Modulo 1 - Analisis de Datos.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.4"},"colab":{"name":"Proyecto Aplicado Diplomado.ipynb","provenance":[],"collapsed_sections":[],"toc_visible":true}},"cells":[{"cell_type":"markdown","metadata":{"id":"zPKspZ3LcAK-"},"source":["## **Entendimiento del Negocio**\n","\n","El Ministerio de Transporte de la república de Colombia está realizando un estudio para entender el comportamiento de los habitantes de la ciudad de Bogotá en las vías del país, esto con el fin de tomar las acciones necesarias en búsqueda de la concientización de la ciudadanía. Dentro de estas acciones que se pretende realizar una vez terminado el estudio están: Jornadas de capacitacion y concientización a conductores, verificacion de señalizaciones de transito, entre otras. \n","\n","Para realizar este estudio, el ministerio cuenta con un conjunto de datos de accidentalidad, registrado desde el año 2015 hasta el 2019."]},{"cell_type":"markdown","metadata":{"id":"MovsG50wwVUo"},"source":["### **1. Objetivo del negocio y situación actual**\n","\n","#### **1.1 Objetivos del negocio**\n","    \n","   * Comprender el comportamiento de los habitantes de la ciudad de Bogotá en las vías.\n","   * Dimensionar el nivel de accidentalidad de la ciudad, así como los tipos de lugares más peligrosos.\n","\n","#### **1.2 Situación actual** \n","\n","La situación actual en cuanto accidentalidad es grave, pues en los ultimos meses se ha dado un incremento considerable de accidentes de tránsito. Por otro lado, actualmente existen unos datos registrados de accidentes desde el año 2015, sin embargo nunca se han estudiado ni se les ha dado un uso provechoso."]},{"cell_type":"markdown","metadata":{"id":"rn9_X9P-wveR"},"source":["### **2. Objetivos del proyecto**\n","\n","\n","1. Conocer aspectos relevantes sobre los accidentes letales, es decir, aquellos donde hayan heridos o muertos. Localidades mas peligrosas, diseños de lugares, etc.\n","\n","2. Identificar comportamientos de las personas en estos accidentes, teniendo en cuenta su edad y sexo.\n","\n","3. Conocer aspectos de los vehiculos implicados en los accidentes de tránsito."]},{"cell_type":"markdown","metadata":{"id":"4wPoqoXew7bt"},"source":["### **3. Planeación del proyecto**\n","Este proyecto de análisis de datos seguirá la metodología CRISP, el cual nos permite de manera organizada llevar a cabo una serie de fases iterativas, con el fin de tener un resultado satisfactorio al final del estudio. A continuación, se detallan las fases que se van a desarrollar en el proyecto."]},{"cell_type":"markdown","metadata":{"id":"0NYo5jXrxKDu"},"source":["#### **1. Fase de Entendimiento de los datos** \n","\n","En esta fase vamos a centrarnos en obtener los conjuntos de datos proprcionados por el ministerio, acá vamos a tener en cuenta aspectos como el formato, espacio en memoria y homogeneidad de los datos. Otra activdad importante dentro de la presente fase, es realizar análisis exploratorios sobre los datos, obteniendo información valiosa por medio de la estadística descriptiva y visualización de datos estadísticos.\n"]},{"cell_type":"markdown","metadata":{"id":"gqlCqE_8xVVe"},"source":["#### **2. Fase de Preparación de los datos**\n","\n","Acá vamos a realizar una selección de los atributos que nos interesan en este estudio, verificaremos los tipos de datos y caracterizaremos la información con la que vamos a trabajar. De igual manera, realizaremos una limpieza de datos con el fin de obviar o eliminar algunos valores _outliers_ que puedan darnos problemas en nuestros resultados."]},{"cell_type":"markdown","metadata":{"id":"zdz4jiU9xZkq"},"source":["#### **3. Fase de Análisis de datos**\n","\n","En esta fase nos ayudaremos de la estadistica descriptiva (o inferencial si se llegasde a necesitar) para dar cumplimiento a los objetivos del proyecto."]},{"cell_type":"markdown","metadata":{"id":"sT2N7xmCxdt6"},"source":["#### **4. Fase de Evaluación de Resultados y Cumplimiento de Objetivos**\n","\n","Esta es la ultima fase de la metodología propuesta para el proyecto, aquí se revisarán los resultados y se verificará si, se ha dado cumplimiento a los objetivos establecidos, en caso de que algun objetivo no se haya cumplido por completo, CRISP nos permite retomar de nuevo los análisis en la etapa de Análisis de datos y luego volver a evaluar.\n","\n","**Nota:** _Los datos usados para el proyecto están disponibles haciendo clic [aquí](https://datosabiertos.bogota.gov.co/dataset/siniestros-viales-consolidados-bogota-d-c/resource/9e3add8e-3f46-42ce-9c0f-419964f6f598)_"]},{"cell_type":"markdown","metadata":{"id":"9LMFmwe4qcrx"},"source":["# **FASE 1: Entendimiento de los datos**\n","\n","Para este proyecto se usará el conjunto de datos de _**Siniestros Viales de la ciudad de Bogotá**_, el cual tiene registrado la información de accidentes desde el año 2015 hasta el año 2019.\n","\n","El formato de la fuente de los datos es Excel, el cual cuenta con 4 hojas, las cuales son: '\n","\n","* **SINIESTROS**: En esta hoja encontramos la información propia de los accidentes de transito (e.g Tipo de accidente, Fecha, Localidad, entre otros)\n","\n","* **ACTOR VIAL**: En esta hoja se encuentra la información de las personas implicadas en el accidente (e.g. Sexo, Edad, Estado de la persona), varias personas pueden verse implicada en un mismo accidente.\n","\n","* **VEHICULOS**: En esta hoja se encuentra la información relacionada a los vehiculos implicados en el accidente de transito (e.g Si el vehiculo es un carro, una moto o un bus. Si el vehiculo se fugó del lugar del accidente o no, entre otros)\n","\n","* **HIPOTESIS**: Por último, en esta hoja se encuentran registradas algunas psoibles causas del accidente, como por ejemplo, el no respetar un semaforo en rojo, el exceso de velocidad o el desobedecer alguna señal de tránsito.\n","\n","Para el presente estudio, se usarán las primeras 3 hojas, las cuales nos ofrecen los datos necesarios para el cumplimiento de los objetivos. Dado que este estudio no busca dar algun motivo por el cual un accidente ocurrió, no se ve necesario el uso de los datos presentes en la hoja **HIPOTESIS**."]},{"cell_type":"markdown","metadata":{"id":"8P8ulx2dcALA"},"source":["### Importacion de Liberías"]},{"cell_type":"code","metadata":{"id":"4vRcT_z5cALI","executionInfo":{"status":"ok","timestamp":1601041961388,"user_tz":300,"elapsed":4867,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"12e84dd8-3f1c-457a-e249-92d2f434bd6c","colab":{"base_uri":"https://localhost:8080/","height":343}},"source":["!pip install seaborn --upgrade"],"execution_count":null,"outputs":[{"output_type":"stream","text":["Collecting seaborn\n","\u001b[?25l  Downloading https://files.pythonhosted.org/packages/bc/45/5118a05b0d61173e6eb12bc5804f0fbb6f196adb0a20e0b16efc2b8e98be/seaborn-0.11.0-py3-none-any.whl (283kB)\n","\u001b[K     |████████████████████████████████| 286kB 4.2MB/s \n","\u001b[?25hRequirement already satisfied, skipping upgrade: matplotlib>=2.2 in /usr/local/lib/python3.6/dist-packages (from seaborn) (3.2.2)\n","Requirement already satisfied, skipping upgrade: scipy>=1.0 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.4.1)\n","Requirement already satisfied, skipping upgrade: pandas>=0.23 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.0.5)\n","Requirement already satisfied, skipping upgrade: numpy>=1.15 in /usr/local/lib/python3.6/dist-packages (from seaborn) (1.18.5)\n","Requirement already satisfied, skipping upgrade: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.2->seaborn) (0.10.0)\n","Requirement already satisfied, skipping upgrade: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.2->seaborn) (1.2.0)\n","Requirement already satisfied, skipping upgrade: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.2->seaborn) (2.4.7)\n","Requirement already satisfied, skipping upgrade: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib>=2.2->seaborn) (2.8.1)\n","Requirement already satisfied, skipping upgrade: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.23->seaborn) (2018.9)\n","Requirement already satisfied, skipping upgrade: six in /usr/local/lib/python3.6/dist-packages (from cycler>=0.10->matplotlib>=2.2->seaborn) (1.15.0)\n","Installing collected packages: seaborn\n","  Found existing installation: seaborn 0.10.1\n","    Uninstalling seaborn-0.10.1:\n","      Successfully uninstalled seaborn-0.10.1\n","Successfully installed seaborn-0.11.0\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"3wVTcImJcALB","executionInfo":{"status":"ok","timestamp":1601041965001,"user_tz":300,"elapsed":1739,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"ad411c56-1bf6-4e29-e5bc-60f1f0eab8e2","colab":{"base_uri":"https://localhost:8080/","height":71}},"source":["# Importacion de librerias\n","import seaborn as sns\n","import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import statsmodels.api as sm\n","# Configuramos el estilo GGPLOT para las visualizaciones\n","#plt.style.use('ggplot')"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n","  import pandas.util.testing as tm\n"],"name":"stderr"}]},{"cell_type":"code","metadata":{"id":"Nhoxc_g1yy33"},"source":["plt.style.use('ggplot')"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"7Qj_MWW-uaOO"},"source":["## **1. Adquisión e Integracion de los datos**\n","Primero realizamos la adquisión de los datos, para el presente estudio, se tendrán en cuenta las tres primeras hojas: **'SINIESTROS'**, **'ACTORES'** y **'VEHICULOS'**.\n","\n","Vamos entonces a guardar en la variables `df_siniestros` un dataframe con los datos de los accidentes, en la variable `df_actores` un dataframe con los datos de las personas y en `df_vehiculos` un dataframe con los datos de los vehiuclos implicados."]},{"cell_type":"code","metadata":{"id":"cuj1t2B03eyt","executionInfo":{"status":"ok","timestamp":1601042255627,"user_tz":300,"elapsed":285851,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"960bf724-9c70-4d96-e60f-27221af27449","colab":{"resources":{"http://localhost:8080/nbextensions/google.colab/files.js":{"data":"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","ok":true,"headers":[["content-type","application/javascript"]],"status":200,"status_text":""}},"base_uri":"https://localhost:8080/","height":89}},"source":["from google.colab import files\n","uploaded = files.upload()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/html":["\n","     <input type=\"file\" id=\"files-21973e74-6a8e-459a-8fb8-7ae55c3298e8\" name=\"files[]\" multiple disabled\n","        style=\"border:none\" />\n","     <output id=\"result-21973e74-6a8e-459a-8fb8-7ae55c3298e8\">\n","      Upload widget is only available when the cell has been executed in the\n","      current browser session. Please rerun this cell to enable.\n","      </output>\n","      <script src=\"/nbextensions/google.colab/files.js\"></script> "],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{"tags":[]}},{"output_type":"stream","text":["Saving accidentalidad_bogota.xlsx to accidentalidad_bogota.xlsx\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"GySIBgVg3_uY"},"source":["#url_datos_accidentes = 'https://datosabiertos.bogota.gov.co/dataset/0b070626-fe5a-42dc-ae99-92601da166d9/resource/9e3add8e-3f46-42ce-9c0f-419964f6f598/download/2015_2019_siniestralidad_vial.xlsx'\n","import io\n","df_siniestros = pd.read_excel(io.BytesIO(uploaded['accidentalidad_bogota.xlsx']), sheet_name='SINIESTROS')\n","df_actores = pd.read_excel(io.BytesIO(uploaded['accidentalidad_bogota.xlsx']), sheet_name='ACTOR_VIAL')\n","df_vehiculos = pd.read_excel(io.BytesIO(uploaded['accidentalidad_bogota.xlsx']), sheet_name='VEHICULOS')"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"bWyCsMz5u4Ls"},"source":["## **2. Análisis exploratorio de los datos**\n","Ahora vamos a explorar cada uno de los dataframes que hemos almacenado en la etapa de Adquisión de los datos:\n"]},{"cell_type":"markdown","metadata":{"id":"GL14RvPu2s29"},"source":["### **Dataframe `df_siniestros`**\n","\n","  Primero damos un vistazo inicial a estos datos, para conocer los nombres de las columnas, sus tipos de datos, su peso en memoria, la cantidad de filas y valores nulos:\n"]},{"cell_type":"code","metadata":{"id":"9mBU_vUHcALL","executionInfo":{"status":"ok","timestamp":1601042956127,"user_tz":300,"elapsed":176614,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"a8ba1f6e-6fb7-48e3-fdf8-31fb69fc1b4b","colab":{"base_uri":"https://localhost:8080/","height":340}},"source":["df_siniestros.info()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 173443 entries, 0 to 173442\n","Data columns (total 12 columns):\n"," #   Column            Non-Null Count   Dtype \n","---  ------            --------------   ----- \n"," 0   CODIGO_SINIESTRO  173443 non-null  int64 \n"," 1   FECHA             173443 non-null  object\n"," 2   HORA              173443 non-null  object\n"," 3   GRAVEDAD          173443 non-null  object\n"," 4   CLASE             173443 non-null  object\n"," 5   CHOQUE_CON        147737 non-null  object\n"," 6   OBJETO_FIJO       5514 non-null    object\n"," 7   DIRECCION         173443 non-null  object\n"," 8   TOTAL_MUERTOS     173443 non-null  int64 \n"," 9   TOTAL_HERIDOS     173443 non-null  int64 \n"," 10  LOCALIDAD         173443 non-null  object\n"," 11  DISENO_LUGAR      173443 non-null  object\n","dtypes: int64(3), object(9)\n","memory usage: 15.9+ MB\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"-ESFWlLuyJiW"},"source":["Con lo anterior podemos observar que el dataframe `df_siniestros` cuenta con 173443 filas, posee un total de 11 columnas, de las cuales 3 de ellas son de tipo entero; importante mencionar que la columna **CODIGO_SINIESTRO** solo nos sirve para identificar al accidente, no es relevante para realizar procesos estadisticos como promedios. En almacenamiento en memoria vemos que usa 15.9MB. Y las columnas **OBJETO_FIJO** y **CHOQUE_CON** tienen valores nulos.