Data Analysis for stolen cars in Argentina(2022).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "7004bd58",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "eda50c4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('C:\\\\Users\\\\joaco\\\\Python\\\\combinado_csv.csv', low_memory=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48fbf19b",
   "metadata": {},
   "source": [
    "# This is a very little analysis of this Dataset in Jupyter\n",
    "\n",
    "The dataset basically have information about stolen cars in Argentina, all the robberies was in 2022 in all the country\n",
    "\n",
    "### The questions will be:\n",
    "<ol>\n",
    "    <li>Origin of the stolen cars</li>\n",
    "    <li>Gender of the owners of the stolen cars</li>\n",
    "    <li>Number of robberies for each province</li>\n",
    "    <li>Top 10 provinces with most Robberies</li>\n",
    "</ol>\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "Enjoy it!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6be2587c",
   "metadata": {},
   "source": [
    "---------------------------------------------------------\n",
    "First I want to see what we have in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6403aa98",
   "metadata": {
    "scrolled": true
   },
   "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>tramite_tipo</th>\n",
       "      <th>tramite_fecha</th>\n",
       "      <th>fecha_inscripcion_inicial</th>\n",
       "      <th>registro_seccional_codigo</th>\n",
       "      <th>registro_seccional_descripcion</th>\n",
       "      <th>registro_seccional_provincia</th>\n",
       "      <th>automotor_origen</th>\n",
       "      <th>automotor_anio_modelo</th>\n",
       "      <th>automotor_tipo_codigo</th>\n",
       "      <th>automotor_tipo_descripcion</th>\n",
       "      <th>...</th>\n",
       "      <th>automotor_uso_descripcion</th>\n",
       "      <th>titular_tipo_persona</th>\n",
       "      <th>titular_domicilio_localidad</th>\n",
       "      <th>titular_domicilio_provincia</th>\n",
       "      <th>titular_genero</th>\n",
       "      <th>titular_anio_nacimiento</th>\n",
       "      <th>titular_pais_nacimiento</th>\n",
       "      <th>titular_porcentaje_titularidad</th>\n",
       "      <th>titular_domicilio_provincia_id</th>\n",
       "      <th>titular_pais_nacimiento_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-01-18</td>\n",
       "      <td>1994-06-03</td>\n",
       "      <td>1173</td>\n",
       "      <td>BERAZATEGUI Nº 2</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>Nacional</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FURGON VIDRID.C/ASIE</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>BERAZATEGUI</td>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>Masculino</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>100</td>\n",
       "      <td>6</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-01-31</td>\n",
       "      <td>2000-10-27</td>\n",
       "      <td>1120</td>\n",
       "      <td>LA MATANZA Nº 03</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>Nacional</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SEDAN</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>LOMAS DEL MIRADOR</td>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>Femenino</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>100</td>\n",
       "      <td>6</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-01-11</td>\n",
       "      <td>1994-04-28</td>\n",
       "      <td>2086</td>\n",
       "      <td>CAPITAL FEDERAL Nº 086</td>\n",
       "      <td>Ciudad Autónoma de Bs.As.</td>\n",
       "      <td>Nacional</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>FUR.VIDRIADO C/ASIEN</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>C.AUTONOMA DE BS.AS</td>\n",
       "      <td>C.AUTONOMA DE BS.AS</td>\n",
       "      <td>Masculino</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>PERU</td>\n",
       "      <td>100</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-01-10</td>\n",
       "      <td>1992-03-27</td>\n",
       "      <td>1119</td>\n",
       "      <td>MORON Nº 03</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>Importado</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>RURAL 4 PTAS.</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>HAEDO</td>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>No identificado</td>\n",
       "      <td>1982.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>50</td>\n",
       "      <td>6</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-01-24</td>\n",
       "      <td>2000-11-01</td>\n",
       "      <td>1118</td>\n",
       "      <td>QUILMES Nº 2</td>\n",
       "      <td>Buenos Aires</td>\n",
       "      <td>Nacional</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SEDAN 4 PUERTAS</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>QUILMES OESTE</td>\n",
       "      <td>BUENOS AIRES</td>\n",
       "      <td>Masculino</td>\n",
       "      <td>1947.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>100</td>\n",
