diff --git a/Ejemplo_nacimientos_2005_2010/Demo_CDS_nacimientos.ipynb b/Ejemplo_nacimientos_2005_2010/Demo_CDS_nacimientos.ipynb
index 0c55c795f575af3af6aaf128301a789a7bc8509e..e2478c58a0d9389d3d75a42b39c0eea69e2a96e2 100644
--- a/Ejemplo_nacimientos_2005_2010/Demo_CDS_nacimientos.ipynb
+++ b/Ejemplo_nacimientos_2005_2010/Demo_CDS_nacimientos.ipynb
@@ -1,2604 +1,2758 @@
{
- "nbformat": 4,
- "nbformat_minor": 0,
- "metadata": {
- "colab": {
- "name": "Demo_CDS_nacimientos.ipynb",
- "provenance": [],
- "collapsed_sections": []
- },
- "kernelspec": {
- "name": "python3",
- "display_name": "Python 3"
- },
- "language_info": {
- "name": "python"
- }
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "7JgsokQzYAJX"
+ },
+ "source": [
+ "# Introducción\n",
+ "---\n",
+ "En esta propuesta vamos a usar datos del ministerio de salud sobre nacimientos en el paÃs entre 2005 y 2010 para hacer algunas preguntas y obtener una respuesta visual con gráficos.\n",
+ "---\n"
+ ]
},
- "cells": [
- {
- "cell_type": "markdown",
- "source": [
- "# Introducción\n",
- "---\n",
- "En esta demostración vamos a usar datos del ministerio de salud sobre nacimientos en el paÃs entre 2005 y 2010 para hacer algunas preguntas y obtener una respuesta visual con gráficos.\n",
- "---\n",
- "# Herramientas\n",
- "---\n",
- "El lenguaje de programación de esta demostración es Python, un lenguaje muy popular para ciencia de datos, combinado con la librerÃa pandas, también muy popular, ya que nos permite manejar los datos facilmente y finalmente usamos matplotlib para graficar los datos.\n",
- "\n",
- "Pandas trabaja con dataframes, estos son la estructura básica que vamos a manipular y funcionan como una tabla con filas y columnas.\n",
- "\n",
- "---\n",
- "# Funciones importantes\n",
- "---\n",
- "A lo largo de esta demostración vamos a usar 7 funciones principales:\n",
- "\n",
- "# head:\n",
- "Esta función nos permite ver las primeras 5 filas de un dataframe, además de los nombres de columnas. Es muy útil para visualizar una operación.\n",
- "\n",
- "#loc:\n",
- "Esta función nos permite obtener ciertas filas en las columnas que nombramos.\n",
- "Por ejemplo, si tenemos un dataframe con colores y dÃas: \n",
- "\n",
- "\n",
- "\n",
- "\n",
- "dataframe.loc[0:2,[\"color\",\"dÃa\"]] nos da:\n",
- "\n",
- "\n",
- "\n",
- "\n",
- "Nosotros la vamos a usar para obtener ciertas columnas y no vamos a cortar filas, para esto se dejan los lugares al lado de los dos puntos vacÃos.\n",
- "\n",
- "#groupby\n",
- "\n",
- "Esta potente función, nos permite agrupar nuestra información basados en los valores de una columna y luego manipular esos grupos.\n",
- "\n",
- "#sum\n",
- "Nos permite sumar los valores de un DataFrame, o en nuestro caso de los grupos de un groupby.\n",
- "\n",
- "#drop\n",
- "Esta función nos permite eliminar filas de un dataframe, hay que indicarle una condición para seleccionar cuales se borran.\n",
- "\n",
- "#plot\n",
- "Nos permite graficar los datos de un dataframe, le indicamos el tipo de gráfico con kind, y tiene otros parámetros para cosas como tamaño, titulo, etc.\n",
- "\n",
- "#plt.legend\n",
- "Esta función nos permite especificar la leyenda que queremos en nuestro gráfico.\n",
- "\n"
- ],
- "metadata": {
- "id": "7JgsokQzYAJX"
- }
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Qué información podemos obtener"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Link donde obtengo el dataset"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Comentarios sobre el notebooks:\n",
+ "* poner que información vamos a averiguar\n",
+ "* pasar la descripción de las isntrucciones al final como unasección :referencias técnicas\n",
+ "* me parece más claro al quedarse con las columnas en la celda que agregué con la variable *nac_sofia*\n",
+ "* poner el link de donde se obtuvo el dataset\n",
+ "* agregar el grid en los gráficos"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Herramientas\n",
+ "---\n",
+ "El lenguaje de programación que estamos utilizando es **Python**, un lenguaje muy popular para ciencia de datos, combinado con la librerÃa *pandas*, también muy popular, ya que nos permite manejar los datos fácilmente y finalmente usamos *matplotlib* para graficar los datos.\n",
+ "\n",
+ "Pandas trabaja con dataframes, estos son la estructura básica que vamos a manipular y funcionan como una tabla con filas y columnas.\n",
+ "\n",
+ "---\n",
+ "# Funciones importantes\n",
+ "---\n",
+ "A lo largo de esta demostración vamos a usar 7 funciones principales:\n",
+ "\n",
+ "# head:\n",
+ "Esta función nos permite ver las primeras 5 filas de un dataframe, además de los nombres de columnas. Es muy útil para visualizar una operación.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# loc:\n",
+ "Esta función nos permite obtener ciertas filas en las columnas que nombramos.\n",
+ "Por ejemplo, si tenemos un dataframe con colores y dÃas: \n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "dataframe.loc[0:2,[\"color\",\"dÃa\"]] nos da:\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "Nosotros la vamos a usar para obtener ciertas columnas y no vamos a cortar filas, para esto se dejan los lugares al lado de los dos puntos vacÃos.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# groupby\n",
