio_deuda          669 non-null    float64\n",
      " 17  saldo_periodo                669 non-null    float64\n",
      " 18  endeudamiento_periodo        669 non-null    float64\n",
      " 19  tasa                         669 non-null    object \n",
      " 20  sobretasa                    354 non-null    object \n",
      " 21  tasa_final                   669 non-null    object \n",
      "dtypes: float64(8), int64(2), object(12)\n",
      "memory usage: 120.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "35d707e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.reindex(columns=['acreedor','pago_servicio_deuda','endeudamiento_periodo'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "acbac2be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>acreedor</th>\n",
       "      <th>pago_servicio_deuda</th>\n",
       "      <th>endeudamiento_periodo</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>CI BANCO</td>\n",
       "      <td>2.013680e+08</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>3.009060e+08</td>\n",
       "      <td>-1.480940e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>BANCOMER</td>\n",
       "      <td>6.898686e+08</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
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       "      <td>-2.012859e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-01</th>\n",
       "      <td>BANOBRAS</td>\n",
       "      <td>3.448244e+08</td>\n",
       "      <td>-3.203735e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>7.580537e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>8.114167e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>5.522183e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>669 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            acreedor  pago_servicio_deuda  endeudamiento_periodo\n",
       "Fecha                                                           \n",
       "2018-12-01  CI BANCO         2.013680e+08           0.000000e+00\n",
       "2018-12-01  BANCOMER         3.009060e+08          -1.480940e+07\n",
       "2018-12-01  BANCOMER         6.898686e+08          -1.089195e+08\n",
       "2018-12-01  BANCOMER         4.219983e+08          -2.012859e+07\n",
       "2018-12-01  BANOBRAS         3.448244e+08          -3.203735e+08\n",
       "...              ...                  ...                    ...\n",
       "2022-06-01  EVERCORE         7.580537e+07           0.000000e+00\n",
       "2022-06-01  EVERCORE         8.114167e+07           0.000000e+00\n",
       "2022-06-01  EVERCORE         0.000000e+00           0.000000e+00\n",
       "2022-06-01  EVERCORE         0.000000e+00           0.000000e+00\n",
       "2022-06-01  EVERCORE         5.522183e+07           0.000000e+00\n",
       "\n",
       "[669 rows x 3 columns]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "b90d7995",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns.name = 'variables'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "7671c5d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>7.580537e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>8.114167e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-06-01</th>\n",
       "      <td>EVERCORE</td>\n",
       "      <td>5.522183e+07</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>669 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "variables   acreedor  pago_servicio_deuda  endeudamiento_periodo\n",
       "Fecha                                                           \n",
       "2018-12-01  CI BANCO         2.013680e+08           0.000000e+00\n",
       "2018-12-01  BANCOMER         3.009060e+08          -1.480940e+07\n",
       "2018-12-01  BANCOMER         6.898686e+08          -1.089195e+08\n",
       "2018-12-01  BANCOMER         4.219983e+08          -2.012859e+07\n",
       "2018-12-01  BANOBRAS         3.448244e+08          -3.203735e+08\n",
       "...              ...                  ...                    ...\n",
       "2022-06-01  EVERCORE         7.580537e+07           0.000000e+00\n",
       "2022-06-01  EVERCORE         8.114167e+07           0.000000e+00\n",
       "2022-06-01  EVERCORE         0.000000e+00           0.000000e+00\n",
       "2022-06-01  EVERCORE         0.000000e+00           0.000000e+00\n",
       "2022-06-01  EVERCORE         5.522183e+07           0.000000e+00\n",
       "\n",
       "[669 rows x 3 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d0e1e59e",
   "metadata": {},
   "outputs": [],
   "source": [
    "long_data = (df.stack()\n",
    "             .reset_index()\n",
    "             .rename(columns={0: 'valor'}))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "50121fd1",
   "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>Fecha</th>\n",
       "      <th>variables</th>\n",
       "      <th>valor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>acreedor</td>\n",
       "      <td>CI BANCO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>pago_servicio_deuda</td>\n",