       "      <td>6</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946845</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-12-14</td>\n",
       "      <td>1992-05-06</td>\n",
       "      <td>2035</td>\n",
       "      <td>CAPITAL FEDERAL Nº 035</td>\n",
       "      <td>Ciudad Autónoma de Bs.As.</td>\n",
       "      <td>Protocolo 21</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SEDAN 3 PUERTAS</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>C.AUTONOMA DE BS.AS</td>\n",
       "      <td>C.AUTONOMA DE BS.AS</td>\n",
       "      <td>Femenino</td>\n",
       "      <td>1959.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>100</td>\n",
       "      <td>2</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946846</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-12-14</td>\n",
       "      <td>1996-10-21</td>\n",
       "      <td>13018</td>\n",
       "      <td>MENDOZA Nº 11</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>Importado</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>SEDAN 5 PTAS</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>PRESIDENTE SARMIENTO</td>\n",
       "      <td>MENDOZA</td>\n",
       "      <td>Femenino</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946847</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-12-29</td>\n",
       "      <td>2008-05-30</td>\n",
       "      <td>13031</td>\n",
       "      <td>MAIPU Nº 1- MENDOZA</td>\n",
       "      <td>Mendoza</td>\n",
       "      <td>Nacional</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>FURGON</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>CIUDAD</td>\n",
       "      <td>MENDOZA</td>\n",
       "      <td>No identificado</td>\n",
       "      <td>1975.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>100</td>\n",
       "      <td>50</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946848</th>\n",
       "      <td>COMUNICACIÓN DE RECUPERO</td>\n",
       "      <td>2022-12-29</td>\n",
       "      <td>2008-05-09</td>\n",
       "      <td>21054</td>\n",
       "      <td>ARROYO SECO Nº 2</td>\n",
       "      <td>Santa Fe</td>\n",
       "      <td>Protocolo 21</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>SEDAN 3 PTAS</td>\n",
       "      <td>...</td>\n",
       "      <td>Privado</td>\n",
       "      <td>Física</td>\n",
       "      <td>ARROYO SECO</td>\n",
       "      <td>SANTA FE</td>\n",
       "      <td>Masculino</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>100</td>\n",
       "      <td>82</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>946849</th>\n",
       "      <td>DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA</td>\n",
       "      <td>2022-12-29</td>\n",
       "      <td>2011-06-22</td>\n",
       "      <td>4038</td>\n",
       "      <td>CORDOBA Nº 07</td>\n",
       "      <td>Córdoba</td>\n",
       "      <td>Protocolo 21</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>SEDAN 4 PTAS</td>\n",
       "      <td>...</td>\n",
       "      <td>Público</td>\n",
       "      <td>Física</td>\n",
       "      <td>CORDOBA</td>\n",
       "      <td>CORDOBA</td>\n",
       "      <td>No identificado</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>ARGENTINA</td>\n",
       "      <td>100</td>\n",
       "      <td>14</td>\n",
       "      <td>ARG</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>946850 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         tramite_tipo tramite_fecha  \\\n",
       "0       DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-01-18   \n",
       "1       DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-01-31   \n",
       "2       DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-01-11   \n",
       "3       DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-01-10   \n",
       "4       DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-01-24   \n",
       "...                                               ...           ...   \n",
       "946845  DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-12-14   \n",
       "946846  DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-12-14   \n",
       "946847  DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-12-29   \n",
       "946848                       COMUNICACIÓN DE RECUPERO    2022-12-29   \n",
       "946849  DENUNCIA DE ROBO O HURTO / RETENCION INDEBIDA    2022-12-29   \n",
       "\n",
       "       fecha_inscripcion_inicial  registro_seccional_codigo  \\\n",
       "0                     1994-06-03                       1173   \n",
       "1                     2000-10-27                       1120   \n",
       "2                     1994-04-28                       2086   \n",
       "3                     1992-03-27                       1119   \n",
       "4                     2000-11-01                       1118   \n",
       "...                          ...                        ...   \n",
       "946845                1992-05-06                       2035   \n",
       "946846                1996-10-21                      13018   \n",
       "946847                2008-05-30                      13031   \n",