+ "\n",
+ "Esta potente función, nos permite agrupar nuestra información basados en los valores de una columna y luego realizar operaciones con esos grupos.\n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# sum\n",
+ "Nos permite sumar los valores de un conjunto de datos, columna, fila, o en nuestro caso de los grupos de un groupby.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# drop\n",
+ "Esta función nos permite eliminar filas de un dataframe, hay que indicarle una condición para seleccionar cuales se borran.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# plot\n",
+ "Nos permite graficar los datos de un dataframe, le indicamos el tipo de gráfico con la instrucción *kind*, y tiene otros parámetros para cosas como tamaño, titulo, etc.\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# plt.legend\n",
+ "Esta función nos permite especificar la leyenda que queremos en nuestro gráfico."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "QYEZLjtwiH6p"
+ },
+ "source": [
+ "Primero importamos pandas, esto nos permitirá usar las funciones que provee, es costumbre renombrarla como **pd** y también el módulo pyplot de matplotlib normalmente abreviado como **plt**"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "id": "gSPpdLmni-mZ"
+ },
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "import matplotlib.pyplot as plt\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "mGIGSZnmiTyN"
+ },
+ "source": [
+ "Usamos la función **read_csv** que nos transforma nuestros datos (en formato csv) a un dataframe que podemos manipular fácilmente."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "id": "oanfaLLOvlVG"
+ },
+ "outputs": [],
+ "source": [
+ "nacimientos = pd.read_csv(\"Nacimientos_Arg_2005-2010.csv\",encoding = \"UTF-8\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "6cuhJ6w2zbUc"
+ },
+ "source": [
+ "Vamos a ver como vemos la información:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 357
},
+ "id": "FDFSoh0Xwh3M",
+ "outputId": "91c1ca7e-6677-4cc4-9e06-57c461fc8374"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Primero importamos pandas, esto nos permitirá usar las funciones que provee, es costumbre renombrarla como pd y también el módulo pyplot de matplotlib normalmente abreviado como plt"
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+ " .dataframe tbody tr th {\n",
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+ " }\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>anio</th>\n",
+ " <th>jurisdiccion_de_residencia_id</th>\n",
+ " <th>jurisdicion_residencia_nombre</th>\n",
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+ " <td>30 a 34</td>\n",
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+ " <td>4</td>\n",
+ " <td>28 a 31</td>\n",
+ " <td>1500 a 1999</td>\n",
+ " <td>masculino</td>\n",
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+ " <td>masculino</td>\n",
+ " <td>6</td>\n",
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+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>2005</td>\n",
+ " <td>2</td>\n",
+ " <td>Ciudad Autónoma de Buenos Aires</td>\n",
+ " <td>5</td>\n",
+ " <td>30 a 34</td>\n",
+ " <td>Secundaria/Polimodal Incompleta</td>\n",
+ " <td>5</td>\n",
+ " <td>32 a 36</td>\n",
+ " <td>1500 a 1999</td>\n",
+ " <td>masculino</td>\n",
+ " <td>5</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>2005</td>\n",
+ " <td>2</td>\n",
+ " <td>Ciudad Autónoma de Buenos Aires</td>\n",
+ " <td>4</td>\n",
+ " <td>25 a 29</td>\n",
+ " <td>Secundaria/Polimodal Completa</td>\n",
+ " <td>4</td>\n",
+ " <td>28 a 31</td>\n",
+ " <td>1500 a 1999</td>\n",
+ " <td>masculino</td>\n",
+ " <td>1</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
],
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- "id": "QYEZLjtwiH6p"
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {
- "id": "gSPpdLmni-mZ"
- },
- "outputs": [],
- "source": [
- "import pandas as pd\n",
- "import matplotlib.pyplot as plt"
+ "text/plain": [
+ " anio jurisdiccion_de_residencia_id jurisdicion_residencia_nombre \\\n",
+ "0 2005 2 Ciudad Autónoma de Buenos Aires \n",
+ "1 2005 2 Ciudad Autónoma de Buenos Aires \n",
+ "2 2005 2 Ciudad Autónoma de Buenos Aires \n",
+ "3 2005 2 Ciudad Autónoma de Buenos Aires \n",
+ "4 2005 2 Ciudad Autónoma de Buenos Aires \n",
+ "\n",
+ " edad_madre_grupo_id edad_madre_grupo instruccion_madre \\\n",
+ "0 5 30 a 34 Secundaria/Polimodal Incompleta \n",
+ "1 5 30 a 34 Primaria/C. EGB Completa \n",
+ "2 4 25 a 29 Secundaria/Polimodal Completa \n",
+ "3 5 30 a 34 Secundaria/Polimodal Incompleta \n",
+ "4 4 25 a 29 Secundaria/Polimodal Completa \n",
+ "\n",
+ " semana_gestacion_id semana_gestacion intervalo_peso_al_nacer Sexo \\\n",
+ "0 4 28 a 31 1500 a 1999 masculino \n",
+ "1 4 28 a 31 500 a 999 masculino \n",
+ "2 4 28 a 31 1000 a 1499 masculino \n",
+ "3 5 32 a 36 1500 a 1999 masculino \n",
+ "4 4 28 a 31 1500 a 1999 masculino \n",
+ "\n",
+ " nacimientos_cantidad \n",
+ "0 1 \n",
+ "1 2 \n",
+ "2 6 \n",
+ "3 5 \n",
+ "4 1 "
]
- },
- {
- "cell_type": "markdown",
- "source": [
- "Usamos la función read_csv que nos transforma nuestros datos (en formato csv) a un dtaframe que podemos manipular facilmente."