       "      <td>201367979.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>endeudamiento_periodo</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>acreedor</td>\n",
       "      <td>BANCOMER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>pago_servicio_deuda</td>\n",
       "      <td>300906043.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002</th>\n",
       "      <td>2022-06-01</td>\n",
       "      <td>pago_servicio_deuda</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003</th>\n",
       "      <td>2022-06-01</td>\n",
       "      <td>endeudamiento_periodo</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004</th>\n",
       "      <td>2022-06-01</td>\n",
       "      <td>acreedor</td>\n",
       "      <td>EVERCORE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005</th>\n",
       "      <td>2022-06-01</td>\n",
       "      <td>pago_servicio_deuda</td>\n",
       "      <td>55221833.33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006</th>\n",
       "      <td>2022-06-01</td>\n",
       "      <td>endeudamiento_periodo</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2007 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          Fecha              variables        valor\n",
       "0    2018-12-01               acreedor     CI BANCO\n",
       "1    2018-12-01    pago_servicio_deuda  201367979.7\n",
       "2    2018-12-01  endeudamiento_periodo          0.0\n",
       "3    2018-12-01               acreedor     BANCOMER\n",
       "4    2018-12-01    pago_servicio_deuda  300906043.8\n",
       "...         ...                    ...          ...\n",
       "2002 2022-06-01    pago_servicio_deuda          0.0\n",
       "2003 2022-06-01  endeudamiento_periodo          0.0\n",
       "2004 2022-06-01               acreedor     EVERCORE\n",
       "2005 2022-06-01    pago_servicio_deuda  55221833.33\n",
       "2006 2022-06-01  endeudamiento_periodo          0.0\n",
       "\n",
       "[2007 rows x 3 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "long_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8b8631dc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "06ee1afb",
   "metadata": {},
   "source": [
    "# Gráficos y visualización"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "187cc9e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "data=[3,2,5,2,1,5,3,5,7]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "581f464f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15af6ea10>]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b40aff8a",
   "metadata": {},
   "source": [
    "### Figuras y subgráficos"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ecffbde",
   "metadata": {},
   "source": [
    "Los gráficos en matplotlib residen dentro de un objeto Figure. Se puede crer una nueva figura con plt.figure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7a0e2647",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16ed7584",
   "metadata": {},
   "source": [
    "La función **plt.figure** tiene distintas opciones; en particular, figsize garantiza que la figura tenga un determinado tamaño y una cierta proporción de aspecto. Es necesario crear uno o varios subgráficos empleando **add_subplot**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "75a12a25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 2 × 2 (hasta cuatro gráficos en total)\n",
    "fig = plt.figure() \n",
    "ax1 = fig.add_subplot(2, 2, 1) #  el primero de cuatro subgráficos\n",
    "ax2 = fig.add_subplot(2, 2, 2) #  el segundo de cuatro subgráficos\n",
    "ax3 = fig.add_subplot(2, 2, 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f9ae838",
   "metadata": {},
   "source": [
    "Podemos ir añadiendo subgráficos:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "dd5ac7de",
   "metadata": {},
   "outputs": [],
   "source": [
    "ax1.hist(np.random.standard_normal(100), \n",
    "         bins=20, color='black', alpha = 0.5);\n",
    "\n",
    "# alpha=0.3 configura la transparencia del gráfico\n",
    "# bins es el número de particiones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "5ceea0db",
   "metadata": {},
   "outputs": [],
   "source": [
    "ax2.scatter(np.arange(30), \n",
    "            np.arange(30) + 3 * np.random.standard_normal(30));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "d66a0c0f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# gráfico de líneas con el método plot\n",
    "\n",
    "ax3.plot(np.random.standard_normal(50).cumsum(), color='black',\n",
    "         linestyle='dashed');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8ac7e502",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fig"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b69f09ea",
   "metadata": {},
   "source": [
    "Estilos de linea:"
   ]
  },
  {
   "attachments": {
    "Captura%20de%20pantalla%202024-01-16%20a%20la%28s%29%202.27.59.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "b94b4669",
   "metadata": {},
   "source": [
    "![Captura%20de%20pantalla%202024-01-16%20a%20la%28s%29%202.27.59.png](attachment:Captura%20de%20pantalla%202024-01-16%20a%20la%28s%29%202.27.59.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bf6084a",