       "946848                2008-05-09                      21054   \n",
       "946849                2011-06-22                       4038   \n",
       "\n",
       "       registro_seccional_descripcion registro_seccional_provincia  \\\n",
       "0                    BERAZATEGUI Nº 2                 Buenos Aires   \n",
       "1                    LA MATANZA Nº 03                 Buenos Aires   \n",
       "2              CAPITAL FEDERAL Nº 086    Ciudad Autónoma de Bs.As.   \n",
       "3                         MORON Nº 03                 Buenos Aires   \n",
       "4                        QUILMES Nº 2                 Buenos Aires   \n",
       "...                               ...                          ...   \n",
       "946845         CAPITAL FEDERAL Nº 035    Ciudad Autónoma de Bs.As.   \n",
       "946846                  MENDOZA Nº 11                      Mendoza   \n",
       "946847            MAIPU Nº 1- MENDOZA                      Mendoza   \n",
       "946848               ARROYO SECO Nº 2                     Santa Fe   \n",
       "946849                  CORDOBA Nº 07                      Córdoba   \n",
       "\n",
       "       automotor_origen  automotor_anio_modelo automotor_tipo_codigo  \\\n",
       "0              Nacional                 1994.0                   NaN   \n",
       "1              Nacional                 2000.0                   NaN   \n",
       "2              Nacional                 1994.0                   NaN   \n",
       "3             Importado                 1991.0                   NaN   \n",
       "4              Nacional                 2000.0                   NaN   \n",
       "...                 ...                    ...                   ...   \n",
       "946845     Protocolo 21                 1992.0                   NaN   \n",
       "946846        Importado                 1996.0                   NaN   \n",
       "946847         Nacional                 2008.0                  22.0   \n",
       "946848     Protocolo 21                 2008.0                  22.0   \n",
       "946849     Protocolo 21                 2011.0                   2.0   \n",
       "\n",
       "       automotor_tipo_descripcion  ... automotor_uso_descripcion  \\\n",
       "0            FURGON VIDRID.C/ASIE  ...                   Privado   \n",
       "1                           SEDAN  ...                   Privado   \n",
       "2            FUR.VIDRIADO C/ASIEN  ...                   Privado   \n",
       "3                   RURAL 4 PTAS.  ...                   Privado   \n",
       "4                 SEDAN 4 PUERTAS  ...                   Privado   \n",
       "...                           ...  ...                       ...   \n",
       "946845            SEDAN 3 PUERTAS  ...                   Privado   \n",
       "946846               SEDAN 5 PTAS  ...                   Privado   \n",
       "946847                     FURGON  ...                   Privado   \n",
       "946848               SEDAN 3 PTAS  ...                   Privado   \n",
       "946849               SEDAN 4 PTAS  ...                   Público   \n",
       "\n",
       "       titular_tipo_persona titular_domicilio_localidad  \\\n",
       "0                    Física                 BERAZATEGUI   \n",
       "1                    Física           LOMAS DEL MIRADOR   \n",
       "2                    Física         C.AUTONOMA DE BS.AS   \n",
       "3                    Física                       HAEDO   \n",
       "4                    Física               QUILMES OESTE   \n",
       "...                     ...                         ...   \n",
       "946845               Física         C.AUTONOMA DE BS.AS   \n",
       "946846               Física        PRESIDENTE SARMIENTO   \n",
       "946847               Física                      CIUDAD   \n",
       "946848               Física                 ARROYO SECO   \n",
       "946849               Física                     CORDOBA   \n",
       "\n",
       "       titular_domicilio_provincia   titular_genero titular_anio_nacimiento  \\\n",
       "0                     BUENOS AIRES        Masculino                  1972.0   \n",
       "1                     BUENOS AIRES         Femenino                  1991.0   \n",
       "2              C.AUTONOMA DE BS.AS        Masculino                  1971.0   \n",
       "3                     BUENOS AIRES  No identificado                  1982.0   \n",
       "4                     BUENOS AIRES        Masculino                  1947.0   \n",
       "...                            ...              ...                     ...   \n",
       "946845         C.AUTONOMA DE BS.AS         Femenino                  1959.0   \n",
       "946846                     MENDOZA         Femenino                  1985.0   \n",
       "946847                     MENDOZA  No identificado                  1975.0   \n",
       "946848                    SANTA FE        Masculino                  1983.0   \n",
       "946849                     CORDOBA  No identificado                  1972.0   \n",
       "\n",
       "       titular_pais_nacimiento titular_porcentaje_titularidad  \\\n",