- ],
- "metadata": {
- "id": "mGIGSZnmiTyN"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nacimientos = pd.read_csv(\"Nacimientos_Arg_2005-2010.csv\",encoding = \"UTF-8\")"
- ],
- "metadata": {
- "id": "oanfaLLOvlVG"
- },
- "execution_count": null,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "source": [
- "Vamos a ver comose ve la información:"
- ],
- "metadata": {
- "id": "6cuhJ6w2zbUc"
- }
- },
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nacimientos.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "B6kS1QTB6aF9"
+ },
+ "source": [
+ "No vamos a trabajar con toda la información, asi que la cortamos a las columnas que nos interesan:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "nac_sofia = nacimientos[[\"anio\",\"edad_madre_grupo\",\"instruccion_madre\",\"nacimientos_cantidad\"]]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nacimientos.head()"
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+ " </tr>\n",
+ " <tr>\n",
+ " <th>497973</th>\n",
+ " <td>2017</td>\n",
+ " <td>Sin especificar</td>\n",
+ " <td>Sin especificar</td>\n",
+ " <td>10</td>\n",
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+ "<p>497974 rows × 4 columns</p>\n",
+ "</div>"
],
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- "data": {
- "text/plain": [
- " anio jurisdiccion_de_residencia_id jurisdicion_residencia_nombre \\\n",
- "0 2005 2 Ciudad Autónoma de Buenos Aires \n",
- "1 2005 2 Ciudad Autónoma de Buenos Aires \n",
- "2 2005 2 Ciudad Autónoma de Buenos Aires \n",
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- "2 4 25 a 29 Secundaria/Polimodal Completa \n",
- "3 5 30 a 34 Secundaria/Polimodal Incompleta \n",
- "4 4 25 a 29 Secundaria/Polimodal Completa \n",
- "\n",
- " semana_gestacion_id semana_gestacion intervalo_peso_al_nacer Sexo \\\n",
- "0 4 28 a 31 1500 a 1999 masculino \n",
- "1 4 28 a 31 500 a 999 masculino \n",
- "2 4 28 a 31 1000 a 1499 masculino \n",
- "3 5 32 a 36 1500 a 1999 masculino \n",
- "4 4 28 a 31 1500 a 1999 masculino \n",
- "\n",
- " nacimientos_cantidad \n",
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- "3 5 \n",
- "4 1 "
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+ "text/plain": [
+ " anio edad_madre_grupo instruccion_madre \\\n",
+ "0 2005 30 a 34 Secundaria/Polimodal Incompleta \n",
+ "1 2005 30 a 34 Primaria/C. EGB Completa \n",
+ "2 2005 25 a 29 Secundaria/Polimodal Completa \n",
+ "3 2005 30 a 34 Secundaria/Polimodal Incompleta \n",
+ "4 2005 25 a 29 Secundaria/Polimodal Completa \n",
+ "... ... ... ... \n",
+ "497969 2017 30 a 34 Secundaria/Polimodal Completa \n",
+ "497970 2017 30 a 34 Secundaria/Polimodal Completa \n",
+ "497971 2007 25 a 29 Terciaria/Universitaria Completa \n",
+ "497972 2017 30 a 34 Terciaria/Universitaria Incompleta \n",
+ "497973 2017 Sin especificar Sin especificar \n",
+ "\n",
+ " nacimientos_cantidad \n",
+ "0 1 \n",
+ "1 2 \n",
+ "2 6 \n",
+ "3 5 \n",
+ "4 1 \n",
+ "... ... \n",
+ "497969 1 \n",
+ "497970 1 \n",
+ "497971 1 \n",
+ "497972 1 \n",
+ "497973 10 \n",
+ "\n",
+ "[497974 rows x 4 columns]"
]
- },
- {
- "cell_type": "markdown",
- "source": [
- "No vamos a trabajar con toda la información, asique la cortamos a las columnas que nos interesan:"
- ],
- "metadata": {
- "id": "B6kS1QTB6aF9"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nacimientos = nacimientos.loc[:,[\"anio\",\"edad_madre_grupo\",\"instruccion_madre\",\"nacimientos_cantidad\"]]"
- ],
- "metadata": {
- "id": "Z9xxlqmM6kc4"
- },
- "execution_count": null,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "source": [
- "Pregunta: ¿Cuántos nacidos vivos hay por año en el paÃs?"