   "metadata": {},
   "source": [
    "Para que la creación de una cuadrícula de subgráficos sea más cómoda, matplotlib incluye un método plt.subplots que crea una figura nueva y devuelve un array NumPy, que contiene los objetos de subgráficos creados:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "448ef6cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2)\n",
    "\n",
    "axes[0, 1].hist(np.random.standard_normal(100), \n",
    "         bins=20, color='black', alpha=0.5);\n",
    "\n",
    "axes[1, 0].scatter(np.arange(30), \n",
    "            np.arange(30) + 3 * np.random.standard_normal(30));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "4ba36833",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<Axes: >, <Axes: >],\n",
       "       [<Axes: >, <Axes: >]], dtype=object)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "axes"
   ]
  },
  {
   "attachments": {
    "Captura%20de%20pantalla%202024-01-16%20a%20la%28s%29%203.25.01.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "id": "1a86dd9b",
   "metadata": {},
   "source": [
    "![Captura%20de%20pantalla%202024-01-16%20a%20la%28s%29%203.25.01.png](attachment:Captura%20de%20pantalla%202024-01-16%20a%20la%28s%29%203.25.01.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "379f8c98",
   "metadata": {},
   "source": [
    "Se puede cambiar el espacio libre usando el método **subplots_adjust** en objetos Figure:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "d777688b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, sharex=True, sharey=True)\n",
    "\n",
    "for i in range(2):\n",
    "    for j in range(2):\n",
    "        axes[i, j].hist(np.random.standard_normal(500), bins=50,\n",
    "                        color='red', alpha=0.5)\n",
    "\n",
    "fig.subplots_adjust(wspace=0, hspace=0.1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6360caee",
   "metadata": {},
   "source": [
    "**wspace** y **hspace** controlan el porcentaje de la anchura y altura de la figura, respectivamente, para utilizarlo como espaciado entre subgráficos."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "50cfd21f",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ec562ea2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('redmet_2023_05.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b455edb0",
   "metadata": {},
   "source": [
    "La Red de Meteorología y Radiación Solar (REDMET) es el subsistema del Sistema de Monitoreo Atmosférico de la Ciudad de México (SIMAT) que realiza mediciones continuas y permanentes minuto a minuto de temperatura (TMP), humedad relativa (RH), dirección del viento (WDR) y la velocidad del viento (WSP).\n",
    "\n",
    "En este conjunto podrás encontrar los promedios diarios de los registros de estos parámetros para la Ciudad de México."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "c1ccbf0c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>fecha</th>\n",
       "      <th>RH</th>\n",
       "      <th>TMP</th>\n",
       "      <th>WDR</th>\n",
       "      <th>WSP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>60.565476</td>\n",
       "      <td>13.385714</td>\n",
       "      <td>156.723039</td>\n",
       "      <td>1.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>52.452381</td>\n",
       "      <td>13.567262</td>\n",
       "      <td>176.710784</td>\n",
       "      <td>2.559804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>55.763636</td>\n",
       "      <td>13.893333</td>\n",
       "      <td>190.830846</td>\n",
       "      <td>2.136318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>62.776786</td>\n",
       "      <td>12.536012</td>\n",
       "      <td>196.306373</td>\n",
       "      <td>2.592647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>70.271845</td>\n",
       "      <td>9.070227</td>\n",
       "      <td>266.889764</td>\n",
       "      <td>2.963517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3068</th>\n",
       "      <td>2023-05-27</td>\n",
       "      <td>51.899130</td>\n",
       "      <td>19.453565</td>\n",
       "      <td>190.198664</td>\n",
       "      <td>2.187646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3069</th>\n",
       "      <td>2023-05-28</td>\n",
       "      <td>59.949565</td>\n",
       "      <td>17.375826</td>\n",
       "      <td>183.542571</td>\n",
       "      <td>2.092154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3070</th>\n",
       "      <td>2023-05-29</td>\n",
       "      <td>58.837742</td>\n",
       "      <td>17.039153</td>\n",
       "      <td>169.527919</td>\n",
       "      <td>1.952284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3071</th>\n",
       "      <td>2023-05-30</td>\n",
       "      <td>50.145719</td>\n",
       "      <td>18.684699</td>\n",
       "      <td>184.998255</td>\n",
       "      <td>1.978709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3072</th>\n",
       "      <td>2023-05-31</td>\n",
       "      <td>50.353261</td>\n",
       "      <td>20.089130</td>\n",
       "      <td>172.697917</td>\n",