\n","\n","Ahora vamos a explorar las estadisticas descriptivas mas comunes de este dataframe usando `describe()`."]},{"cell_type":"code","metadata":{"id":"yectQReycALO","executionInfo":{"status":"ok","timestamp":1601042956128,"user_tz":300,"elapsed":176603,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"201807e9-d6cb-4143-dcb1-5b30f3a09c2c","colab":{"base_uri":"https://localhost:8080/","height":297}},"source":["df_siniestros[['TOTAL_MUERTOS', 'TOTAL_HERIDOS']].describe()"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>TOTAL_MUERTOS</th>\n","      <th>TOTAL_HERIDOS</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>173443.000000</td>\n","      <td>173443.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>0.015538</td>\n","      <td>0.471135</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>0.127536</td>\n","      <td>0.975981</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>0.000000</td>\n","      <td>1.000000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>4.000000</td>\n","      <td>72.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["       TOTAL_MUERTOS  TOTAL_HERIDOS\n","count  173443.000000  173443.000000\n","mean        0.015538       0.471135\n","std         0.127536       0.975981\n","min         0.000000       0.000000\n","25%         0.000000       0.000000\n","50%         0.000000       0.000000\n","75%         0.000000       1.000000\n","max         4.000000      72.000000"]},"metadata":{"tags":[]},"execution_count":63}]},{"cell_type":"markdown","metadata":{"id":"xQn6gdKVbN9D"},"source":["Los datos anteriores nos ofrecen una información valiosa acerca de los muertos y heridos. Podemos observar que el **máximo número de heridos es de 72 personas**, mientras que **4 es el máximo número de muertos**. También vemos que los datos tienen una desviación estandar pequeña, para los heridos tenemos un valor de 0.98 aproximadamente, y para los muertos, tenemos un valor de 0.13 aproximadamente, siendo además la media 0.01 para los muertos y 0.47 para los heridos, podemos decir que los datos no están muy dispersos con respecto a su media. Por lo que, si graficamos en un histograma la distribución de estos datos, tendremos una curva, en realizad angosta y la mayoría de los datos concentrados cerca a la media. Otro dato que podemos obtener es el rango, haciendo la resta entre mínimo y máximo, dándonos 68 para esta muestra.\n","\n","Ahora, revisemos la curtosis de esta muestra, para conocer la forma del pico de la distribución."]},{"cell_type":"code","metadata":{"id":"9kljP004fLK4","executionInfo":{"status":"ok","timestamp":1601042956130,"user_tz":300,"elapsed":176593,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"48726e29-318b-4cc5-86ab-c9cf14199bd3","colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["df_siniestros[['TOTAL_MUERTOS', 'TOTAL_HERIDOS']].kurt()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["TOTAL_MUERTOS     86.705634\n","TOTAL_HERIDOS    616.730827\n","dtype: float64"]},"metadata":{"tags":[]},"execution_count":64}]},{"cell_type":"markdown","metadata":{"id":"kqZzNCXBgKdL"},"source":["Esto nos confirma lo que sospechabamos, el metodo `kurt() `de Pandas realiza el cálculo de la curtosis con el coeficiente de Fisher, si este es mayor que cero , nos indica que los datos tienden a estar proximos a la media. El pico de está distribución debería ser angosto.\n","\n","Si graficamos la distribución de estas variables, tenemos lo siguiente:"]},{"cell_type":"code","metadata":{"id":"z4B_pdi0q4H_","executionInfo":{"status":"ok","timestamp":1601042959168,"user_tz":300,"elapsed":179617,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"7814b9c6-c2ce-4fb6-aae8-59170112fc68","colab":{"base_uri":"https://localhost:8080/","height":575}},"source":["fig, ax = plt.subplots(dpi=120)\n","ax.set_title('Distribución del total de heridos')\n","# Primera grafica, distribucion del total de heridos\n","sns.distplot(df_siniestros['TOTAL_HERIDOS'], ax=ax)\n","ax.set_xlabel('Total de heridos')\n","ax_zoom = fig.add_axes([0.4, 0.2, 0.3, 0.3], facecolor='lightblue')\n","sns.distplot(df_siniestros['TOTAL_HERIDOS'], ax=ax_zoom)\n","ax_zoom.set_title('Zoom')\n","ax_zoom.set_xlim(-0.5, 5.0)\n","ax_zoom.set_xlabel('')\n","ax_zoom.set_ylabel('');"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n","  warnings.warn(msg, FutureWarning)\n","/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n","  warnings.warn(msg, FutureWarning)\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x480 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"Y-MFsrTZhcxd","executionInfo":{"status":"ok","timestamp":1601042961881,"user_tz":300,"elapsed":182314,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"acd32c4a-5e91-4038-8c56-bdac7921f6d9","colab":{"base_uri":"https://localhost:8080/","height":575}},"source":["fig, ax = plt.subplots(dpi=120)\n","ax.set_title('Distribución del total de muertos')\n","# Primera grafica, distribucion del total de heridos\n","sns.distplot(df_siniestros['TOTAL_MUERTOS'], ax=ax)\n","ax.set_xlabel('Total de muertos')\n","ax_zoom2 = fig.add_axes([0.4, 0.2, 0.3, 0.3], facecolor='lightblue')\n","sns.distplot(df_siniestros['TOTAL_MUERTOS'], ax=ax_zoom2)\n","ax_zoom2.set_title('Zoom')\n","ax_zoom2.set_xlim(-0.05, 0.5)\n","ax_zoom2.set_xlabel('')\n","ax_zoom2.set_ylabel('');"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n","  warnings.warn(msg, FutureWarning)\n","/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n","  warnings.warn(msg, FutureWarning)\n"],"name":"stderr"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x480 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"_f-DhETVikOC"},"source":["Lo gráfica anterior termina de afirmar nuestros cálculos, los datos del total de muertos y heridos no están muy dispersos y sus valores tienden a ser cercanos a la media.\n","\n","Por último, miremos la asimetría, definida en pandas con el método `skew() `, nos dice hacia donde tiende la curva de la distribución."]},{"cell_type":"code","metadata":{"id":"t96x74kQnQVc","executionInfo":{"status":"ok","timestamp":1601042961882,"user_tz":300,"elapsed":182301,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"3441a620-37f6-4340-bcf1-90c3795402d7","colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["df_siniestros[['TOTAL_MUERTOS', 'TOTAL_HERIDOS']].skew()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["TOTAL_MUERTOS     8.707379\n","TOTAL_HERIDOS    13.837383\n","dtype: float64"]},"metadata":{"tags":[]},"execution_count":67}]},{"cell_type":"markdown","metadata":{"id":"G6zQOcCqnnT6"},"source":["Este dato nos confirma algo que ya hemos visto en la grafica, las distribuciones tienen una asínmetría positiva. Otro dato que nos gustaría saber es la suma del total de muertos y heridos a través de los años. La calculamos en la siguiente celda."]},{"cell_type":"code","metadata":{"id":"JrEhnTuOeaAn","executionInfo":{"status":"ok","timestamp":1601042961883,"user_tz":300,"elapsed":182293,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"851102ca-c270-4a06-de2e-7a17f04681a2","colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["df_siniestros[['TOTAL_MUERTOS', 'TOTAL_HERIDOS']].sum()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["TOTAL_MUERTOS     2695\n","TOTAL_HERIDOS    81715\n","dtype: int64"]},"metadata":{"tags":[]},"execution_count":68}]},{"cell_type":"markdown","metadata":{"id":"uAb48Dk10d_Z"},"source":["Por otra parte, debemos conocer los atributos categóricos de este dataframe, para saber qué valores pueden tomar, nos vamos a centrar en los atributos: **GRAVEDAD**, **CLASE**, **CHOQUE_CON**, **OBJETO_FIJO** y **DISENO_LUGAR** para ello haremos uso del método `unique()`"]},{"cell_type":"code","metadata":{"id":"F0VgzWpR1WQH","executionInfo":{"status":"ok","timestamp":1601042961883,"user_tz":300,"elapsed":182283,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"a94a787a-8b16-48c0-b181-ffcd5eb7d612","colab":{"base_uri":"https://localhost:8080/","height":255}},"source":["print(f\"GRAVEDAD: {df_siniestros['GRAVEDAD'].unique()}\\n\")\n","print(f\"CLASE: {df_siniestros['CLASE'].unique()}\\n\")\n","print(f\"OBJETO_FIJO: {df_siniestros['OBJETO_FIJO'].unique()}\\n\")\n","print(f\"CHOQUE_CON: {df_siniestros['CHOQUE_CON'].unique()}\\n\")\n","print(f\"DISENO_LUGAR: {df_siniestros['DISENO_LUGAR'].unique()}\\n\")\n"],"execution_count":null,"outputs":[{"output_type":"stream","text":["GRAVEDAD: ['Con Heridos' 'Solo Daños' 'Con Muertos']\n","\n","CLASE: ['Choque' 'Volcamiento' 'Atropello' 'Otro' 'Caida de ocupante'\n"," 'Autolesion' 'Incendio']\n","\n","OBJETO_FIJO: [nan 'Muro' 'Inmueble' 'Vehiculo estacionado' 'Poste' 'Barandas' 'Arbol'\n"," 'Valla, Señal' 'Otro' 'Tarima, Caseta' 'Semaforo' 'Hidrante']\n","\n","CHOQUE_CON: ['Vehiculo' nan 'Objeto Fijo' 'Tren' 'Semoviente']\n","\n","DISENO_LUGAR: ['Interseccion' 'Tramo de Via' 'Paso elevado' 'Lote o predio'\n"," 'Paso inferior' 'Puente' 'Paso a nivel' 'Glorieta' 'Cicloruta'\n"," 'Via peatonal' 'Ponton' 'Tunel' 'Via troncal']\n","\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"i4icNER1cALR"},"source":["Con base en los procesos realizados anteriormente, podemos caracterizar un poco mejor el conjunto de datos:\n","\n","| Variable | Definición\t| Valores | \n","| --- | --- | --- |\n","| CODIGO_SINIESTRO | Identificador del accidente | |\n","| FECHA \t| Fecha en la que ocurrio el accidente | |\n","| HORA \t| Hora en la que ocurrio el accidente \t| |\n","| GRAVEDAD |\tGravedad del accidente \t| \"Solo Daños\", \"Con Heridos\" o \"Con muertos\" |\n","| CLASE |\tClase de accidente ocurrido \t| \"Choque\", \"Atropello\", \"Caida de ocupante\", \"Volcamiento\", \"Otro\", \"Incendio\", \"Autolesion\"|\n","| CHOQUE_CON |\tHace alución al objeto con el cual se produjo el choque \t| \"Vehiculo\", 'Objeto Fijo', \"Semoviente\" o \"Tren\"  |\n","| OBJETO_FIJO |\tHace alución a algún objeto fijo con el cual ocurrio el choque | \"Vehiculo estacionado\", \"Poste\", \"Muro\", \"Inmueble\", \"Barandas\", \"Otro\", \"Valla, Señal\", \"Arbol\", \"Semaforo\", \"Tarima, Caseta\", \"Hidrante\". |\t\n","| DIRECCION \t| Dirección donde tuvo lugar el accidente | |\t\n","| TOTAL_MUERTOS | Número de muertos totales del accidente | |\n","| TOTAL_HERIDOS | Número de heridos totales del accidente |\t|\n","| LOCALIDAD |Localidad de Bogotá donde ocurrió el siniestro| |\n","| DISENO_LUGAR | Descripción del lugar donde ocurrio el accidente|\t\"Tramo de Via\", \"Interseccion\", \"Glorieta\", \"Lote o predio\", \"Paso elevado\", \"Paso inferior\", \"Puente\", \"Paso a nivel\", \"Cicloruta\", \"Via peatonal\", \"Tunel\", \"Ponton\" y \"Via troncal\" |\n","\n","Lo mismo hacemos para los otros dos Dataframes."]},{"cell_type":"markdown","metadata":{"id":"GdvOb3Ek4GiO"},"source":["### **Dataframe `df_actores`**\n","\n","Primero realizamos el vistazo inicial con el método `info()`"]},{"cell_type":"code","metadata":{"id":"7DO7H49K4dcp","executionInfo":{"status":"ok","timestamp":1601042961884,"user_tz":300,"elapsed":182274,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"9a03b053-afa4-4e36-e7f7-bdc8439938fb","colab":{"base_uri":"https://localhost:8080/","height":255}},"source":["df_actores.info()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 374078 entries, 0 to 374077\n","Data columns (total 7 columns):\n"," #   Column            Non-Null Count   Dtype  \n","---  ------            --------------   -----  \n"," 0   CODIGO_SINIESTRO  374078 non-null  int64  \n"," 1   FECHA             374078 non-null  object \n"," 2   CONDICION         374078 non-null  object \n"," 3   ESTADO            374078 non-null  object \n"," 4   EDAD              367491 non-null  float64\n"," 5   SEXO              374078 non-null  object \n"," 6   VEHICULO          352757 non-null  object \n","dtypes: float64(1), int64(1), object(5)\n","memory usage: 20.0+ MB\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"5hV4CQod4ipb"},"source":["Vemos que es un dataset mas grande que `df_accidentes`, esto tiene sentido ya que en un mismo accidente pueden verse implicadas varias personas, con el análisis exploratorio hecho anteriormente, vimos que en un solo accidente se vieron implicados 72 personas heridas. \n","\n","En total tenemos 374078 filas, con 6 columnas, de las cuales dos son variables numéricas, **CODIGO_SINIESTRO** y **EDAD**. El resto, son variables categóricas. También, podemos observar que las columnas **EDAD** y **VEHICULO** presentan valores nulos.