- ],
- "metadata": {
- "id": "HY9NHf7Mw2Z8"
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "Para esto vamos a necesitar menos información que antes, solo la cantidad de nacimientos y el año en el que ocurrieron.\n",
- "Se abrevia nacimientos como nac para mayor legibilidad:"
- ],
- "metadata": {
- "id": "XJ_i_X3IA5oI"
- }
- },
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_sofia"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {
+ "id": "Z9xxlqmM6kc4"
+ },
+ "outputs": [],
+ "source": [
+ "nacimientos = nacimientos.loc[:,[\"anio\",\"edad_madre_grupo\",\"instruccion_madre\",\"nacimientos_cantidad\"]]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {},
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nac_por_año = nacimientos.loc[:,[\"anio\",\"nacimientos_cantidad\"]]\n",
- "nac_por_año.head()"
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+ " anio edad_madre_grupo instruccion_madre \\\n",
+ "0 2005 30 a 34 Secundaria/Polimodal Incompleta \n",
+ "1 2005 30 a 34 Primaria/C. EGB Completa \n",
+ "2 2005 25 a 29 Secundaria/Polimodal Completa \n",
+ "3 2005 30 a 34 Secundaria/Polimodal Incompleta \n",
+ "4 2005 25 a 29 Secundaria/Polimodal Completa \n",
+ "... ... ... ... \n",
+ "497969 2017 30 a 34 Secundaria/Polimodal Completa \n",
+ "497970 2017 30 a 34 Secundaria/Polimodal Completa \n",
+ "497971 2007 25 a 29 Terciaria/Universitaria Completa \n",
+ "497972 2017 30 a 34 Terciaria/Universitaria Incompleta \n",
+ "497973 2017 Sin especificar Sin especificar \n",
+ "\n",
+ " nacimientos_cantidad \n",
+ "0 1 \n",
+ "1 2 \n",
+ "2 6 \n",
+ "3 5 \n",
+ "4 1 \n",
+ "... ... \n",
+ "497969 1 \n",
+ "497970 1 \n",
+ "497971 1 \n",
+ "497972 1 \n",
+ "497973 10 \n",
+ "\n",
+ "[497974 rows x 4 columns]"
]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nacimientos"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "HY9NHf7Mw2Z8"
+ },
+ "source": [
+ "Pregunta: ¿Cuántos nacimientos hay por año en el paÃs?"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "XJ_i_X3IA5oI"
+ },
+ "source": [
+ "Para esto vamos a necesitar menos información que antes, solo la cantidad de nacimientos y el año en el que ocurrieron.\n",
+ "Se abrevia nacimientos como nac para mayor legibilidad:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
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+ "height": 206
},
+ "id": "I-PYL_Qez5hV",
+ "outputId": "c2f2eca1-7814-459a-92c7-2312ceef12ae"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Hay un problema con esta información, como la cantidad de nacimientos no está agregada por año sino que también por otros factores, hay que agrupar por año y sumar los nacimientos de cada grupo:"
- ],
- "metadata": {
- "id": "D6Dps9axBQrp"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nac_por_año = nac_por_año.groupby(\"anio\").sum()\n",
- "nac_por_año.head()"
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- "anio \n",
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+ "text/plain": [
+ " anio nacimientos_cantidad\n",
+ "0 2005 1\n",
+ "1 2005 2\n",
+ "2 2005 6\n",
+ "3 2005 5\n",
+ "4 2005 1"
]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_por_año = nacimientos.loc[:,[\"anio\",\"nacimientos_cantidad\"]]\n",
+ "nac_por_año.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "D6Dps9axBQrp"
+ },
+ "source": [
+ "Hay un problema con esta información, como la cantidad de nacimientos no está agregada por año sino que también por otros factores, hay que agrupar por año y sumar los nacimientos de cada grupo:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 238
},
+ "id": "FbY9_hRmBDuW",
+ "outputId": "d998fa9e-dd17-4c9c-b6e1-20d89040609c"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Ahora está mejor.\n",
- "Vamos a graficarlo con un simple gráfico de lÃnea:"
- ],
- "metadata": {
- "id": "xPLMRoEUmicq"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nac_por_año.plot(kind= \"line\",figsize= (15,7),)\n",
- "plt.legend([\"Cantidad de nacimientos\"])"
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- "execution_count": 7
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "<Figure size 1080x504 with 1 Axes>"
- ],
- "image/png": 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\n"
- },
- "metadata": {
- "needs_background": "light"
- }
- }
+ "text/plain": [
+ " nacimientos_cantidad\n",
+ "anio \n",
+ "2005 712220\n",
+ "2006 696451\n",
+ "2007 700792\n",
+ "2008 746460\n",
+ "2009 745336"
]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_por_año = nac_por_año.groupby(\"anio\").sum()\n",
+ "nac_por_año.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "xPLMRoEUmicq"
+ },
+ "source": [
+ "Ahora está mejor.\n",
+ "Vamos a graficarlo con un simple gráfico de lÃnea:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 459
},
+ "id": "19u3wAvl0jIN",
+ "outputId": "c992d64b-5c86-461f-a177-b7b2267985a3"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Hay un problema con el gráfico, el eje y no comienza en 0 y hace que el gráfico se vea mal, esto se soluciona indicando el lÃmite inferior de y:\n",
- "También establecemos la leyenda del gráfico"
- ],
- "metadata": {
- "id": "ef0DL8Gh8jLf"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nac_por_año.plot(kind= \"line\",figsize= (15,7),ylim=(0))\n",
- "plt.legend([\"Cantidad de nacimientos\"])"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 459
- },
- "id": "D8TfEws58gvQ",
- "outputId": "bf04b080-2228-419e-f6a7-3fdfeb702573"
- },
- "execution_count": null,
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x7fb578d6e390>"
- ]
- },
- "metadata": {},
- "execution_count": 8
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "<Figure size 1080x504 with 1 Axes>"
- ],
- "image/png": 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- }
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x7fb578ea6e10>"
]
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+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
},
{
- "cell_type": "markdown",
- "source": [
- "Pregunta: ¿Cuántos nacidos vivos hay por año en el paÃs según el grupo etario de la madre?"
- ],
- "metadata": {
- "id": "_NpC6hVyzwSc"
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "En este caso necesitamos saber el año, el grupo etario de la madre y la cantidad:"
- ],
- "metadata": {
- "id": "IgOe-p4pCly3"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nac_edad_madre = nacimientos.loc[:,[\"anio\",\"edad_madre_grupo\",\"nacimientos_cantidad\"]]\n"
- ],
- "metadata": {
- "id": "glA4XLTT86wg"
- },
- "execution_count": null,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "source": [
- "Hay algunos nacimientos donde el grupo etario de la madre no fue especificado, por lo tanto no podemos sacar conclusiones, asique se ignoran."