       "0                    ARGENTINA                            100   \n",
       "1                    ARGENTINA                            100   \n",
       "2                         PERU                            100   \n",
       "3                    ARGENTINA                             50   \n",
       "4                    ARGENTINA                            100   \n",
       "...                        ...                            ...   \n",
       "946845               ARGENTINA                            100   \n",
       "946846               ARGENTINA                             50   \n",
       "946847               ARGENTINA                            100   \n",
       "946848               ARGENTINA                            100   \n",
       "946849               ARGENTINA                            100   \n",
       "\n",
       "       titular_domicilio_provincia_id titular_pais_nacimiento_id  \n",
       "0                                   6                        ARG  \n",
       "1                                   6                        ARG  \n",
       "2                                   2                        NaN  \n",
       "3                                   6                        ARG  \n",
       "4                                   6                        ARG  \n",
       "...                               ...                        ...  \n",
       "946845                              2                        ARG  \n",
       "946846                             50                        ARG  \n",
       "946847                             50                        ARG  \n",
       "946848                             82                        ARG  \n",
       "946849                             14                        ARG  \n",
       "\n",
       "[946850 rows x 25 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
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  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "02841315",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['tramite_tipo', 'tramite_fecha', 'fecha_inscripcion_inicial',\n",
       "       'registro_seccional_codigo', 'registro_seccional_descripcion',\n",
       "       'registro_seccional_provincia', 'automotor_origen',\n",
       "       'automotor_anio_modelo', 'automotor_tipo_codigo',\n",
       "       'automotor_tipo_descripcion', 'automotor_marca_codigo',\n",
       "       'automotor_marca_descripcion', 'automotor_modelo_codigo',\n",
       "       'automotor_modelo_descripcion', 'automotor_uso_codigo',\n",
       "       'automotor_uso_descripcion', 'titular_tipo_persona',\n",
       "       'titular_domicilio_localidad', 'titular_domicilio_provincia',\n",
       "       'titular_genero', 'titular_anio_nacimiento', 'titular_pais_nacimiento',\n",
       "       'titular_porcentaje_titularidad', 'titular_domicilio_provincia_id',\n",
       "       'titular_pais_nacimiento_id'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "eb037335",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tramite_tipo                       object\n",
       "tramite_fecha                      object\n",
       "fecha_inscripcion_inicial          object\n",
       "registro_seccional_codigo           int64\n",
       "registro_seccional_descripcion     object\n",
       "registro_seccional_provincia       object\n",
       "automotor_origen                   object\n",
       "automotor_anio_modelo             float64\n",
       "automotor_tipo_codigo              object\n",
       "automotor_tipo_descripcion         object\n",
       "automotor_marca_codigo             object\n",
       "automotor_marca_descripcion        object\n",
       "automotor_modelo_codigo            object\n",
       "automotor_modelo_descripcion       object\n",
       "automotor_uso_codigo                int64\n",
       "automotor_uso_descripcion          object\n",
       "titular_tipo_persona               object\n",
       "titular_domicilio_localidad        object\n",
       "titular_domicilio_provincia        object\n",
       "titular_genero                     object\n",
       "titular_anio_nacimiento           float64\n",
       "titular_pais_nacimiento            object\n",
       "titular_porcentaje_titularidad      int64\n",
       "titular_domicilio_provincia_id      int64\n",
       "titular_pais_nacimiento_id         object\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "578940d3",
   "metadata": {},
   "source": [
    "### Alright, so we have 25 columns and close to 1 million rows in the data set, there is information about dates, description of the vehicle, who owned it, where it was stolen, etc.\n",
    "\n",
    "Now I want to know the origin of the stolen cars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "dc2ba3e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Nacional        451875\n",
       "Protocolo 21    365075\n",
       "Importado       129900\n",
       "Name: automotor_origen, dtype: int64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['automotor_origen'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "f3e49aec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = df['automotor_origen'].unique()\n",