\n","\n","Ahora vamos a usar `describe()` para obtener las estadisticas mas comunes."]},{"cell_type":"code","metadata":{"id":"7PbjpaZK5lOx","executionInfo":{"status":"ok","timestamp":1601042961885,"user_tz":300,"elapsed":182266,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"563dbc96-9563-465d-daae-3e4e8afe85de","colab":{"base_uri":"https://localhost:8080/","height":297}},"source":["df_actores[['EDAD']].describe()"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>EDAD</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>count</th>\n","      <td>367491.000000</td>\n","    </tr>\n","    <tr>\n","      <th>mean</th>\n","      <td>37.834722</td>\n","    </tr>\n","    <tr>\n","      <th>std</th>\n","      <td>14.261490</td>\n","    </tr>\n","    <tr>\n","      <th>min</th>\n","      <td>-2.000000</td>\n","    </tr>\n","    <tr>\n","      <th>25%</th>\n","      <td>27.000000</td>\n","    </tr>\n","    <tr>\n","      <th>50%</th>\n","      <td>36.000000</td>\n","    </tr>\n","    <tr>\n","      <th>75%</th>\n","      <td>47.000000</td>\n","    </tr>\n","    <tr>\n","      <th>max</th>\n","      <td>120.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                EDAD\n","count  367491.000000\n","mean       37.834722\n","std        14.261490\n","min        -2.000000\n","25%        27.000000\n","50%        36.000000\n","75%        47.000000\n","max       120.000000"]},"metadata":{"tags":[]},"execution_count":71}]},{"cell_type":"markdown","metadata":{"id":"Gx-wMEi65uvJ"},"source":["Con lo anterior, podemos llegar a algunas conclusiones: Hay **algunos outliers como -2** (no pueden haber edades negativas), y tal vez 120, que debemos ir a revisar antes de algun proceso de correlación, por ejemplo. **El promedio de edades está en los 37 años aproximandamente**, la mitad de las personas que se vieron implicadas en accidentes de transito entre 2015 y 2019 tenian al rededor de 36 años, esto nos lo dice el Cuartil 2.\n","\n","También podemos ver que la desviación estándar es mucho mayor a cero, lo que nos dice que **los datos están algo dispersos**, por último miremos la curtosis, para conocer el ancho de la curva o pico de las edades."]},{"cell_type":"code","metadata":{"id":"YuppfDKAlSmJ","executionInfo":{"status":"ok","timestamp":1601042961886,"user_tz":300,"elapsed":182257,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"315951f2-4762-45d4-e358-a64d7541f526","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["df_actores['EDAD'].kurt()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.715000341514263"]},"metadata":{"tags":[]},"execution_count":72}]},{"cell_type":"markdown","metadata":{"id":"2QPWN4AvliU0"},"source":["La curtosis nos dio un valor levemente mayor a 0, lo que indica que **los datos NO están concentrados en la media**, tendremos una curva mas abierta, la curva debería formar ***casi*** una distribución normal. Si graficamos la distribución podemos entonces, darnos cuenta de nuestros cálculos."]},{"cell_type":"code","metadata":{"id":"7pvo27fkjnrJ","executionInfo":{"status":"ok","timestamp":1601042964900,"user_tz":300,"elapsed":185262,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"6dccb726-b832-4095-b2b5-bf65f6f2ba24","colab":{"base_uri":"https://localhost:8080/","height":336}},"source":["sns.distplot(x=df_actores['EDAD'])"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/seaborn/distributions.py:2551: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n","  warnings.warn(msg, FutureWarning)\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["<matplotlib.axes._subplots.AxesSubplot at 0x7fee4a0415c0>"]},"metadata":{"tags":[]},"execution_count":73},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"djUeKDK6ZT5E"},"source":["Ahora vamos a revisar en detalle los atributos categóricos, con el fin de averiguar que valores pueden tomar, para ello vamos a hacer uso de nuevo del método `unique()`. Vamos a ejecutar este metodo con los atributos categóricos **'CONDICION'**, **'ESTADO'** y **'SEXO'**"]},{"cell_type":"code","metadata":{"id":"R2CP8pvVZiWe","executionInfo":{"status":"ok","timestamp":1601042964901,"user_tz":300,"elapsed":185254,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"44e443a3-7947-41b5-b9cb-81faf7fa6c82","colab":{"base_uri":"https://localhost:8080/","height":119}},"source":["print(f\"CONDICION: {df_actores['CONDICION'].unique()}\\n\")\n","print(f\"ESTADO: {df_actores['ESTADO'].unique()}\\n\")\n","print(f\"SEXO: {df_actores['SEXO'].unique()}\\n\")"],"execution_count":null,"outputs":[{"output_type":"stream","text":["CONDICION: ['CONDUCTOR' 'PEATON' 'PASAJERO' 'MOTOCICLISTA' 'CICLISTA']\n","\n","ESTADO: ['ILESO' 'HERIDO' 'SIN INFORMACION' 'MUERTO']\n","\n","SEXO: ['MASCULINO' 'FEMENINO' 'SIN INFORMACION']\n","\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"qJDnFJZtaHAs"},"source":["Ahora, queremos ver la cantidad de apariciones de los valores anteriormente mencionados, para ello hacemos uso del método `value_counts()`"]},{"cell_type":"code","metadata":{"id":"MGwi2-XaaTe8","executionInfo":{"status":"ok","timestamp":1601042964902,"user_tz":300,"elapsed":185244,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"38f72fae-56d7-45c9-b573-9a5ac7a8ec42","colab":{"base_uri":"https://localhost:8080/","height":119}},"source":["df_actores['CONDICION'].value_counts()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["CONDUCTOR       273024\n","MOTOCICLISTA     45066\n","PASAJERO         24369\n","PEATON           21321\n","CICLISTA         10298\n","Name: CONDICION, dtype: int64"]},"metadata":{"tags":[]},"execution_count":75}]},{"cell_type":"code","metadata":{"id":"cBWsj_Zzahtv","executionInfo":{"status":"ok","timestamp":1601042964903,"user_tz":300,"elapsed":185234,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"eedd0f00-9266-4b21-8fae-9dd940a1a6be","colab":{"base_uri":"https://localhost:8080/","height":102}},"source":["df_actores['ESTADO'].value_counts()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["ILESO              287582\n","HERIDO              81448\n","MUERTO               2697\n","SIN INFORMACION      2351\n","Name: ESTADO, dtype: int64"]},"metadata":{"tags":[]},"execution_count":76}]},{"cell_type":"code","metadata":{"id":"AE7-NOZ0aoMv","executionInfo":{"status":"ok","timestamp":1601042964903,"user_tz":300,"elapsed":185224,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"a55e2540-fac5-4b69-cbe6-266575b991cc","colab":{"base_uri":"https://localhost:8080/","height":85}},"source":["df_actores['SEXO'].value_counts()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["MASCULINO          308236\n","FEMENINO            57525\n","SIN INFORMACION      8317\n","Name: SEXO, dtype: int64"]},"metadata":{"tags":[]},"execution_count":77}]},{"cell_type":"markdown","metadata":{"id":"ZZ5nQmGIa0tv"},"source":["Con base en los procesos realizados anteriormente, podemos caracterizar mucho mejor el conjunto de datos:\n","\n","| Variable | Definición\t| Valores | \n","| --- | --- | --- |\n","| CODIGO SINIESTRO | Codigo que idengtifica al siniestro|| |FECHA| Fecha en la cual se registró el sinisestro||\n","| CONDICION| Rol que cumple la persona en el accidente|'CONDUCTOR' 'PEATON' 'PASAJERO' 'MOTOCICLISTA' 'CICLISTA' |\n","| ESTADO | Estado de salud de la persona luego del accidente | 'ILESO' 'HERIDO' 'SIN INFORMACION' 'MUERTO' |\n","| EDAD | Edad de la persona implicada en el siniestro| |\n","| SEXO | Sexo de la persona implicada| 'MASCULINO' 'FEMENINO' 'SIN INFORMACION'|\n","| VEHICULO | Identificador del vehiculo | |"]},{"cell_type":"markdown","metadata":{"id":"s5r8zDF6b_LE"},"source":["### **Dataframe `df_vehiculos`**\n","\n","Siguiendo con nuestro analísis exploratorio, queda por revisar el dataframe df_vehiculos. Primero realizamos el vistazo general con el método `info()`."]},{"cell_type":"code","metadata":{"id":"7gENfp1rcW_e","executionInfo":{"status":"ok","timestamp":1601042965136,"user_tz":300,"elapsed":185447,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"e88ed898-5fd2-491b-bce0-28a2e4e1e0fe","colab":{"base_uri":"https://localhost:8080/","height":238}},"source":["df_vehiculos.info()"],"execution_count":null,"outputs":[{"output_type":"stream","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 328390 entries, 0 to 328389\n","Data columns (total 6 columns):\n"," #   Column            Non-Null Count   Dtype \n","---  ------            --------------   ----- \n"," 0   CODIGO_SINIESTRO  328390 non-null  int64 \n"," 1   FECHA             328390 non-null  object\n"," 2   VEHICULO          328390 non-null  object\n"," 3   CLASE             326355 non-null  object\n"," 4   SERVICIO          316038 non-null  object\n"," 5   ENFUGA            328390 non-null  object\n","dtypes: int64(1), object(5)\n","memory usage: 15.0+ MB\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"-NkeQFcXcsft"},"source":["Con lo anterior, podemos ver que hay un total de 328390 filas, de igual forma podemos decir que estos datos tienen sentido, puesto que en un Siniestro pueden verse implicados mas de un vehículo. Los atributos CLASE y SERVICIO son los unico con valores faltantes, además podemos observar que todos los atributos de este conjunto de datos son categóricos.\n","\n","Miremos mas de cerca los atributos categóricos de este dataframe, en especial **CLASE**, **SERVICIO** y ENFUGA."]},{"cell_type":"code","metadata":{"id":"hvYitPE1dQiR","executionInfo":{"status":"ok","timestamp":1601042965137,"user_tz":300,"elapsed":185437,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"84caf949-4f9e-40b6-f454-bade82969ee0","colab":{"base_uri":"https://localhost:8080/","height":153}},"source":["print(f\"CLASE: {df_vehiculos['CLASE'].unique()}\\n\")\n","print(f\"SERVICIO: {df_vehiculos['SERVICIO'].unique()}\\n\")\n","print(f\"ENFUGA: {df_vehiculos['ENFUGA'].unique()}\\n\")"],"execution_count":null,"outputs":[{"output_type":"stream","text":["CLASE: ['Microbus' 'Motocicleta' 'Bus' 'Automovil' 'Campero' 'Camioneta'\n"," 'Bicicleta' 'Camion, Furgon' 'Volqueta' 'Tractocamion' nan 'Buseta'\n"," 'Motocarro' 'Motociclo' 'Cuatrimoto']\n","\n","SERVICIO: ['Publico' 'Particular' 'Oficial' nan 'Diplomatico']\n","\n","ENFUGA: ['N' 'S']\n","\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"yBCvw3JFd4NV"},"source":["Ahora miremos la cantidad de apariciones de las variables categóricas anteriores."]},{"cell_type":"code","metadata":{"id":"CgJKAgwBd-p3","executionInfo":{"status":"ok","timestamp":1601042965138,"user_tz":300,"elapsed":185428,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"49c1f850-2dd9-4cfd-86c7-78becddc2db0","colab":{"base_uri":"https://localhost:8080/","height":272}},"source":["df_vehiculos['CLASE'].value_counts()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Automovil         136721\n","Camioneta          45250\n","Motocicleta        45066\n","Bus                34206\n","Camion, Furgon     17948\n","Campero            14349\n","Bicicleta          10329\n","Microbus            9546\n","Buseta              5027\n","Tractocamion        4570\n","Volqueta            3259\n","Motocarro             76\n","Motociclo              5\n","Cuatrimoto             3\n","Name: CLASE, dtype: int64"]},"metadata":{"tags":[]},"execution_count":80}]},{"cell_type":"code","metadata":{"id":"jFpA37RreGxo","executionInfo":{"status":"ok","timestamp":1601042965139,"user_tz":300,"elapsed":185419,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"a50580df-d4ed-4dbf-d32e-5330723d569c","colab":{"base_uri":"https://localhost:8080/","height":102}},"source":["df_vehiculos['SERVICIO'].value_counts()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Particular     178634\n","Publico        128881\n","Oficial          8442\n","Diplomatico        81\n","Name: SERVICIO, dtype: int64"]},"metadata":{"tags":[]},"execution_count":81}]},{"cell_type":"code","metadata":{"id":"JKZ3nn4deOoC","executionInfo":{"status":"ok","timestamp":1601042965383,"user_tz":300,"elapsed":185652,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"4903efbf-b43d-4b50-84e6-d2c0f60d9cd0","colab":{"base_uri":"https://localhost:8080/","height":68}},"source":["df_vehiculos['ENFUGA'].value_counts()"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["N    324082\n","S      4308\n","Name: ENFUGA, dtype: int64"]},"metadata":{"tags":[]},"execution_count":82}]},{"cell_type":"markdown","metadata":{"id":"u-BXsHX4kQsH"},"source":["Ahora, podemos caracterizar de una mejor manera los datos de este dataframe, así:\n","\n","| Variable | Definición\t| Valores | \n","| --- | --- | --- |\n","|CODIGO_SINIESTRO| Identificador del siniestro| |\n","| FECHA | Fecha en la que ocurrió el siniestro| |\n","| VEHICULO| Vehiculo implicado en el accidente| |\n","| CLASE | Clase de vehículo que se vio implicado| 'Microbus' 'Motocicleta' 'Bus' 'Automovil' 'Campero' 'Camioneta' 'Bicicleta' 'Camion, Furgon' 'Volqueta' 'Tractocamion' 'Buseta' 'Motocarro' 'Motociclo' 'Cuatrimoto' |\n","| SERVICIO |Servicio que prestaba el carro| 'Publico' 'Particular' 'Oficial' 'Diplomatico' |\n","| ENFUGA| Nos dice si el carro se dió a la fuga despupes del accidente o no| 'N' 'S' |"]},{"cell_type":"markdown","metadata":{"id":"vjz1E4Gdo7AB"},"source":["# **FASE 2: Preparación de los datos**"]},{"cell_type":"markdown","metadata":{"id":"9roACc3xpYEi"},"source":["### **1. Limpieza de los datos**\n"]},{"cell_type":"markdown","metadata":{"id":"n0CK0p1924qF"},"source":["Con base en el análisis exploratorio que se realizó en la etapa anterior, solamente vamos a tener en cuenta las edades de 0 en adelante, siendo cero los recién nacidos. Además, no vamos a tener en cuenta aquellos registros que no tenga información de sexo, se hace necesario para el cumplimiento de los objetivos poder caracterizar a las personas de acuerdo a esta variable para encontrar comportamientos de los hombres y mujeres en las vías más adelante. Para finalizar, excluimos las personas que hayan salido ilesas de los accidentes, ya que según los objetivos del proyecto, nos interesan aquellos accidentes que temrinaron con alguna persona herida o fallecida."]