- ],
- "metadata": {
- "id": "qCnqL52JC-SA"
- }
- },
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- "cell_type": "code",
- "source": [
- "nac_edad_madre.drop(nac_edad_madre.index[nac_edad_madre['edad_madre_grupo'] == \"Sin especificar\"], inplace = True)"
- ],
- "metadata": {
- "id": "If8D3jpHC93r"
- },
- "execution_count": null,
- "outputs": []
- },
- {
- "cell_type": "markdown",
- "source": [
- "Ahora con la información filtrada, hay que agrupar por dos criterios, primero por el año y luego por el grupo etario y finalmente sumar las cantidades de estos grupos:"
- ],
- "metadata": {
- "id": "ccDvLT5BDpKQ"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nac_edad_madre=nac_edad_madre.groupby([\"anio\",\"edad_madre_grupo\"]).sum()\n",
- "nac_edad_madre.head()"
- ],
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- "output_type": "execute_result",
- "data": {
- "text/plain": [
- " nacimientos_cantidad\n",
- "anio edad_madre_grupo \n",
- "2005 Menor de 15 2699\n",
- " 15 a 19 104410\n",
- " 20 a 24 177813\n",
- " 25 a 29 182778\n",
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- " }\n",
- "\n",
- " [theme=dark] .colab-df-convert {\n",
- " background-color: #3B4455;\n",
- " fill: #D2E3FC;\n",
- " }\n",
- "\n",
- " [theme=dark] .colab-df-convert:hover {\n",
- " background-color: #434B5C;\n",
- " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
- " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
- " fill: #FFFFFF;\n",
- " }\n",
- " </style>\n",
- "\n",
- " <script>\n",
- " const buttonEl =\n",
- " document.querySelector('#df-901b47a4-ae34-46e5-a722-e9cae84c43a9 button.colab-df-convert');\n",
- " buttonEl.style.display =\n",
- " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
- "\n",
- " async function convertToInteractive(key) {\n",
- " const element = document.querySelector('#df-901b47a4-ae34-46e5-a722-e9cae84c43a9');\n",
- " const dataTable =\n",
- " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
- " [key], {});\n",
- " if (!dataTable) return;\n",
- "\n",
- " const docLinkHtml = 'Like what you see? Visit the ' +\n",
- " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
- " + ' to learn more about interactive tables.';\n",
- " element.innerHTML = '';\n",
- " dataTable['output_type'] = 'display_data';\n",
- " await google.colab.output.renderOutput(dataTable, element);\n",
- " const docLink = document.createElement('div');\n",
- " docLink.innerHTML = docLinkHtml;\n",
- " element.appendChild(docLink);\n",
- " }\n",
- " </script>\n",
- " </div>\n",
- " </div>\n",
- " "
- ]
- },
- "metadata": {},
- "execution_count": 11
- }
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ "<Figure size 1080x504 with 1 Axes>"
]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nac_por_año.plot(kind= \"line\",figsize= (15,7),)\n",
+ "plt.legend([\"Cantidad de nacimientos\"])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "ef0DL8Gh8jLf"
+ },
+ "source": [
+ "Hay un problema con el gráfico, el eje y no comienza en 0 y hace que el gráfico se vea mal, esto se soluciona indicando el lÃmite inferior de y:\n",
+ "También establecemos la leyenda del gráfico"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 459
},
+ "id": "D8TfEws58gvQ",
+ "outputId": "bf04b080-2228-419e-f6a7-3fdfeb702573"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "La información comoestá no puede ser graficada, ya que está toda junta en 2 grupos, asique usamos la función .unstack(), que despliega la información para que se puede visualizar"
- ],
- "metadata": {
- "id": "AO6pJxA6EIKF"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nac_edad_madre = nac_edad_madre.unstack()\n",
- "nac_edad_madre.head()"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 269
- },
- "id": "l13_EjwlEWhK",
- "outputId": "22f5d144-62d2-4192-c7d2-08a83caf7dee"
- },
- "execution_count": null,
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- " nacimientos_cantidad \\\n",
- "edad_madre_grupo Menor de 15 15 a 19 20 a 24 25 a 29 30 a 34 35 a 39 \n",
- "anio \n",
- "2005 2699 104410 177813 182778 141689 73194 \n",
- "2006 2766 103885 174342 176931 139003 73177 \n",
- "2007 2841 106720 174679 175632 139393 73532 \n",
- "2008 2937 112034 183265 184978 153805 80258 \n",
- "2009 3346 113478 182747 178935 155464 81397 \n",
- "\n",
- " \n",
- "edad_madre_grupo 40 a 44 De 45 y más \n",
- "anio \n",
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{
- "cell_type": "markdown",
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- "Finalmente graficamos como en los ejemplos anteriores, con la diferencia de que ahora hay varios grupos lo que nos da varias lÃneas. No existe el mismo problema del eje y ya que ciertos grupos tienen muy pocos nacimientos y esto hace que el eje empieze en 0:"
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- ],
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\n",
+ "text/plain": [
+ "<Figure size 1080x504 with 1 Axes>"
]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nac_por_año.plot(kind= \"line\",figsize= (15,7),ylim=(0))\n",
+ "plt.legend([\"Cantidad de nacimientos\"])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "_NpC6hVyzwSc"
+ },
+ "source": [
+ "Pregunta: ¿Cuántos nacidos vivos hay por año en el paÃs según el grupo etario de la madre?"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "IgOe-p4pCly3"
+ },
+ "source": [
+ "En este caso necesitamos saber el año, el grupo etario de la madre y la cantidad:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {
+ "id": "glA4XLTT86wg"
+ },
+ "outputs": [],
+ "source": [
+ "nac_edad_madre = nacimientos.loc[:,[\"anio\",\"edad_madre_grupo\",\"nacimientos_cantidad\"]]\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "qCnqL52JC-SA"
+ },
+ "source": [
+ "Hay algunos nacimientos donde el grupo etario de la madre no fue especificado, por lo tanto no podemos sacar conclusiones, asique se ignoran."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {
+ "id": "If8D3jpHC93r"
+ },
+ "outputs": [],
+ "source": [
+ "nac_edad_madre.drop(nac_edad_madre.index[nac_edad_madre['edad_madre_grupo'] == \"Sin especificar\"], inplace = True)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "ccDvLT5BDpKQ"
+ },
+ "source": [
+ "Ahora con la información filtrada, hay que agrupar por dos criterios, primero por el año y luego por el grupo etario y finalmente sumar las cantidades de estos grupos:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 238
},
+ "id": "-iJyxCfUC2SY",
+ "outputId": "ce5721ab-c4ca-48b8-afb5-08f9abeae1ad"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Pregunta: ¿Que proporción de madres tuvo hijos antes de los 20?"