       "      <td>1.962153</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3073 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           fecha         RH        TMP         WDR       WSP\n",
       "0     2015-01-01  60.565476  13.385714  156.723039  1.933333\n",
       "1     2015-01-02  52.452381  13.567262  176.710784  2.559804\n",
       "2     2015-01-03  55.763636  13.893333  190.830846  2.136318\n",
       "3     2015-01-04  62.776786  12.536012  196.306373  2.592647\n",
       "4     2015-01-05  70.271845   9.070227  266.889764  2.963517\n",
       "...          ...        ...        ...         ...       ...\n",
       "3068  2023-05-27  51.899130  19.453565  190.198664  2.187646\n",
       "3069  2023-05-28  59.949565  17.375826  183.542571  2.092154\n",
       "3070  2023-05-29  58.837742  17.039153  169.527919  1.952284\n",
       "3071  2023-05-30  50.145719  18.684699  184.998255  1.978709\n",
       "3072  2023-05-31  50.353261  20.089130  172.697917  1.962153\n",
       "\n",
       "[3073 rows x 5 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "4a135a4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "df=df.iloc[0:365]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "92e38b49",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>fecha</th>\n",
       "      <th>RH</th>\n",
       "      <th>TMP</th>\n",
       "      <th>WDR</th>\n",
       "      <th>WSP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>60.565476</td>\n",
       "      <td>13.385714</td>\n",
       "      <td>156.723039</td>\n",
       "      <td>1.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015-01-02</td>\n",
       "      <td>52.452381</td>\n",
       "      <td>13.567262</td>\n",
       "      <td>176.710784</td>\n",
       "      <td>2.559804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2015-01-03</td>\n",
       "      <td>55.763636</td>\n",
       "      <td>13.893333</td>\n",
       "      <td>190.830846</td>\n",
       "      <td>2.136318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2015-01-04</td>\n",
       "      <td>62.776786</td>\n",
       "      <td>12.536012</td>\n",
       "      <td>196.306373</td>\n",
       "      <td>2.592647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2015-01-05</td>\n",
       "      <td>70.271845</td>\n",
       "      <td>9.070227</td>\n",
       "      <td>266.889764</td>\n",
       "      <td>2.963517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>2015-12-27</td>\n",
       "      <td>51.462891</td>\n",
       "      <td>16.580859</td>\n",
       "      <td>179.712092</td>\n",
       "      <td>3.320921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>2015-12-28</td>\n",
       "      <td>46.672619</td>\n",
       "      <td>14.301190</td>\n",
       "      <td>158.097222</td>\n",
       "      <td>1.662302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>2015-12-29</td>\n",
       "      <td>48.090744</td>\n",
       "      <td>16.570417</td>\n",
       "      <td>183.606884</td>\n",
       "      <td>2.264130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>2015-12-30</td>\n",
       "      <td>52.071038</td>\n",
       "      <td>17.190164</td>\n",
       "      <td>186.452899</td>\n",
       "      <td>1.493116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>2015-12-31</td>\n",
       "      <td>53.152450</td>\n",
       "      <td>17.219782</td>\n",
       "      <td>169.976406</td>\n",
       "      <td>1.543557</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>365 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          fecha         RH        TMP         WDR       WSP\n",
       "0    2015-01-01  60.565476  13.385714  156.723039  1.933333\n",
       "1    2015-01-02  52.452381  13.567262  176.710784  2.559804\n",
       "2    2015-01-03  55.763636  13.893333  190.830846  2.136318\n",
       "3    2015-01-04  62.776786  12.536012  196.306373  2.592647\n",
       "4    2015-01-05  70.271845   9.070227  266.889764  2.963517\n",
       "..          ...        ...        ...         ...       ...\n",
       "360  2015-12-27  51.462891  16.580859  179.712092  3.320921\n",
       "361  2015-12-28  46.672619  14.301190  158.097222  1.662302\n",
       "362  2015-12-29  48.090744  16.570417  183.606884  2.264130\n",
       "363  2015-12-30  52.071038  17.190164  186.452899  1.493116\n",
       "364  2015-12-31  53.152450  17.219782  169.976406  1.543557\n",
       "\n",
       "[365 rows x 5 columns]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "300770c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2)\n",
    "\n",
    "axes[0, 0].plot(df['RH'], color='black');\n",
    "\n",
    "axes[0, 1].hist(df['RH'], \n",
    "         bins=20, color='orange', alpha=0.5);\n",
    "\n",
    "axes[1, 0].scatter(df['RH'],df['TMP']);\n",
    "\n",
    "axes[1, 1].boxplot(df['RH'], vert = False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4ab05b2e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "87541961",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x1600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, figsize=(8,8), dpi=200)\n",