},{"cell_type":"code","metadata":{"id":"0VsE_XTYzAas","executionInfo":{"status":"ok","timestamp":1601042965384,"user_tz":300,"elapsed":185641,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"dbd3d6a0-9009-4dba-cf6d-d98a1befed04","colab":{"base_uri":"https://localhost:8080/","height":359}},"source":["df_actores_limpio = df_actores[~(df_actores['SEXO'] == 'SIN INFORMACION') & (df_actores['EDAD'] >= 0) & ~(df_actores['ESTADO'] == 'ILESO')]\n","df_actores_limpio.sample(10)"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>CODIGO_SINIESTRO</th>\n","      <th>FECHA</th>\n","      <th>CONDICION</th>\n","      <th>ESTADO</th>\n","      <th>EDAD</th>\n","      <th>SEXO</th>\n","      <th>VEHICULO</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>171628</th>\n","      <td>4482461</td>\n","      <td>22/05/2017</td>\n","      <td>MOTOCICLISTA</td>\n","      <td>HERIDO</td>\n","      <td>47.0</td>\n","      <td>MASCULINO</td>\n","      <td>4482461-2</td>\n","    </tr>\n","    <tr>\n","      <th>359943</th>\n","      <td>10500805</td>\n","      <td>23/10/2019</td>\n","      <td>MOTOCICLISTA</td>\n","      <td>HERIDO</td>\n","      <td>25.0</td>\n","      <td>MASCULINO</td>\n","      <td>10500805-1</td>\n","    </tr>\n","    <tr>\n","      <th>308618</th>\n","      <td>10476588</td>\n","      <td>23/02/2019</td>\n","      <td>CICLISTA</td>\n","      <td>HERIDO</td>\n","      <td>24.0</td>\n","      <td>MASCULINO</td>\n","      <td>10476588-2</td>\n","    </tr>\n","    <tr>\n","      <th>372163</th>\n","      <td>10506365</td>\n","      <td>20/12/2019</td>\n","      <td>PASAJERO</td>\n","      <td>HERIDO</td>\n","      <td>49.0</td>\n","      <td>FEMENINO</td>\n","      <td>10506365-1</td>\n","    </tr>\n","    <tr>\n","      <th>51184</th>\n","      <td>4425548</td>\n","      <td>02/10/2015</td>\n","      <td>PASAJERO</td>\n","      <td>HERIDO</td>\n","      <td>27.0</td>\n","      <td>MASCULINO</td>\n","      <td>4425548-4</td>\n","    </tr>\n","    <tr>\n","      <th>319229</th>\n","      <td>10481525</td>\n","      <td>11/04/2019</td>\n","      <td>PEATON</td>\n","      <td>HERIDO</td>\n","      <td>21.0</td>\n","      <td>MASCULINO</td>\n","      <td>NaN</td>\n","    </tr>\n","    <tr>\n","      <th>30168</th>\n","      <td>4415455</td>\n","      <td>12/06/2015</td>\n","      <td>MOTOCICLISTA</td>\n","      <td>HERIDO</td>\n","      <td>21.0</td>\n","      <td>MASCULINO</td>\n","      <td>4415455-2</td>\n","    </tr>\n","    <tr>\n","      <th>340443</th>\n","      <td>10491560</td>\n","      <td>23/07/2019</td>\n","      <td>MOTOCICLISTA</td>\n","      <td>HERIDO</td>\n","      <td>21.0</td>\n","      <td>MASCULINO</td>\n","      <td>10491560-1</td>\n","    </tr>\n","    <tr>\n","      <th>326724</th>\n","      <td>10484966</td>\n","      <td>18/05/2019</td>\n","      <td>MOTOCICLISTA</td>\n","      <td>MUERTO</td>\n","      <td>29.0</td>\n","      <td>MASCULINO</td>\n","      <td>10484966-1</td>\n","    </tr>\n","    <tr>\n","      <th>18187</th>\n","      <td>4409836</td>\n","      <td>12/04/2015</td>\n","      <td>PASAJERO</td>\n","      <td>HERIDO</td>\n","      <td>46.0</td>\n","      <td>FEMENINO</td>\n","      <td>4409836-1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["        CODIGO_SINIESTRO       FECHA     CONDICION  ...  EDAD       SEXO    VEHICULO\n","171628           4482461  22/05/2017  MOTOCICLISTA  ...  47.0  MASCULINO   4482461-2\n","359943          10500805  23/10/2019  MOTOCICLISTA  ...  25.0  MASCULINO  10500805-1\n","308618          10476588  23/02/2019      CICLISTA  ...  24.0  MASCULINO  10476588-2\n","372163          10506365  20/12/2019      PASAJERO  ...  49.0   FEMENINO  10506365-1\n","51184            4425548  02/10/2015      PASAJERO  ...  27.0  MASCULINO   4425548-4\n","319229          10481525  11/04/2019        PEATON  ...  21.0  MASCULINO         NaN\n","30168            4415455  12/06/2015  MOTOCICLISTA  ...  21.0  MASCULINO   4415455-2\n","340443          10491560  23/07/2019  MOTOCICLISTA  ...  21.0  MASCULINO  10491560-1\n","326724          10484966  18/05/2019  MOTOCICLISTA  ...  29.0  MASCULINO  10484966-1\n","18187            4409836  12/04/2015      PASAJERO  ...  46.0   FEMENINO   4409836-1\n","\n","[10 rows x 7 columns]"]},"metadata":{"tags":[]},"execution_count":83}]},{"cell_type":"markdown","metadata":{"id":"SR5siToN3ydZ"},"source":["Para conocer el nivel de accidentalidad de la capital, se tomarán solo los siniestros en los cuales se hayan visto implicados heridos o muertos. Ya que, de acuerdo a los objetivos del proyecto nos interesa los accidentes letales, es decir, donde se vio implicado la muerte o estropeo de alguna persona."]},{"cell_type":"code","metadata":{"id":"CI_oxfyZ1cHN","executionInfo":{"status":"ok","timestamp":1601042965385,"user_tz":300,"elapsed":185630,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"919a3172-aca2-4620-94a2-50b25745d2ee","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["df_siniestros_limpio = df_siniestros[\n","    ~((df_siniestros['TOTAL_MUERTOS'] == 0) & (df_siniestros['TOTAL_HERIDOS'] == 0))\n","]\n","len(df_siniestros_limpio)"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["59238"]},"metadata":{"tags":[]},"execution_count":84}]},{"cell_type":"markdown","metadata":{"id":"BHOVygIq8y_H"},"source":["Para el dataframe `df_vehiculos` no se ve necesario limpiar, puesto que tenemos unos datos precisos y siguiendo de la mano con los objetivos, estos no hacen referencia a alguno en particular, por lo que vamos a estudiar todo el conjunto de datos."]},{"cell_type":"markdown","metadata":{"id":"BMBny6gQpbkw"},"source":["### **2. Selección de características**\n","Vamos a eliminar la columna **FECHA**, ya que es un dato que tenemos repetido en los tres dataframes del estudio, esta fecha hace referencia al dia del accidente. Vamos a eliminar esta caracteristica en los dataframes `df_actores_limpio` y `df_vehiculos`."]},{"cell_type":"code","metadata":{"id":"Ij915zyE-SMs"},"source":["#df_actores_limpio.drop(columns='FECHA', inplace=True)\n","#df_vehiculos.drop(columns='FECHA', inplace=True)"],"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"Kevq0jowpfn6"},"source":["### **3. Preporocesamiento y transformación**\n","\n","Vamos a realizar una serie de transformaciones al dataframe `df_siniestros_limpio`, en búsqueda de poder clasificar información de acuerdo a los años, con el fin de ayudar en el cumplimiento del primer objetivo, el cual nnos dice que neceitamos dimensionar como ha evolucionado Bogotá en materia de accidentalidad.\n","\n","Primero creamos una columna ANIO_SINIESTRO, en el cual tendremos el dato del año en el cual ocurrio el accidente."]},{"cell_type":"code","metadata":{"id":"9yQd_dcTBdTk","executionInfo":{"status":"ok","timestamp":1601046099709,"user_tz":300,"elapsed":483,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"d5873af1-969a-4d0b-e067-0dbc7fbfebb5","colab":{"base_uri":"https://localhost:8080/","height":462}},"source":["# Primero hacemos una transformacion al tipo de dato datetime.\n","df_siniestros_limpio['FECHA'] = pd.to_datetime(df_siniestros_limpio['FECHA'], format='%d/%m/%Y', errors='coerce')\n","df_siniestros_limpio['ANIO_SINIESTRO'] = df_siniestros_limpio['FECHA'].dt.year\n","df_siniestros_limpio['ANIO_SINIESTRO'].unique() # array([2015, 2016, 2017, 2018, 2019])\n","\n","df_actores_limpio['FECHA'] = pd.to_datetime(df_actores_limpio['FECHA'], format='%d/%m/%Y', errors='coerce')\n","df_actores_limpio['ANIO_SINIESTRO'] = df_actores_limpio['FECHA'].dt.year\n","df_actores_limpio['ANIO_SINIESTRO'].unique() # array([2015, 2016, 2017, 2018, 2019])\n","\n","df_vehiculos['FECHA'] = pd.to_datetime(df_actores_limpio['FECHA'], format='%d/%m/%Y', errors='coerce')\n","df_vehiculos['ANIO_SINIESTRO'] = df_actores_limpio['FECHA'].dt.year\n","df_vehiculos['ANIO_SINIESTRO'].unique() # array([2015, 2016, 2017, 2018, 2019])"],"execution_count":null,"outputs":[{"output_type":"stream","text":["/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame.\n","Try using .loc[row_indexer,col_indexer] = value instead\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  \n","/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame.\n","Try using .loc[row_indexer,col_indexer] = value instead\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  This is separate from the ipykernel package so we can avoid doing imports until\n","/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame.\n","Try using .loc[row_indexer,col_indexer] = value instead\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  \n","/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:7: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame.\n","Try using .loc[row_indexer,col_indexer] = value instead\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  import sys\n"],"name":"stderr"},{"output_type":"execute_result","data":{"text/plain":["array([  nan, 2015., 2016., 2017., 2018., 2019.])"]},"metadata":{"tags":[]},"execution_count":137}]},{"cell_type":"markdown","metadata":{"id":"zkusBffMh_21"},"source":["# **FASE 3: Análisis de datos**\n","\n","Luego de haber explorado y preparado los datos que vamos a estudiar, queremos realizar algunos análisis usando estadística descriptiva, con el fin de obtener una mayor información, que nos permita dar solución a los objetivos planetados en el presente proyecto."]},{"cell_type":"markdown","metadata":{"id":"AonRjFGO2qA8"},"source":["### **Comportamiento de los ciudadanos en las vías de Bogotá**\n","\n","Con base en los objetivos del proyecto, se desea saber el comportamiento de los habitantes de Bogotá en los accidentes. Obtengamos los numeros de hombres y mujeres implicados en accidentes de tránsito. Para ello se hace uso de una tabla de contingencia que relaciona el año del accidente con el sexo y estado de la persona."]},{"cell_type":"code","metadata":{"id":"MhpHMZxp2muy","executionInfo":{"status":"ok","timestamp":1601042965604,"user_tz":300,"elapsed":185819,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"b348afc6-8329-4bbb-e410-068242aa95fb","colab":{"base_uri":"https://localhost:8080/","height":235}},"source":["accidentes_por_sexo = pd.crosstab(df_actores_limpio['ANIO_SINIESTRO'], df_actores_limpio['SEXO'], normalize='index')\n","accidentes_por_sexo"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>SEXO</th>\n","      <th>FEMENINO</th>\n","      <th>MASCULINO</th>\n","    </tr>\n","    <tr>\n","      <th>ANIO_SINIESTRO</th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2015</th>\n","      <td>0.360833</td>\n","      <td>0.639167</td>\n","    </tr>\n","    <tr>\n","      <th>2016</th>\n","      <td>0.353172</td>\n","      <td>0.646828</td>\n","    </tr>\n","    <tr>\n","      <th>2017</th>\n","      <td>0.361970</td>\n","      <td>0.638030</td>\n","    </tr>\n","    <tr>\n","      <th>2018</th>\n","      <td>0.347566</td>\n","      <td>0.652434</td>\n","    </tr>\n","    <tr>\n","      <th>2019</th>\n","      <td>0.367544</td>\n","      <td>0.632456</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["SEXO            FEMENINO  MASCULINO\n","ANIO_SINIESTRO                     \n","2015            0.360833   0.639167\n","2016            0.353172   0.646828\n","2017            0.361970   0.638030\n","2018            0.347566   0.652434\n","2019            0.367544   0.632456"]},"metadata":{"tags":[]},"execution_count":87}]},{"cell_type":"markdown","metadata":{"id":"LgW2YcsE2Zod"},"source":["Con esta tabla de frecuencias podemos llegar a varias conclusiones. A lo largo de los cinco años siempre fue mayor el número de hombres que se vieron implicados en accidentes de tránsito en comparación a las mujeres, según la tabla de contingencia, aproximadamente el 35% fueron mujeres y el 65% fueron hombres. Sería aconsejable realizar campañas de concientización mayoritariamente a los hombres, pues son ellos los actores principales (sean victimas o causales) de los accidentes de tránsito en Bogotá."]