- ],
- "metadata": {
- "id": "bPtagRwyz4t4"
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "Igual que los ejemplos anteriores, seleccionamos las columnas relevantes,edad_madre_grupo y nacimientos_cantidad filtrando los sin especificar:"
- ],
- "metadata": {
- "id": "VIiicLlNFoX5"
- }
- },
- {
- "cell_type": "code",
- "source": [
- "nac_madre_menor_20 = nacimientos.loc[:,[\"edad_madre_grupo\",\"nacimientos_cantidad\"]]\n",
- "nac_madre_menor_20.drop(nac_madre_menor_20.index[nac_madre_menor_20['edad_madre_grupo'] == \"Sin especificar\"], inplace = True)"
+ "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></th>\n",
+ " <th>nacimientos_cantidad</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>anio</th>\n",
+ " <th>edad_madre_grupo</th>\n",
+ " <th></th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th rowspan=\"5\" valign=\"top\">2005</th>\n",
+ " <th>Menor de 15</th>\n",
+ " <td>2699</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>15 a 19</th>\n",
+ " <td>104410</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>20 a 24</th>\n",
+ " <td>177813</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>25 a 29</th>\n",
+ " <td>182778</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>30 a 34</th>\n",
+ " <td>141689</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
],
- "metadata": {
- "id": "8lqCEEoFF1JP"
- },
- "execution_count": null,
- "outputs": []
+ "text/plain": [
+ " nacimientos_cantidad\n",
+ "anio edad_madre_grupo \n",
+ "2005 Menor de 15 2699\n",
+ " 15 a 19 104410\n",
+ " 20 a 24 177813\n",
+ " 25 a 29 182778\n",
+ " 30 a 34 141689"
+ ]
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_edad_madre = nac_edad_madre.groupby([\"anio\",\"edad_madre_grupo\"]).sum()\n",
+ "nac_edad_madre.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "AO6pJxA6EIKF"
+ },
+ "source": [
+ "La información como está no puede ser graficada, ya que está toda junta en 2 grupos, asi que usamos la función .unstack(), que despliega la información para que se puede visualizar"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 269
},
+ "id": "l13_EjwlEWhK",
+ "outputId": "22f5d144-62d2-4192-c7d2-08a83caf7dee"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Luego agrupamos los nacimientos en dos categorÃas, basado en si cumple o no la condición: Si está en los grupos \" Menor de 15\" o \"15 a 19\", ponerlos en un grupo, sino en otro grupo. (la | es el equivalente a un \"o\")"
+ "data": {
+ "text/html": [
+ "\n",
+ " <div id=\"df-c12f7bb2-7584-4d83-8fc7-65f82c89ec8b\">\n",
+ " <div class=\"colab-df-container\">\n",
+ " <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></th>\n",
+ " <th colspan=\"8\" halign=\"left\">nacimientos_cantidad</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>edad_madre_grupo</th>\n",
+ " <th>Menor de 15</th>\n",
+ " <th>15 a 19</th>\n",
+ " <th>20 a 24</th>\n",
+ " <th>25 a 29</th>\n",
+ " <th>30 a 34</th>\n",
+ " <th>35 a 39</th>\n",
+ " <th>40 a 44</th>\n",
+ " <th>De 45 y más</th>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>anio</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>2005</th>\n",
+ " <td>2699</td>\n",
+ " <td>104410</td>\n",
+ " <td>177813</td>\n",
+ " <td>182778</td>\n",
+ " <td>141689</td>\n",
+ " <td>73194</td>\n",
+ " <td>21382</td>\n",
+ " <td>1575</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2006</th>\n",
+ " <td>2766</td>\n",
+ " <td>103885</td>\n",
+ " <td>174342</td>\n",
+ " <td>176931</td>\n",
+ " <td>139003</td>\n",
+ " <td>73177</td>\n",
+ " <td>19866</td>\n",
+ " <td>1488</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2007</th>\n",
+ " <td>2841</td>\n",
+ " <td>106720</td>\n",
+ " <td>174679</td>\n",
+ " <td>175632</td>\n",
+ " <td>139393</td>\n",
+ " <td>73532</td>\n",
+ " <td>19879</td>\n",
+ " <td>1497</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2008</th>\n",
+ " <td>2937</td>\n",
+ " <td>112034</td>\n",
+ " <td>183265</td>\n",
+ " <td>184978</td>\n",
+ " <td>153805</td>\n",
+ " <td>80258</td>\n",
+ " <td>20824</td>\n",
+ " <td>1630</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2009</th>\n",
+ " <td>3346</td>\n",
+ " <td>113478</td>\n",
+ " <td>182747</td>\n",
+ " <td>178935</td>\n",
+ " <td>155464</td>\n",
+ " <td>81397</td>\n",
+ " <td>20840</td>\n",
+ " <td>1546</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>\n",
+ " <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c12f7bb2-7584-4d83-8fc7-65f82c89ec8b')\"\n",
+ " title=\"Convert this dataframe to an interactive table.\"\n",
+ " style=\"display:none;\">\n",
+ " \n",
+ " <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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+ " </svg>\n",
+ " </button>\n",
+ " \n",
+ " <style>\n",
+ " .colab-df-container {\n",
+ " display:flex;\n",
+ " flex-wrap:wrap;\n",
+ " gap: 12px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert {\n",
+ " background-color: #E8F0FE;\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
+ " cursor: pointer;\n",
+ " display: none;\n",
+ " fill: #1967D2;\n",
+ " height: 32px;\n",