    "y = df['automotor_origen'].value_counts()\n",
    "colors = ['tab:red','tab:blue','tab:green']\n",
    "\n",
    "plt.bar(x, y, color=colors)\n",
    "plt.title(\"Origin of stolen cars in Argentina (2022)\")\n",
    "plt.xlabel(\"Origin\")\n",
    "plt.ylabel(\"Amount \")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cdb1e74",
   "metadata": {},
   "source": [
    "Most stolen cars are made in Argentina"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca89c423",
   "metadata": {},
   "source": [
    "-----------------------------------------------------------------------------------------\n",
    "### Next, let's see the gender of the owners of the stolen cars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f913d07c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.patches.Wedge at 0x21e863a6100>,\n",
       "  <matplotlib.patches.Wedge at 0x21e874f0550>,\n",
       "  <matplotlib.patches.Wedge at 0x21e874f0bb0>,\n",
       "  <matplotlib.patches.Wedge at 0x21e87652460>],\n",
       " [Text(-0.02919448765494532, 1.099612514429772, 'Masculino'),\n",
       "  Text(-0.7254546531265961, -0.8268709368800976, 'Femenino'),\n",
       "  Text(0.6923920122220749, -0.8547475074026635, 'No identificado'),\n",
       "  Text(1.08873267193814, -0.15703875016835425, 'No aplica')],\n",
       " [Text(-0.015924265993606534, 0.599788644234421, '50.8%'),\n",
       "  Text(-0.39570253806905237, -0.4510205110255077, '25.4%'),\n",
       "  Text(0.3776683703029499, -0.46622591312872547, '19.2%'),\n",
       "  Text(0.5938541846935308, -0.08565750009182958, '4.6%')])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = df['titular_genero'].unique()\n",
    "values = df['titular_genero'].value_counts()\n",
    "\n",
    "plt.pie(values, labels=labels, colors=['orange', 'yellow','green','lightblue'], autopct='%1.1f%%')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90b76c44",
   "metadata": {},
   "source": [
    "Masculino = Male <br>\n",
    "Femenino = Female <br>\n",
    "No identificado = No identified <br>\n",
    "No aplica = Doesn't apply (This mean that the owner of the stolen car is the government or a private company)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59b57c0c",
   "metadata": {},
   "source": [
    "----------------------------------------\n",
    "### What is the number of robberies for each province?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e5f8d10e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Buenos Aires                 626550\n",
       "Ciudad Autónoma de Bs.As.    121075\n",
       "Córdoba                       80450\n",
       "Mendoza                       46425\n",
       "Santa Fe                      43250\n",
       "Neuquén                        5825\n",
       "Río Negro                      3600\n",
       "Entre Ríos                     3275\n",
       "Corrientes                     2375\n",
       "Chubut                         2050\n",
       "Tucumán                        1650\n",
       "Chaco                          1425\n",
       "Misiones                       1275\n",
       "San Luis                       1100\n",
       "Jujuy                          1025\n",
       "Salta                          1025\n",
       "Tierra del Fuego                800\n",
       "Santa Cruz                      700\n",
       "San Juan                        675\n",
       "Santiago del Estero             625\n",
       "La Pampa                        625\n",
       "Formosa                         550\n",
       "La Rioja                        325\n",
       "Catamarca                       175\n",
       "Name: registro_seccional_provincia, dtype: int64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['registro_seccional_provincia'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00c6a9d6",
   "metadata": {},
   "source": [
    "### Top 10 provinces with most robberies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "a52bf99c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = df['registro_seccional_provincia'].unique()[:10]\n",
    "y = df['registro_seccional_provincia'].value_counts()[:10]\n",
    "\n",
    "\n",
    "\n",
    "plt.bar(x, y)\n",
    "plt.title(\"Origin of stolen cars in Argentina (2022)\")\n",
    "plt.xlabel(\"Origin\")\n",
    "plt.ylabel(\"Amount \")\n",
    "plt.xticks(rotation=70)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b6524b3",
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   "source": [
    "As we can imagine, Buenos Aires and CABA (Buenos Aires City) are the most populated provinces in Argentina, thus are the provinces with more stolen cars in Argentina (With difference)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10611e69",
   "metadata": {},
   "source": [
    "-----------------------------------\n",
    "Well, this is the end, maybe in the future I would expand this analysis because the dataset is giant, or maybe I could combine this dataset with another one.\n",
    "But for the moment this is all, see you."
   ]
  }
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