},{"cell_type":"markdown","metadata":{"id":"mojW-y7j5rXW"},"source":["Ahora, vamos a aveirguar la proprción de muertos y heridos entre hombres y mujeres. Para ello hacemos uso de una tabla de contingencia que nos relacione el sexo, el estado y el año en que ocurrieron los siniestros."]},{"cell_type":"code","metadata":{"id":"KHpoW6R49XD9","executionInfo":{"status":"ok","timestamp":1601042965605,"user_tz":300,"elapsed":185810,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"32c828f0-8efa-4b4b-c12d-c6f6c08a46fb","colab":{"base_uri":"https://localhost:8080/","height":266}},"source":["accidentados_por_anio = pd.crosstab(df_actores_limpio['ANIO_SINIESTRO'], [df_actores_limpio['SEXO'], df_actores_limpio['ESTADO']])\n","accidentados_por_anio\n"],"execution_count":null,"outputs":[{"output_type":"execute_result","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 tr th {\n","        text-align: left;\n","    }\n","\n","    .dataframe thead tr:last-of-type th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr>\n","      <th>SEXO</th>\n","      <th colspan=\"3\" halign=\"left\">FEMENINO</th>\n","      <th colspan=\"3\" halign=\"left\">MASCULINO</th>\n","    </tr>\n","    <tr>\n","      <th>ESTADO</th>\n","      <th>HERIDO</th>\n","      <th>MUERTO</th>\n","      <th>SIN INFORMACION</th>\n","      <th>HERIDO</th>\n","      <th>MUERTO</th>\n","      <th>SIN INFORMACION</th>\n","    </tr>\n","    <tr>\n","      <th>ANIO_SINIESTRO</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>2015</th>\n","      <td>5270</td>\n","      <td>101</td>\n","      <td>0</td>\n","      <td>9127</td>\n","      <td>382</td>\n","      <td>5</td>\n","    </tr>\n","    <tr>\n","      <th>2016</th>\n","      <td>5099</td>\n","      <td>116</td>\n","      <td>1</td>\n","      <td>9127</td>\n","      <td>423</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>2017</th>\n","      <td>5421</td>\n","      <td>106</td>\n","      <td>1</td>\n","      <td>9322</td>\n","      <td>413</td>\n","      <td>9</td>\n","    </tr>\n","    <tr>\n","      <th>2018</th>\n","      <td>6593</td>\n","      <td>98</td>\n","      <td>0</td>\n","      <td>12175</td>\n","      <td>384</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2019</th>\n","      <td>6836</td>\n","      <td>115</td>\n","      <td>0</td>\n","      <td>11597</td>\n","      <td>364</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["SEXO           FEMENINO                        MASCULINO                       \n","ESTADO           HERIDO MUERTO SIN INFORMACION    HERIDO MUERTO SIN INFORMACION\n","ANIO_SINIESTRO                                                                 \n","2015               5270    101               0      9127    382               5\n","2016               5099    116               1      9127    423               3\n","2017               5421    106               1      9322    413               9\n","2018               6593     98               0     12175    384               1\n","2019               6836    115               0     11597    364               0"]},"metadata":{"tags":[]},"execution_count":88}]},{"cell_type":"code","metadata":{"id":"nGStm7YZwCKz","executionInfo":{"status":"ok","timestamp":1601042965606,"user_tz":300,"elapsed":185799,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"4da09e63-a2a8-4fd6-c0e6-a021b5e43d62","colab":{"base_uri":"https://localhost:8080/","height":266}},"source":["accidentados_por_anio = pd.crosstab(df_actores_limpio['ANIO_SINIESTRO'], [df_actores_limpio['SEXO'], df_actores_limpio['ESTADO']], normalize='index')\n","accidentados_por_anio"],"execution_count":null,"outputs":[{"output_type":"execute_result","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 tr th {\n","        text-align: left;\n","    }\n","\n","    .dataframe thead tr:last-of-type th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr>\n","      <th>SEXO</th>\n","      <th colspan=\"3\" halign=\"left\">FEMENINO</th>\n","      <th colspan=\"3\" halign=\"left\">MASCULINO</th>\n","    </tr>\n","    <tr>\n","      <th>ESTADO</th>\n","      <th>HERIDO</th>\n","      <th>MUERTO</th>\n","      <th>SIN INFORMACION</th>\n","      <th>HERIDO</th>\n","      <th>MUERTO</th>\n","      <th>SIN INFORMACION</th>\n","    </tr>\n","    <tr>\n","      <th>ANIO_SINIESTRO</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>2015</th>\n","      <td>0.354048</td>\n","      <td>0.006785</td>\n","      <td>0.000000</td>\n","      <td>0.613168</td>\n","      <td>0.025663</td>\n","      <td>0.000336</td>\n","    </tr>\n","    <tr>\n","      <th>2016</th>\n","      <td>0.345250</td>\n","      <td>0.007854</td>\n","      <td>0.000068</td>\n","      <td>0.617984</td>\n","      <td>0.028641</td>\n","      <td>0.000203</td>\n","    </tr>\n","    <tr>\n","      <th>2017</th>\n","      <td>0.354963</td>\n","      <td>0.006941</td>\n","      <td>0.000065</td>\n","      <td>0.610398</td>\n","      <td>0.027043</td>\n","      <td>0.000589</td>\n","    </tr>\n","    <tr>\n","      <th>2018</th>\n","      <td>0.342476</td>\n","      <td>0.005091</td>\n","      <td>0.000000</td>\n","      <td>0.632435</td>\n","      <td>0.019947</td>\n","      <td>0.000052</td>\n","    </tr>\n","    <tr>\n","      <th>2019</th>\n","      <td>0.361464</td>\n","      <td>0.006081</td>\n","      <td>0.000000</td>\n","      <td>0.613209</td>\n","      <td>0.019247</td>\n","      <td>0.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["SEXO            FEMENINO            ... MASCULINO                \n","ESTADO            HERIDO    MUERTO  ...    MUERTO SIN INFORMACION\n","ANIO_SINIESTRO                      ...                          \n","2015            0.354048  0.006785  ...  0.025663        0.000336\n","2016            0.345250  0.007854  ...  0.028641        0.000203\n","2017            0.354963  0.006941  ...  0.027043        0.000589\n","2018            0.342476  0.005091  ...  0.019947        0.000052\n","2019            0.361464  0.006081  ...  0.019247        0.000000\n","\n","[5 rows x 6 columns]"]},"metadata":{"tags":[]},"execution_count":89}]},{"cell_type":"code","metadata":{"id":"BIPzh-YGo3r8","executionInfo":{"status":"ok","timestamp":1601042966175,"user_tz":300,"elapsed":186358,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"52faa346-b3e3-43a6-a4b3-ce53d10bf42a","colab":{"base_uri":"https://localhost:8080/","height":481}},"source":["fig, ax = plt.subplots(figsize=(10, 5))\n","mascara = accidentados_por_anio == 0\n","a = sns.heatmap(accidentados_por_anio, linewidths=5, fmt='.2%', annot=True, mask=mascara, ax=ax)\n","a.set_ylabel('AÑO DEL SINIESTRO');"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x360 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"hgsycMQe7kkL"},"source":["Vemos que a través de los 5 años, hay una mayor proporción de hombres heridos que de mujeres, casi el doble de hombres salieron heridos en accidentes de tránsito con respecto a las mujeres. En el ultimo año 2019, el 36% de las mujeres resultaron heridas (siendo este el año donde más mujeres fallecieron en comparación a los otros), versus un 61% de hombres. En el año 2018 se vio un incremento del 2% en la cantidad de hombres heridos con respecto a los otro años, llegando a un total de 12175.\n","\n","En materia de fallecimientos los hombres tambien van por delante, se puede decir que por cada mujer que fallece en un accidente de tránsito, mueren tres hombres. En el año 2016, fue donde se registró la mayor cantidad de muertes de hombres con 423 fallecidos equivalente a un 2.86%.\n","\n","Continuando con el comportamiento de los ciudadanos, queremos saber la edad de las personas que se ven implicadas en accidentes de tránsito, para ello vamos a usar una tabla de contingencia que relaciones el sexo, el estado del actor y me dé un promedio de las edades."]},{"cell_type":"code","metadata":{"id":"OhJbeWzGCOCZ","executionInfo":{"status":"ok","timestamp":1601042966177,"user_tz":300,"elapsed":186333,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"c384ce79-e233-4ee2-8d12-bb687ce760a4","colab":{"base_uri":"https://localhost:8080/","height":266}},"source":["promedio_edades_sexo = pd.crosstab(df_actores_limpio['ANIO_SINIESTRO'], [df_actores_limpio['SEXO'], df_actores_limpio['ESTADO']], aggfunc=np.mean, values=df_actores_limpio['EDAD'])\n","promedio_edades_sexo"],"execution_count":null,"outputs":[{"output_type":"execute_result","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 tr th {\n","        text-align: left;\n","    }\n","\n","    .dataframe thead tr:last-of-type th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr>\n","      <th>SEXO</th>\n","      <th colspan=\"3\" halign=\"left\">FEMENINO</th>\n","      <th colspan=\"3\" halign=\"left\">MASCULINO</th>\n","    </tr>\n","    <tr>\n","      <th>ESTADO</th>\n","      <th>HERIDO</th>\n","      <th>MUERTO</th>\n","      <th>SIN INFORMACION</th>\n","      <th>HERIDO</th>\n","      <th>MUERTO</th>\n","      <th>SIN INFORMACION</th>\n","    </tr>\n","    <tr>\n","      <th>ANIO_SINIESTRO</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>2015</th>\n","      <td>35.407590</td>\n","      <td>45.366337</td>\n","      <td>NaN</td>\n","      <td>32.850005</td>\n","      <td>42.028796</td>\n","      <td>45.000000</td>\n","    </tr>\n","    <tr>\n","      <th>2016</th>\n","      <td>36.101981</td>\n","      <td>44.405172</td>\n","      <td>38.0</td>\n","      <td>33.368029</td>\n","      <td>40.513002</td>\n","      <td>48.000000</td>\n","    </tr>\n","    <tr>\n","      <th>2017</th>\n","      <td>35.723298</td>\n","      <td>45.415094</td>\n","      <td>36.0</td>\n","      <td>32.941000</td>\n","      <td>42.246973</td>\n","      <td>38.222222</td>\n","    </tr>\n","    <tr>\n","      <th>2018</th>\n","      <td>36.056120</td>\n","      <td>48.244898</td>\n","      <td>NaN</td>\n","      <td>33.653060</td>\n","      <td>43.679688</td>\n","      <td>38.000000</td>\n","    </tr>\n","    <tr>\n","      <th>2019</th>\n","      <td>35.283645</td>\n","      <td>43.817391</td>\n","      <td>NaN</td>\n","      <td>32.376735</td>\n","      <td>40.173077</td>\n","      <td>NaN</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["SEXO             FEMENINO             ...  MASCULINO                \n","ESTADO             HERIDO     MUERTO  ...     MUERTO SIN INFORMACION\n","ANIO_SINIESTRO                        ...                           \n","2015            35.407590  45.366337  ...  42.028796       45.000000\n","2016            36.101981  44.405172  ...  40.513002       48.000000\n","2017            35.723298  45.415094  ...  42.246973       38.222222\n","2018            36.056120  48.244898  ...  43.679688       38.000000\n","2019            35.283645  43.817391  ...  40.173077             NaN\n","\n","[5 rows x 6 columns]"]},"metadata":{"tags":[]},"execution_count":91}]},{"cell_type":"markdown","metadata":{"id":"4hUvwLZPvnia"},"source":["Con los datos anteriores, nos damos cuenta que en promedio, los hombres que mueren en los accidentes de tránsito son aproximadamente 4 años mas jovenes que las mujeres, de igual manera los heridos, donde los hombres son aproximadamente 3 años más jovenes que ellas. "]},{"cell_type":"code","metadata":{"id":"Sq2eDztx7XF9","executionInfo":{"status":"ok","timestamp":1601042966179,"user_tz":300,"elapsed":186313,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"727200cd-e9f4-4816-d082-0e454bbf23f4","colab":{"base_uri":"https://localhost:8080/","height":34}},"source":["def get_intervalo_confianza_edad(sexo, estado, alpha=0.05):\n","  datos_a_evaluar = df_actores_limpio[(df_actores_limpio['SEXO'] == sexo) & (df_actores_limpio['ESTADO'] == estado)]\n","  limite_superior, limite_inferior = sm.stats.DescrStatsW(datos_a_evaluar.EDAD).zconfint_mean(alpha = 0.05)\n","  return (limite_superior, limite_inferior)\n","\n","print(get_intervalo_confianza_edad('MASCULINO', 'MUERTO'))\n","#limite_superior, limite_inferior = sm.stats.DescrStatsW([mujeres_muertas_edades.EDAD]).zconfint_mean(mujeres_muertas_edades.EDAD)"],"execution_count":null,"outputs":[{"output_type":"stream","text":["(40.78194912826623, 42.67278128882432)\n"],"name":"stdout"}]},{"cell_type":"markdown","metadata":{"id":"0U83Yy9B1F0i"},"source":["Ahora queremos saber en donde se concentran las edades de los actores segun su estado. Para ello graficamos el diagrama de violín que vemos en la celda siguiente, recordemos que la barra negra de la mitad nos dice el intervalo de confianza del 95%. Con el grafico nos podemos dar cuenta que aproximadamente los hombres entre los 20 y los 40 años, tienen mayor riesgo de salir heridos en los accidentes, mientras que las mujeres van desde los 20 años hasta los 50 años aproximadamente.\n","\n","En cuanto a fallecimientos, los hombres qie tienen entre 22 y 58 años tienen mas riesgo de morir en accidentes, para las mujeres este rango de edad va desde los 22 hasta los 65 años aproximadamente."]