+ " padding: 0 0 0 0;\n",
+ " width: 32px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
+ " background-color: #E2EBFA;\n",
+ " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: #174EA6;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert {\n",
+ " background-color: #3B4455;\n",
+ " fill: #D2E3FC;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert:hover {\n",
+ " background-color: #434B5C;\n",
+ " box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+ " filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+ " fill: #FFFFFF;\n",
+ " }\n",
+ " </style>\n",
+ "\n",
+ " <script>\n",
+ " const buttonEl =\n",
+ " document.querySelector('#df-c12f7bb2-7584-4d83-8fc7-65f82c89ec8b button.colab-df-convert');\n",
+ " buttonEl.style.display =\n",
+ " google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+ "\n",
+ " async function convertToInteractive(key) {\n",
+ " const element = document.querySelector('#df-c12f7bb2-7584-4d83-8fc7-65f82c89ec8b');\n",
+ " const dataTable =\n",
+ " await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+ " [key], {});\n",
+ " if (!dataTable) return;\n",
+ "\n",
+ " const docLinkHtml = 'Like what you see? Visit the ' +\n",
+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
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+ " </div>\n",
+ " </div>\n",
+ " "
],
- "metadata": {
- "id": "Gyor1fguGMyw"
- }
+ "text/plain": [
+ " nacimientos_cantidad \\\n",
+ "edad_madre_grupo Menor de 15 15 a 19 20 a 24 25 a 29 30 a 34 35 a 39 \n",
+ "anio \n",
+ "2005 2699 104410 177813 182778 141689 73194 \n",
+ "2006 2766 103885 174342 176931 139003 73177 \n",
+ "2007 2841 106720 174679 175632 139393 73532 \n",
+ "2008 2937 112034 183265 184978 153805 80258 \n",
+ "2009 3346 113478 182747 178935 155464 81397 \n",
+ "\n",
+ " \n",
+ "edad_madre_grupo 40 a 44 De 45 y más \n",
+ "anio \n",
+ "2005 21382 1575 \n",
+ "2006 19866 1488 \n",
+ "2007 19879 1497 \n",
+ "2008 20824 1630 \n",
+ "2009 20840 1546 "
+ ]
+ },
+ "execution_count": 12,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_edad_madre = nac_edad_madre.unstack()\n",
+ "nac_edad_madre.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "tNJtFS-WEc0l"
+ },
+ "source": [
+ "Finalmente graficamos como en los ejemplos anteriores, con la diferencia de que ahora hay varios grupos lo que nos da varias lÃneas. No existe el mismo problema del eje y ya que ciertos grupos tienen muy pocos nacimientos y esto hace que el eje empiece en 0:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 777
},
+ "id": "o6puSivZDjIQ",
+ "outputId": "9ad8a5e5-1427-46a3-9b82-6a5b5c9d0c57"
+ },
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nac_madre_menor_20=nac_madre_menor_20.groupby((nac_madre_menor_20.edad_madre_grupo == \" Menor de 15\") | (nac_madre_menor_20.edad_madre_grupo == \"15 a 19\"))"
- ],
- "metadata": {
- "id": "KzbpAR3kGMPo"
- },
- "execution_count": null,
- "outputs": []
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x7fb57882c110>"
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
},
{
- "cell_type": "markdown",
- "source": [
- "Luego sumamos los nacimientos de cada grupo:"
- ],
- "metadata": {
- "id": "a-9-o4q3MGjm"
- }
- },
+ "data": {
+ "image/png": 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7krxkAf0DAADY1erUUzYAAAAAAABgmjw+EQAAAAAAgMmTFAMAAAAAAGDyJMUAAAAAAACYPEkxAAAAAAAAJk9SDAAAAAAAgMmTFAMAAAAAAGDyJMUAAAAAAACYvP8HHCZiUnZ01joAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ "<Figure size 2160x1080 with 1 Axes>"
+ ]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nac_edad_madre.plot(kind= \"line\",figsize= (30,15))\n",
+ "plt.legend([\"Menor de 15\", \"15 a 19\", \"20 a 24\", \"25 a 29\", \"30 a 34\", \"35 a 39\", \"40 a 44\", \"De 45 y más\"])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "bPtagRwyz4t4"
+ },
+ "source": [
+ "Pregunta: ¿Que proporción de madres tuvo hijos antes de los 20?"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "VIiicLlNFoX5"
+ },
+ "source": [
+ "Igual que los ejemplos anteriores, seleccionamos las columnas relevantes,edad_madre_grupo y nacimientos_cantidad filtrando los sin especificar:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 57,
+ "metadata": {
+ "id": "8lqCEEoFF1JP"
+ },
+ "outputs": [],
+ "source": [
+ "nac_madre_menor_20 = nacimientos.loc[:,[\"edad_madre_grupo\",\"nacimientos_cantidad\"]]\n",
+ "nac_madre_menor_20.drop(nac_madre_menor_20.index[\n",
+ " nac_madre_menor_20['edad_madre_grupo'] == \"Sin especificar\"], inplace = True)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Si consultamos cuáles son los valores únicos que tiene la columna \"edad_madre:grupo\" nos encontramos con filas que no tienen información significativa"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 65,
+ "metadata": {},
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nac_madre_menor_20=nac_madre_menor_20.sum()\n",
- "nac_madre_menor_20.head()"
- ],
- "metadata": {
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 143
- },
- "id": "3HFy7OavMCJU",