    "\n",
    "axes[0, 0].plot(df['RH'], color='black');\n",
    "\n",
    "axes[0, 1].hist(df['RH'], \n",
    "         bins=20, color='orange', alpha=0.5);\n",
    "\n",
    "axes[1, 0].scatter(df['RH'],df['TMP']);\n",
    "\n",
    "axes[1, 1].boxplot(df['RH'], vert = False);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "43251133",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "2b6d9a24",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Fecha</th>\n",
       "      <th>Centro Ozono</th>\n",
       "      <th>Centro diÛxido de azufre</th>\n",
       "      <th>Centro diÛxido de nitrÛgeno</th>\n",
       "      <th>Centro monÛxido de carbono</th>\n",
       "      <th>Centro PM10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>36.916667</td>\n",
       "      <td>6.333333</td>\n",
       "      <td>22.458333</td>\n",
       "      <td>10.208333</td>\n",
       "      <td>106.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-01-02</td>\n",
       "      <td>17.250000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>15.833333</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>97.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>24.083333</td>\n",
       "      <td>7.833333</td>\n",
       "      <td>17.875000</td>\n",
       "      <td>5.041667</td>\n",
       "      <td>61.958333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-01-04</td>\n",
       "      <td>27.583333</td>\n",
       "      <td>27.416667</td>\n",
       "      <td>27.125000</td>\n",
       "      <td>8.250000</td>\n",
       "      <td>91.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>30.875000</td>\n",
       "      <td>12.833333</td>\n",
       "      <td>25.791667</td>\n",
       "      <td>9.791667</td>\n",
       "      <td>94.000000</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>2022-12-27</td>\n",
       "      <td>19.041667</td>\n",
       "      <td>5.750000</td>\n",
       "      <td>18.541667</td>\n",
       "      <td>5.583333</td>\n",
       "      <td>39.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>2022-12-28</td>\n",
       "      <td>17.041667</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>19.125000</td>\n",
       "      <td>8.583333</td>\n",
       "      <td>53.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>2022-12-29</td>\n",
       "      <td>14.083333</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>16.791667</td>\n",
       "      <td>7.625000</td>\n",
       "      <td>42.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>2022-12-30</td>\n",
       "      <td>12.416667</td>\n",
       "      <td>4.916667</td>\n",
       "      <td>17.625000</td>\n",
       "      <td>10.166667</td>\n",
       "      <td>45.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>13.291667</td>\n",
       "      <td>2.833333</td>\n",
       "      <td>12.666667</td>\n",
       "      <td>5.541667</td>\n",
       "      <td>37.583333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>365 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Fecha  Centro Ozono  Centro diÛxido de azufre   \n",
       "0   2022-01-01     36.916667                  6.333333  \\\n",
       "1   2022-01-02     17.250000                  7.750000   \n",
       "2   2022-01-03     24.083333                  7.833333   \n",
       "3   2022-01-04     27.583333                 27.416667   \n",
       "4   2022-01-05     30.875000                 12.833333   \n",
       "..         ...           ...                       ...   \n",
       "360 2022-12-27     19.041667                  5.750000   \n",
       "361 2022-12-28     17.041667                 11.000000   \n",
       "362 2022-12-29     14.083333                  4.750000   \n",
       "363 2022-12-30     12.416667                  4.916667   \n",
       "364 2022-12-31     13.291667                  2.833333   \n",
       "\n",
       "     Centro diÛxido de nitrÛgeno  Centro monÛxido de carbono  Centro PM10  \n",
       "0                      22.458333                   10.208333   106.916667  \n",
       "1                      15.833333                    9.500000    97.875000  \n",
       "2                      17.875000                    5.041667    61.958333  \n",
       "3                      27.125000                    8.250000    91.333333  \n",
       "4                      25.791667                    9.791667    94.000000  \n",
       "..                           ...                         ...          ...  \n",
       "360                    18.541667                    5.583333    39.500000  \n",
       "361                    19.125000                    8.583333    53.666667  \n",
       "362                    16.791667                    7.625000    42.416667  \n",
       "363                    17.625000                   10.166667    45.500000  \n",
       "364                    12.666667                    5.541667    37.583333  \n",
       "\n",
       "[365 rows x 6 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_excel('contam2022.xlsx')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ee580db0",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.columns = ['Fecha','ozono','d_azufre',\n",