},{"cell_type":"code","metadata":{"id":"w2hBslr9ENA9","executionInfo":{"status":"ok","timestamp":1601042967197,"user_tz":300,"elapsed":187318,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"972feeac-cd01-4a01-a922-1564b8f8efb6","colab":{"base_uri":"https://localhost:8080/","height":337}},"source":["fig, ax = plt.subplots(figsize=(10, 5))\n","distribucion_por_estado = sns.violinplot(ax = ax, data=df_actores_limpio, x='ESTADO', y='EDAD', hue='SEXO');"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 720x360 with 1 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"983ZjlpoCmxr","executionInfo":{"status":"ok","timestamp":1601042967199,"user_tz":300,"elapsed":187310,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"cdbdd87b-d9b7-4bb0-ef31-c1241d04fe18","colab":{"base_uri":"https://localhost:8080/","height":235}},"source":["accidentes_por_anio = df_siniestros_limpio.groupby('ANIO_SINIESTRO')[['CODIGO_SINIESTRO', 'TOTAL_MUERTOS', 'TOTAL_HERIDOS']].agg(\n","    {'CODIGO_SINIESTRO': pd.Series.count, 'TOTAL_MUERTOS': np.sum, 'TOTAL_HERIDOS': np.sum}\n",").rename(columns={'CODIGO_SINIESTRO': 'CANTIDAD_SINIESTRO'})\n","accidentes_por_anio"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>CANTIDAD_SINIESTRO</th>\n","      <th>TOTAL_MUERTOS</th>\n","      <th>TOTAL_HERIDOS</th>\n","    </tr>\n","    <tr>\n","      <th>ANIO_SINIESTRO</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>2015</th>\n","      <td>11256</td>\n","      <td>540</td>\n","      <td>14801</td>\n","    </tr>\n","    <tr>\n","      <th>2016</th>\n","      <td>11127</td>\n","      <td>590</td>\n","      <td>14521</td>\n","    </tr>\n","    <tr>\n","      <th>2017</th>\n","      <td>10923</td>\n","      <td>542</td>\n","      <td>15022</td>\n","    </tr>\n","    <tr>\n","      <th>2018</th>\n","      <td>13067</td>\n","      <td>516</td>\n","      <td>18902</td>\n","    </tr>\n","    <tr>\n","      <th>2019</th>\n","      <td>12865</td>\n","      <td>507</td>\n","      <td>18469</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["                CANTIDAD_SINIESTRO  TOTAL_MUERTOS  TOTAL_HERIDOS\n","ANIO_SINIESTRO                                                  \n","2015                         11256            540          14801\n","2016                         11127            590          14521\n","2017                         10923            542          15022\n","2018                         13067            516          18902\n","2019                         12865            507          18469"]},"metadata":{"tags":[]},"execution_count":94}]},{"cell_type":"markdown","metadata":{"id":"uw_p8NbIDVG6"},"source":["### Lugares mas peligrosos y Localidades con mas accidentes"]},{"cell_type":"markdown","metadata":{"id":"Tp2ewoLUGBIR"},"source":["Siguiendo con el cumplimiento de objetivos, ahora vamos a fijarnos en los tipos de lugar donde ocurrieron los siniestros, obteniendo los tipos de lugares más peligrosos, para ello vamos a realizar una tabla de contingenia donde obtenemos la proporción de peligrosidad de los sitios de acuerdo al números de heridos y muertos."]},{"cell_type":"code","metadata":{"id":"ulz5olu51yun","executionInfo":{"status":"ok","timestamp":1601042967200,"user_tz":300,"elapsed":187300,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"0a9431a9-499e-4a8c-ee35-b1a4a2a2b1bf","colab":{"base_uri":"https://localhost:8080/","height":272}},"source":["# Seleccionamos los datos donde hubo muertos\n","actores_muertos = df_siniestros_limpio[df_siniestros_limpio['TOTAL_MUERTOS'] > 0]\n","muertos_diseno_lugar = pd.crosstab(actores_muertos['TOTAL_MUERTOS'], actores_muertos['DISENO_LUGAR'], margins=True, normalize=True)\n","muertos_diseno_lugar"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>DISENO_LUGAR</th>\n","      <th>Cicloruta</th>\n","      <th>Glorieta</th>\n","      <th>Interseccion</th>\n","      <th>Lote o predio</th>\n","      <th>Paso a nivel</th>\n","      <th>Paso elevado</th>\n","      <th>Paso inferior</th>\n","      <th>Puente</th>\n","      <th>Tramo de Via</th>\n","      <th>Via peatonal</th>\n","      <th>All</th>\n","    </tr>\n","    <tr>\n","      <th>TOTAL_MUERTOS</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>1</th>\n","      <td>0.000763</td>\n","      <td>0.003053</td>\n","      <td>0.13626</td>\n","      <td>0.008779</td>\n","      <td>0.001145</td>\n","      <td>0.008397</td>\n","      <td>0.003053</td>\n","      <td>0.001145</td>\n","      <td>0.811069</td>\n","      <td>0.000382</td>\n","      <td>0.974046</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.00458</td>\n","      <td>0.000382</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.019084</td>\n","      <td>0.000000</td>\n","      <td>0.024046</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.00000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.001145</td>\n","      <td>0.000000</td>\n","      <td>0.001145</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.00000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000763</td>\n","      <td>0.000000</td>\n","      <td>0.000763</td>\n","    </tr>\n","    <tr>\n","      <th>All</th>\n","      <td>0.000763</td>\n","      <td>0.003053</td>\n","      <td>0.14084</td>\n","      <td>0.009160</td>\n","      <td>0.001145</td>\n","      <td>0.008397</td>\n","      <td>0.003053</td>\n","      <td>0.001145</td>\n","      <td>0.832061</td>\n","      <td>0.000382</td>\n","      <td>1.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["DISENO_LUGAR   Cicloruta  Glorieta  ...  Via peatonal       All\n","TOTAL_MUERTOS                       ...                        \n","1               0.000763  0.003053  ...      0.000382  0.974046\n","2               0.000000  0.000000  ...      0.000000  0.024046\n","3               0.000000  0.000000  ...      0.000000  0.001145\n","4               0.000000  0.000000  ...      0.000000  0.000763\n","All             0.000763  0.003053  ...      0.000382  1.000000\n","\n","[5 rows x 11 columns]"]},"metadata":{"tags":[]},"execution_count":95}]},{"cell_type":"code","metadata":{"id":"cAudVSgY8VZg","executionInfo":{"status":"ok","timestamp":1601042967504,"user_tz":300,"elapsed":187594,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"c43c589e-4181-46d7-9312-b48bd5172513","colab":{"base_uri":"https://localhost:8080/","height":342}},"source":["fig, ax = plt.subplots(figsize=(14, 4))\n","mask = muertos_diseno_lugar == 0\n","sns.heatmap(muertos_diseno_lugar, fmt='.2%',ax=ax, mask=mask, annot=True, linewidths=2);\n","ax.set_ylabel('TOTAL DE MUERTOS')\n","ax.set_xlabel('DISEÑO DEL LUGAR DEL ACCIDENTE');"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1008x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"noWQ98Eu767O","executionInfo":{"status":"ok","timestamp":1601042967778,"user_tz":300,"elapsed":187858,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"ff612117-a72c-46a8-b082-36690148731a","colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["actores_heridos = df_siniestros_limpio[df_siniestros_limpio['TOTAL_HERIDOS'] > 0]\n","heridos_diseno_lugar = pd.crosstab(actores_heridos['TOTAL_HERIDOS'], actores_heridos['DISENO_LUGAR'], margins=True)\n","heridos_diseno_lugar"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>DISENO_LUGAR</th>\n","      <th>Cicloruta</th>\n","      <th>Glorieta</th>\n","      <th>Interseccion</th>\n","      <th>Lote o predio</th>\n","      <th>Paso a nivel</th>\n","      <th>Paso elevado</th>\n","      <th>Paso inferior</th>\n","      <th>Ponton</th>\n","      <th>Puente</th>\n","      <th>Tramo de Via</th>\n","      <th>Tunel</th>\n","      <th>Via peatonal</th>\n","      <th>All</th>\n","    </tr>\n","    <tr>\n","      <th>TOTAL_HERIDOS</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>1</th>\n","      <td>95</td>\n","      <td>242</td>\n","      <td>8930</td>\n","      <td>202</td>\n","      <td>27</td>\n","      <td>162</td>\n","      <td>100</td>\n","      <td>3</td>\n","      <td>57</td>\n","      <td>31402</td>\n","      <td>16</td>\n","      <td>24</td>\n","      <td>41260</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>24</td>\n","      <td>44</td>\n","      <td>3140</td>\n","      <td>25</td>\n","      <td>4</td>\n","      <td>51</td>\n","      <td>27</td>\n","      <td>0</td>\n","      <td>21</td>\n","      <td>8714</td>\n","      <td>2</td>\n","      <td>5</td>\n","      <td>12057</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>3</td>\n","      <td>8</td>\n","      <td>683</td>\n","      <td>6</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>3</td>\n","      <td>0</td>\n","      <td>4</td>\n","      <td>1892</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>2606</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>1</td>\n","      <td>4</td>\n","      <td>202</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>2</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>444</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>657</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>75</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>3</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>177</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>258</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>35</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>105</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>140</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>22</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>57</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>80</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>18</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>42</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>61</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>12</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>2</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>22</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>36</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>4</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>21</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>25</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>21</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>25</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>6</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>8</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>15</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>13</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>14</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>3</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>4</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>8</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>5</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>6</td>\n","    </tr>\n","    <tr>\n","      <th>16</th>\n","      <td>0</td>\n","      <td>0</td>\n","      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<td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>All</th>\n","      <td>123</td>\n","      <td>300</td>\n","      <td>13144</td>\n","      <td>234</td>\n","      <td>35</td>\n","      <td>227</td>\n","      <td>134</td>\n","      <td>3</td>\n","      <td>84</td>\n","      <td>42962</td>\n","      <td>18</td>\n","      <td>30</td>\n","      <td>57294</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["DISENO_LUGAR   Cicloruta  Glorieta  Interseccion  ...  Tunel  Via peatonal    All\n","TOTAL_HERIDOS                                     ...                            \n","1                     95       242          8930  ...     16            24  41260\n","2                     24        44          3140  ...      2             5  12057\n","3                      3         8           683  ...      0             1   2606\n","4                      1         4           202  ...      0             0    657\n","5                      0         1            75  ...      0             0    258\n","6                      0         0            35  ...      0             0    140\n","7                      0         1            22  ...      0             0     80\n","8                      0         0            18  ...      0             0     61\n","9                      0         0            12  ...      0             0     36\n","10                     0         0             4  ...      0             0     25\n","11                     0         0             3  ...      0             0     25\n","12                     0         0             6  ...      0             0     15\n","13                     0         0             0  ...      0             0     14\n","14                     0         0             3  ...      0             0      8\n","15                     0         0             0  ...      0             0      6\n","16                     0         0             2  ...      0             0      2\n","17                     0         0             2  ...      0             0      4\n","18                     0         0             0  ...      0             0      4\n","19                     0         0             2  ...      0             0      3\n","20                     0         0             1  ...      0             0      1\n","21                     0         0             1  ...      0             0      2\n","22                     0         0             0  ...      0             0      2\n","23                     0         0             0  ...      0             0      2\n","24                     0         0             0  ...      0             0      1\n","25                     0         0             1  ...      0             0      5\n","26                     0         0             0  ...      0             0      1\n","28                     0         0             0  ...      0             0      4\n","29                     0         0             0  ...      0             0      1\n","30                     0         0             1  ...      0             0      6\n","34                     0         0             0  ...      0             0      1\n","42                     0         0             0  ...      0             0      1\n","44                     0         0             1  ...      0             0      1\n","51                     0         0             0  ...      0             0      1\n","59                     0         0             0  ...      0             0      1\n","60                     0         0             0  ...      0             0      1\n","65                     0         0             0  ...      0             0      1\n","72                     0         0             0  ...      0             0      1\n","All                  123       300         13144  ...     18            30  57294\n","\n","[38 rows x 13 columns]"]},"metadata":{"tags":[]},"execution_count":97}]},{"cell_type":"code","metadata":{"id":"rsqibET1A7v7","executionInfo":{"status":"ok","timestamp":1601042969125,"user_tz":300,"elapsed":189195,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"973a7654-5553-40ad-897a-0fb053421ff4","colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["fig, ax = plt.subplots(figsize=(14, 17))\n","mask = heridos_diseno_lugar == 0\n","sns.heatmap(heridos_diseno_lugar, fmt='d',ax=ax, mask=mask, annot=True, linewidths=2);\n","ax.set_ylabel('TOTAL DE HERIDOS')\n","ax.set_xlabel('DISEÑO DEL LUGAR DEL ACCIDENTE');"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1008x1224 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"v1wwPXooIDPN"},"source":["De acuerdo a los datos anteriormente calculados e interpretando las gráficas de calor, podemos concluir que los lugares más peligrosos teniendo en cuenta la cantidad de accidentes que en estos sitios ocurren son los Tramos de Vía, en donde un 83.21% de las personas mueren y un total de 42962 personas resultaron heridas a lo largo de los 5 años. En el siguiente lugar encontramos a las intersecciones, en donde el 14.1% de personas mueren y 13144 resultaron heridas."]},{"cell_type":"code","metadata":{"id":"-C9ZHI5yKhCe","executionInfo":{"status":"ok","timestamp":1601042969128,"user_tz":300,"elapsed":189187,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"4690e708-27a5-4ddb-e605-33d804040436","colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["heridos_por_localidad = pd.crosstab(actores_heridos['TOTAL_HERIDOS'], actores_heridos['LOCALIDAD'], margins=True)\n","heridos_por_localidad"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>LOCALIDAD</th>\n","      <th>Antonio Nariño</th>\n","      <th>Barrios Unidos</th>\n","      <th>Bosa</th>\n","      <th>Chapinero</th>\n","      <th>Ciudad Bolívar</th>\n","      <th>Engativá</th>\n","      <th>Fontibón</th>\n","      <th>Kennedy</th>\n","      <th>La Candelaria</th>\n","      <th>Los Mártires</th>\n","      <th>Puente Aranda</th>\n","      <th>Rafael Uribe Uribe</th>\n","      <th>San Cristóbal</th>\n","      <th>Santa Fe</th>\n","      <th>Suba</th>\n","      <th>Sumapaz</th>\n","      <th>Teusaquillo</th>\n","      <th>Tunjuelito</th>\n","      <th>Usaquén</th>\n","      <th>Usme</th>\n","      <th>All</th>\n","    </tr>\n","    <tr>\n","      <th>TOTAL_HERIDOS</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      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     <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>60</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>65</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>72</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>All</th>\n","      <td>1480</td>\n","      <td>2446</td>\n","      <td>3700</td>\n","      <td>2303</td>\n","      <td>3131</td>\n","      <td>5405</td>\n","      <td>3327</td>\n","      <td>7811</td>\n","      <td>288</td>\n","      <td>2072</td>\n","      <td>4095</td>\n","      <td>2187</td>\n","      <td>2373</td>\n","      <td>1888</td>\n","      <td>4979</td>\n","      <td>2</td>\n","      <td>2518</td>\n","      <td>2079</td>\n","      <td>3611</td>\n","      <td>1599</td>\n","      <td>57294</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["LOCALIDAD      Antonio Nariño  Barrios Unidos  Bosa  ...  Usaquén  Usme    All\n","TOTAL_HERIDOS                                        ...                      \n","1                        1044            1755  2581  ...     2716  1151  41260\n","2                         317             513   825  ...      652   322  12057\n","3                          80             115   212  ...      146    74   2606\n","4                          14              31    47  ...       52    31    657\n","5                           9              15    13  ...       21     4    258\n","6                           8               5     8  ...        6     6    140\n","7                           2               2     3  ...        5     1     80\n","8                           0               3     5  ...        5     4     61\n","9                           0               2     2  ...        0     0     36\n","10                          1               0     1  ...        2     2     25\n","11                          2               1     0  ...        0     1     25\n","12                          0               0     1  ...        3     0     15\n","13                          0               3     1  ...        1     1     14\n","14                          0               0     0  ...        0     1      8\n","15                          0               0     1  ...        0     0      6\n","16                          0               0     0  ...        0     0      2\n","17                          0               0     0  ...        1     0      4\n","18                          1               0     0  ...        0     1      4\n","19                          1               0     0  ...        0     0      3\n","20                          0               0     0  ...        0     0      1\n","21                          0               1     0  ...        0     0      2\n","22                          0               0     0  ...        0     0      2\n","23                          0               0     0  ...        0     0      2\n","24                          0               0     0  ...        0     0      1\n","25                          0               0     0  ...        0     0      5\n","26                          0               0     0  ...        0     0      1\n","28                          0               0     0  ...        0     0      4\n","29                          0               0     0  ...        1     0      1\n","30                          1               0     0  ...        0     0      6\n","34                          0               0     0  ...        0     0      1\n","42                          0               0     0  ...        0     0      1\n","44                          0               0     0  ...        0     0      1\n","51                          0               0     0  ...        0     0      1\n","59                          0               0     0  ...        0     0      1\n","60                          0               0     0  ...        0     0      1\n","65                          0               0     0  ...        0     0      1\n","72                          0               0     0  ...        0     0      1\n","All                      1480            2446  3700  ...     3611  1599  57294\n","\n","[38 rows x 21 columns]"]},"metadata":{"tags":[]},"execution_count":99}]},{"cell_type":"code","metadata":{"id":"lt4q24mVOBO6","executionInfo":{"status":"ok","timestamp":1601042971150,"user_tz":300,"elapsed":191198,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"b136f46e-799c-417a-945e-d099f55d7f87","colab":{"base_uri":"https://localhost:8080/","height":1000}},"source":["fig, ax = plt.subplots(figsize=(15, 16))\n","mask = heridos_por_localidad == 0\n","sns.heatmap(heridos_por_localidad, fmt='d',ax=ax, mask=mask, annot=True, linewidths=2, vmax=8000)\n","ax.set_ylabel('TOTAL DE HERIDOS')\n","ax.set_xlabel('LOCALIDAD');"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1080x1152 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"code","metadata":{"id":"HEzJBxJ2ZaZ_","executionInfo":{"status":"ok","timestamp":1601042971157,"user_tz":300,"elapsed":191195,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"2b971461-7433-423b-fd76-4d25a3e4b335","colab":{"base_uri":"https://localhost:8080/","height":289}},"source":["muertos_por_localidad = pd.crosstab(actores_muertos['TOTAL_MUERTOS'], actores_muertos['LOCALIDAD'], margins=True, normalize=True)\n","muertos_por_localidad"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>LOCALIDAD</th>\n","      <th>Antonio Nariño</th>\n","      <th>Barrios Unidos</th>\n","      <th>Bosa</th>\n","      <th>Chapinero</th>\n","      <th>Ciudad Bolívar</th>\n","      <th>Engativá</th>\n","      <th>Fontibón</th>\n","      <th>Kennedy</th>\n","      <th>La Candelaria</th>\n","      <th>Los Mártires</th>\n","      <th>Puente Aranda</th>\n","      <th>Rafael Uribe Uribe</th>\n","      <th>San Cristóbal</th>\n","      <th>Santa Fe</th>\n","      <th>Suba</th>\n","      <th>Sumapaz</th>\n","      <th>Teusaquillo</th>\n","      <th>Tunjuelito</th>\n","      <th>Usaquén</th>\n","      <th>Usme</th>\n","      <th>All</th>\n","    </tr>\n","    <tr>\n","      <th>TOTAL_MUERTOS</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","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>1</th>\n","      <td>0.027863</td>\n","      <td>0.033588</td>\n","      <td>0.062977</td>\n","      <td>0.028244</td>\n","      <td>0.070229</td>\n","      <td>0.08855</td>\n","      <td>0.068702</td>\n","      <td>0.137405</td>\n","      <td>0.004198</td>\n","      <td>0.032824</td>\n","      <td>0.070229</td>\n","      <td>0.039695</td>\n","      <td>0.040458</td>\n","      <td>0.027099</td>\n","      <td>0.078244</td>\n","      <td>0.000763</td>\n","      <td>0.032443</td>\n","      <td>0.040076</td>\n","      <td>0.051145</td>\n","      <td>0.039313</td>\n","      <td>0.974046</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>0.000382</td>\n","      <td>0.001908</td>\n","      <td>0.001145</td>\n","      <td>0.000382</td>\n","      <td>0.001908</td>\n","      <td>0.00229</td>\n","      <td>0.001908</td>\n","      <td>0.001527</td>\n","      <td>0.000000</td>\n","      <td>0.000382</td>\n","      <td>0.001908</td>\n","      <td>0.001908</td>\n","      <td>0.000763</td>\n","      <td>0.000763</td>\n","      <td>0.001527</td>\n","      <td>0.000000</td>\n","      <td>0.001908</td>\n","      <td>0.001145</td>\n","      <td>0.000382</td>\n","      <td>0.001908</td>\n","      <td>0.024046</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.00000</td>\n","      <td>0.000000</td>\n","      <td>0.000382</td>\n","      <td>0.000000</td>\n","      <td>0.000382</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000382</td>\n","      <td>0.000000</td>\n","      <td>0.001145</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.00000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000382</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000382</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.000763</td>\n","    </tr>\n","    <tr>\n","      <th>All</th>\n","      <td>0.028244</td>\n","      <td>0.035496</td>\n","      <td>0.064122</td>\n","      <td>0.028626</td>\n","      <td>0.072137</td>\n","      <td>0.09084</td>\n","      <td>0.070611</td>\n","      <td>0.139313</td>\n","      <td>0.004198</td>\n","      <td>0.033588</td>\n","      <td>0.072519</td>\n","      <td>0.041603</td>\n","      <td>0.041221</td>\n","      <td>0.028244</td>\n","      <td>0.079771</td>\n","      <td>0.000763</td>\n","      <td>0.034351</td>\n","      <td>0.041221</td>\n","      <td>0.051908</td>\n","      <td>0.041221</td>\n","      <td>1.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["LOCALIDAD      Antonio Nariño  Barrios Unidos  ...      Usme       All\n","TOTAL_MUERTOS                                  ...                    \n","1                    0.027863        0.033588  ...  0.039313  0.974046\n","2                    0.000382        0.001908  ...  0.001908  0.024046\n","3                    0.000000        0.000000  ...  0.000000  0.001145\n","4                    0.000000        0.000000  ...  0.000000  0.000763\n","All                  0.028244        0.035496  ...  