    "               'd_nitrogeno',\n",
    "               'm_carbono',\n",
    "               'PM10']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "51c0aed2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    <tr style=\"text-align: right;\">\n",
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       "      <th>Fecha</th>\n",
       "      <th>ozono</th>\n",
       "      <th>d_azufre</th>\n",
       "      <th>d_nitrogeno</th>\n",
       "      <th>m_carbono</th>\n",
       "      <th>PM10</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-01-01</td>\n",
       "      <td>36.916667</td>\n",
       "      <td>6.333333</td>\n",
       "      <td>22.458333</td>\n",
       "      <td>10.208333</td>\n",
       "      <td>106.916667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-01-02</td>\n",
       "      <td>17.250000</td>\n",
       "      <td>7.750000</td>\n",
       "      <td>15.833333</td>\n",
       "      <td>9.500000</td>\n",
       "      <td>97.875000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-01-03</td>\n",
       "      <td>24.083333</td>\n",
       "      <td>7.833333</td>\n",
       "      <td>17.875000</td>\n",
       "      <td>5.041667</td>\n",
       "      <td>61.958333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-01-04</td>\n",
       "      <td>27.583333</td>\n",
       "      <td>27.416667</td>\n",
       "      <td>27.125000</td>\n",
       "      <td>8.250000</td>\n",
       "      <td>91.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-01-05</td>\n",
       "      <td>30.875000</td>\n",
       "      <td>12.833333</td>\n",
       "      <td>25.791667</td>\n",
       "      <td>9.791667</td>\n",
       "      <td>94.000000</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",
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       "    <tr>\n",
       "      <th>360</th>\n",
       "      <td>2022-12-27</td>\n",
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       "      <td>5.750000</td>\n",
       "      <td>18.541667</td>\n",
       "      <td>5.583333</td>\n",
       "      <td>39.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>2022-12-28</td>\n",
       "      <td>17.041667</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>19.125000</td>\n",
       "      <td>8.583333</td>\n",
       "      <td>53.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>362</th>\n",
       "      <td>2022-12-29</td>\n",
       "      <td>14.083333</td>\n",
       "      <td>4.750000</td>\n",
       "      <td>16.791667</td>\n",
       "      <td>7.625000</td>\n",
       "      <td>42.416667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>363</th>\n",
       "      <td>2022-12-30</td>\n",
       "      <td>12.416667</td>\n",
       "      <td>4.916667</td>\n",
       "      <td>17.625000</td>\n",
       "      <td>10.166667</td>\n",
       "      <td>45.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>364</th>\n",
       "      <td>2022-12-31</td>\n",
       "      <td>13.291667</td>\n",
       "      <td>2.833333</td>\n",
       "      <td>12.666667</td>\n",
       "      <td>5.541667</td>\n",
       "      <td>37.583333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>365 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Fecha      ozono   d_azufre  d_nitrogeno  m_carbono        PM10\n",
       "0   2022-01-01  36.916667   6.333333    22.458333  10.208333  106.916667\n",
       "1   2022-01-02  17.250000   7.750000    15.833333   9.500000   97.875000\n",
       "2   2022-01-03  24.083333   7.833333    17.875000   5.041667   61.958333\n",
       "3   2022-01-04  27.583333  27.416667    27.125000   8.250000   91.333333\n",
       "4   2022-01-05  30.875000  12.833333    25.791667   9.791667   94.000000\n",
       "..         ...        ...        ...          ...        ...         ...\n",
       "360 2022-12-27  19.041667   5.750000    18.541667   5.583333   39.500000\n",
       "361 2022-12-28  17.041667  11.000000    19.125000   8.583333   53.666667\n",
       "362 2022-12-29  14.083333   4.750000    16.791667   7.625000   42.416667\n",
       "363 2022-12-30  12.416667   4.916667    17.625000  10.166667   45.500000\n",
       "364 2022-12-31  13.291667   2.833333    12.666667   5.541667   37.583333\n",
       "\n",
       "[365 rows x 6 columns]"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "1616b4e7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 2, sharex=True, sharey=True,\n",
    "                         figsize=(4,4), dpi=200)\n",
    "\n",
    "axes[0, 0].hist(df['ozono'], bins=20, color='orange');\n",
    "axes[0, 1].hist(df['d_azufre'], bins=20, color='green', alpha=1);\n",
    "axes[1, 0].hist(df['d_nitrogeno'], bins=20, color='blue', alpha=0.7);\n",
    "axes[1, 1].hist(df['m_carbono'], bins=20, color='red', alpha=0.7);\n",
    "\n",
    "fig.subplots_adjust(wspace=0.1, hspace=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "329e387b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}