0.041221  1.000000\n","\n","[5 rows x 21 columns]"]},"metadata":{"tags":[]},"execution_count":101}]},{"cell_type":"code","metadata":{"id":"mSbP0vmVZm7Q","executionInfo":{"status":"ok","timestamp":1601042971911,"user_tz":300,"elapsed":191939,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"ba9168a1-a9b2-42cd-d98d-970acdc40153","colab":{"base_uri":"https://localhost:8080/","height":368}},"source":["fig, ax = plt.subplots(figsize=(16, 4))\n","mask = muertos_por_localidad == 0\n","sns.heatmap(muertos_por_localidad, fmt='.1%',ax=ax, mask=mask, annot=True, linewidths=2, vmax=0.2)\n","ax.set_ylabel('TOTAL DE MUERTOS')\n","ax.set_xlabel('LOCALIDAD');"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1152x288 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"lgGpRWcUZGUL"},"source":["Según los datos calculados e interpretando la gráfica, nos podemos dar cuenta que la localida de Bogotá más peligrosa es Kennedy, en donde se concentra el 13.9% del total de muertos y un total de 7811 heridos a lo largo de los 5 años, seguida por Engativá con con 9.1% y 5045 heridos y por último Subá con el 8% de muertes y 4979 en número de heridos.\n","\n","Algo que se debe notar y que no debe pasar por alto, es la localidad de Ciudad Bolivar, donde se presentaron los accidentes con la mayor cantidad de heridos. Un accidente de tránsito dejó 72 heridos y otro más 65."]},{"cell_type":"markdown","metadata":{"id":"jtfyuC6BhMgJ"},"source":["### **Vehículos más peligrosos y naturaleza de los mismos**"]},{"cell_type":"markdown","metadata":{"id":"-gT5y3ZLsOWU"},"source":["### **Dataframe `df_vehiculos`**\n","\n","Por último, vamos a realizar un estudio teniendo en cuenta los vehiculos implicados en accidentes. Primero usamos una tabla de contenigencia para realizar un conteo por clase de vehiculo y el servicio para el cual el vehículo es usado. "]},{"cell_type":"code","metadata":{"id":"AYAsNikdsroQ","executionInfo":{"status":"ok","timestamp":1601048420433,"user_tz":300,"elapsed":651,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"535bc473-0403-45ad-aabd-20d101cee53a","colab":{"base_uri":"https://localhost:8080/","height":545}},"source":["pd.crosstab(df_vehiculos['CLASE'], df_vehiculos['SERVICIO'], margins=True)"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>SERVICIO</th>\n","      <th>Diplomatico</th>\n","      <th>Oficial</th>\n","      <th>Particular</th>\n","      <th>Publico</th>\n","      <th>All</th>\n","    </tr>\n","    <tr>\n","      <th>CLASE</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>Automovil</th>\n","      <td>35</td>\n","      <td>3170</td>\n","      <td>93827</td>\n","      <td>39688</td>\n","      <td>136720</td>\n","    </tr>\n","    <tr>\n","      <th>Bicicleta</th>\n","      <td>0</td>\n","      <td>4</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>5</td>\n","    </tr>\n","    <tr>\n","      <th>Bus</th>\n","      <td>1</td>\n","      <td>112</td>\n","      <td>412</td>\n","      <td>33681</td>\n","      <td>34206</td>\n","    </tr>\n","    <tr>\n","      <th>Buseta</th>\n","      <td>1</td>\n","      <td>57</td>\n","      <td>100</td>\n","      <td>4869</td>\n","      <td>5027</td>\n","    </tr>\n","    <tr>\n","      <th>Camion, Furgon</th>\n","      <td>0</td>\n","      <td>551</td>\n","      <td>2280</td>\n","      <td>15117</td>\n","      <td>17948</td>\n","    </tr>\n","    <tr>\n","      <th>Camioneta</th>\n","      <td>31</td>\n","      <td>1912</td>\n","      <td>25061</td>\n","      <td>18246</td>\n","      <td>45250</td>\n","    </tr>\n","    <tr>\n","      <th>Campero</th>\n","      <td>13</td>\n","      <td>1137</td>\n","      <td>12257</td>\n","      <td>942</td>\n","      <td>14349</td>\n","    </tr>\n","    <tr>\n","      <th>Cuatrimoto</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>2</td>\n","      <td>3</td>\n","    </tr>\n","    <tr>\n","      <th>Microbus</th>\n","      <td>0</td>\n","      <td>93</td>\n","      <td>346</td>\n","      <td>9107</td>\n","      <td>9546</td>\n","    </tr>\n","    <tr>\n","      <th>Motocarro</th>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>70</td>\n","      <td>5</td>\n","      <td>76</td>\n","    </tr>\n","    <tr>\n","      <th>Motocicleta</th>\n","      <td>0</td>\n","      <td>1291</td>\n","      <td>43754</td>\n","      <td>19</td>\n","      <td>45064</td>\n","    </tr>\n","    <tr>\n","      <th>Motociclo</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>5</td>\n","      <td>0</td>\n","      <td>5</td>\n","    </tr>\n","    <tr>\n","      <th>Tractocamion</th>\n","      <td>0</td>\n","      <td>15</td>\n","      <td>131</td>\n","      <td>4424</td>\n","      <td>4570</td>\n","    </tr>\n","    <tr>\n","      <th>Volqueta</th>\n","      <td>0</td>\n","      <td>99</td>\n","      <td>389</td>\n","      <td>2771</td>\n","      <td>3259</td>\n","    </tr>\n","    <tr>\n","      <th>All</th>\n","      <td>81</td>\n","      <td>8442</td>\n","      <td>178634</td>\n","      <td>128871</td>\n","      <td>316028</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["SERVICIO        Diplomatico  Oficial  Particular  Publico     All\n","CLASE                                                            \n","Automovil                35     3170       93827    39688  136720\n","Bicicleta                 0        4           1        0       5\n","Bus                       1      112         412    33681   34206\n","Buseta                    1       57         100     4869    5027\n","Camion, Furgon            0      551        2280    15117   17948\n","Camioneta                31     1912       25061    18246   45250\n","Campero                  13     1137       12257      942   14349\n","Cuatrimoto                0        0           1        2       3\n","Microbus                  0       93         346     9107    9546\n","Motocarro                 0        1          70        5      76\n","Motocicleta               0     1291       43754       19   45064\n","Motociclo                 0        0           5        0       5\n","Tractocamion              0       15         131     4424    4570\n","Volqueta                  0       99         389     2771    3259\n","All                      81     8442      178634   128871  316028"]},"metadata":{"tags":[]},"execution_count":144}]},{"cell_type":"markdown","metadata":{"id":"1gj1B5b0s4i9"},"source":["Los datos anteriores nos permite concluir que los automoviles, las camionetas y las motocicletas son los 3 vehiculos donde más se presentan accidentes, es decir, la mayoría de las veces en las que sucede un accidente de tránsito, están implicados estas tres clases de vehiculos. Tambien, los medios de transporte de caracter Público son los mas accidentados, exceptuando algunos vehiculos poco comunes como las Cuatrimotos, Motocarros y Motocilo."]},{"cell_type":"code","metadata":{"id":"-lK9hf8go0gC","executionInfo":{"status":"ok","timestamp":1601044220353,"user_tz":300,"elapsed":659,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"b87d90c9-3ebf-4db8-ec94-cbbbe7ecd92c","colab":{"base_uri":"https://localhost:8080/","height":545}},"source":["porcentaje_por_vehiculos = pd.crosstab(df_vehiculos['CLASE'], df_vehiculos['SERVICIO'], margins=True, normalize='index')\n","porcentaje_por_vehiculos"],"execution_count":null,"outputs":[{"output_type":"execute_result","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>SERVICIO</th>\n","      <th>Diplomatico</th>\n","      <th>Oficial</th>\n","      <th>Particular</th>\n","      <th>Publico</th>\n","    </tr>\n","    <tr>\n","      <th>CLASE</th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","      <th></th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Automovil</th>\n","      <td>0.000256</td>\n","      <td>0.023186</td>\n","      <td>0.686271</td>\n","      <td>0.290287</td>\n","    </tr>\n","    <tr>\n","      <th>Bicicleta</th>\n","      <td>0.000000</td>\n","      <td>0.800000</td>\n","      <td>0.200000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>Bus</th>\n","      <td>0.000029</td>\n","      <td>0.003274</td>\n","      <td>0.012045</td>\n","      <td>0.984652</td>\n","    </tr>\n","    <tr>\n","      <th>Buseta</th>\n","      <td>0.000199</td>\n","      <td>0.011339</td>\n","      <td>0.019893</td>\n","      <td>0.968570</td>\n","    </tr>\n","    <tr>\n","      <th>Camion, Furgon</th>\n","      <td>0.000000</td>\n","      <td>0.030700</td>\n","      <td>0.127034</td>\n","      <td>0.842267</td>\n","    </tr>\n","    <tr>\n","      <th>Camioneta</th>\n","      <td>0.000685</td>\n","      <td>0.042254</td>\n","      <td>0.553834</td>\n","      <td>0.403227</td>\n","    </tr>\n","    <tr>\n","      <th>Campero</th>\n","      <td>0.000906</td>\n","      <td>0.079239</td>\n","      <td>0.854206</td>\n","      <td>0.065649</td>\n","    </tr>\n","    <tr>\n","      <th>Cuatrimoto</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>0.333333</td>\n","      <td>0.666667</td>\n","    </tr>\n","    <tr>\n","      <th>Microbus</th>\n","      <td>0.000000</td>\n","      <td>0.009742</td>\n","      <td>0.036246</td>\n","      <td>0.954012</td>\n","    </tr>\n","    <tr>\n","      <th>Motocarro</th>\n","      <td>0.000000</td>\n","      <td>0.013158</td>\n","      <td>0.921053</td>\n","      <td>0.065789</td>\n","    </tr>\n","    <tr>\n","      <th>Motocicleta</th>\n","      <td>0.000000</td>\n","      <td>0.028648</td>\n","      <td>0.970930</td>\n","      <td>0.000422</td>\n","    </tr>\n","    <tr>\n","      <th>Motociclo</th>\n","      <td>0.000000</td>\n","      <td>0.000000</td>\n","      <td>1.000000</td>\n","      <td>0.000000</td>\n","    </tr>\n","    <tr>\n","      <th>Tractocamion</th>\n","      <td>0.000000</td>\n","      <td>0.003282</td>\n","      <td>0.028665</td>\n","      <td>0.968053</td>\n","    </tr>\n","    <tr>\n","      <th>Volqueta</th>\n","      <td>0.000000</td>\n","      <td>0.030377</td>\n","      <td>0.119362</td>\n","      <td>0.850261</td>\n","    </tr>\n","    <tr>\n","      <th>All</th>\n","      <td>0.000256</td>\n","      <td>0.026713</td>\n","      <td>0.565247</td>\n","      <td>0.407783</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["SERVICIO        Diplomatico   Oficial  Particular   Publico\n","CLASE                                                      \n","Automovil          0.000256  0.023186    0.686271  0.290287\n","Bicicleta          0.000000  0.800000    0.200000  0.000000\n","Bus                0.000029  0.003274    0.012045  0.984652\n","Buseta             0.000199  0.011339    0.019893  0.968570\n","Camion, Furgon     0.000000  0.030700    0.127034  0.842267\n","Camioneta          0.000685  0.042254    0.553834  0.403227\n","Campero            0.000906  0.079239    0.854206  0.065649\n","Cuatrimoto         0.000000  0.000000    0.333333  0.666667\n","Microbus           0.000000  0.009742    0.036246  0.954012\n","Motocarro          0.000000  0.013158    0.921053  0.065789\n","Motocicleta        0.000000  0.028648    0.970930  0.000422\n","Motociclo          0.000000  0.000000    1.000000  0.000000\n","Tractocamion       0.000000  0.003282    0.028665  0.968053\n","Volqueta           0.000000  0.030377    0.119362  0.850261\n","All                0.000256  0.026713    0.565247  0.407783"]},"metadata":{"tags":[]},"execution_count":115}]},{"cell_type":"code","metadata":{"id":"Z1i433i3qwUB","executionInfo":{"status":"ok","timestamp":1601044789162,"user_tz":300,"elapsed":1191,"user":{"displayName":"Carlos Andrés Moreno","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Ggj1aCpYdvDDIF19ZKEM3OvcR7Eq4KOvJcE6UsR=s64","userId":"05711904004999807600"}},"outputId":"f6bbe97d-4d02-4dbe-831f-9ca2f8675643","colab":{"base_uri":"https://localhost:8080/","height":504}},"source":["fig, ax = plt.subplots(figsize=(8, 8))\n","mask = porcentaje_por_vehiculos == 0\n","sns.heatmap(porcentaje_por_vehiculos, linewidths=5, fmt='.2%', annot=True, mask=mask, ax=ax);"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 576x576 with 2 Axes>"]},"metadata":{"tags":[]}}]},{"cell_type":"markdown","metadata":{"id":"BhkRmrySA1A1"},"source":["# **FASE 4: Evaluación de resultados y cumplimiento de objetivos**\n","\n","Luego de realizar los análisis de datos vistos anteriormente, tenemos herramientas suficientes para la toma de desiciones por parte del ministerior de transporte. Hay que enfocarse en programas de concientización que vayan dirigidos a Hombres en su mayoria, con un promedio de edad de 36 años, puesto que son estas personas las que se han visto implicadas a lo largo de los años en accidentes de tránsito. \n","\n","Es importante también revisar las interescciones viales y los tramos de vía de la ciudad, en especial las localidades de Kennedy, Suba y Engativa. Ya que en estos tipos de lugares y localidades, se concetra alta peligrosidad en cuanto a numero de accidentes.\n","\n","Aparte, tambien se descubrio que los autos, motocicletas y camionetas son las que mas se ven involucradas en accidentes de tránsito. Un target interesante para realizar campañas de concientización serían aquellos hombres con un promedio de edad de 36 años, cuyo vehiculo sea auto, moto o camioneta. Ya que es en ese foco, donde se puede atacar el problema de raiz con el objetivo de minimizar el número de accidentes."]}]}