- "outputId": "a9c476c6-c382-4746-958e-d08e03c0facd"
- },
- "execution_count": null,
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
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+ "data": {
+ "text/plain": [
+ "array(['30 a 34', '25 a 29', '20 a 24', '15 a 19', 'Sin especificar',\n",
+ " '40 a 44', 'De 45 y más', ' Menor de 15', '35 a 39'], dtype=object)"
]
- },
+ },
+ "execution_count": 65,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_sofia_menor_20 = nacimientos[[\"edad_madre_grupo\",\"nacimientos_cantidad\"]]\n",
+ "nac_sofia_menor_20[\"edad_madre_grupo\"].unique()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Eliminamos las filas que dicen 'Sin especificar' "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 64,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "nac_sofia_menor_20 = nac_sofia_menor_20.drop(nac_sofia_menor_20[nac_sofia_menor_20['edad_madre_grupo'] == \"Sin especificar\"].index)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 63,
+ "metadata": {},
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Hay un problema con esta información, en la columna de grupo dece \"True\" y \"False\", esto es por la operación de clasificación de más arriba. Hay que renombrarlos para que true sea: Menor a 20 (osea que estaba en uno de los rangos etarios de nuestra condición) o \"20 o mayor\" (osea que estaba en uno de los otros rangos etarios):"
- ],
- "metadata": {
- "id": "DFLoNabhMQG5"
- }
- },
+ "data": {
+ "text/plain": [
+ "array(['30 a 34', '25 a 29', '20 a 24', '15 a 19', '40 a 44',\n",
+ " 'De 45 y más', ' Menor de 15', '35 a 39'], dtype=object)"
+ ]
+ },
+ "execution_count": 63,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_sofia_menor_20[\"edad_madre_grupo\"].unique()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 48,
+ "metadata": {},
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nac_madre_menor_20=nac_madre_menor_20.rename({True:'Menor a 20',False:'20 o mayor'})\n",
- "nac_madre_menor_20.head()"
- ],
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- "height": 143
- },
- "id": "IiU4eCi_MwbO",
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- },
- "execution_count": null,
- "outputs": [
- {
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- "data": {
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- "edad_madre_grupo \n",
- "20 o mayor 9630285\n",
- "Menor a 20 1657570"
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- " }\n",
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- " [key], {});\n",
- " if (!dataTable) return;\n",
- "\n",
- " const docLinkHtml = 'Like what you see? Visit the ' +\n",
- " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
- " + ' to learn more about interactive tables.';\n",
- " element.innerHTML = '';\n",
- " dataTable['output_type'] = 'display_data';\n",
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- "metadata": {},
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+ "data": {
+ "text/plain": [
+ "<AxesSubplot:ylabel='nacimientos_cantidad'>"
]
+ },
+ "execution_count": 48,
+ "metadata": {},
+ "output_type": "execute_result"
},
{
- "cell_type": "markdown",
- "source": [
- "Finalmente, graficamos con un gráfico de torta para mostrar la propoción visualmente, agregando algunas cosas como los porcentajes (con autopct ='%.2f'), el tÃtulo y el tamaño."
- ],
- "metadata": {
- "id": "UQj6wVmoNjq5"
- }
- },
+ "data": {
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\n",
+ "text/plain": [
+ "<Figure size 432x288 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nac_sofia_menor_20.groupby(\"edad_madre_grupo\")[\"nacimientos_cantidad\"].count().plot(kind='pie')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "nac_sofia_rango_edad = nac_sofia_menor_20.groupby((nac_madre_menor_20.edad_madre_grupo == \" Menor de 15\") \n",
+ " | (nac_madre_menor_20.edad_madre_grupo == \"15 a 19\"))[\"edad_madre_grupo\"].count()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 67,
+ "metadata": {},
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nac_madre_menor_20.plot(kind= \"pie\", y='nacimientos_cantidad', figsize=(15, 15),autopct='%.2f',title = \"Proporción de madres tuvo hijos antes de los 20\",ylabel=\"\")\n",
- "plt.legend([\"20 o mayor\", \"Menor a 20\"])"
- ],
- "metadata": {
- "id": "fNs2UewvS6Bq",
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 879
- },
- "outputId": "a86853c1-bf6f-47c9-87c6-c7186656b47a"
- },
- "execution_count": null,
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x7fb5787ce990>"
- ]
- },
- "metadata": {},
- "execution_count": 18
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "<Figure size 1080x1080 with 1 Axes>"
- ],
- "image/png": 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\n"
- },
- "metadata": {}
- }
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x7fd4302df250>"
]
+ },
+ "execution_count": 67,
+ "metadata": {},
+ "output_type": "execute_result"
},
{
- "cell_type": "markdown",
- "source": [
- "Pregunta: Para cada nivel de instrucción/educación, ¿Cuántos nacimientos hubo en cada grupo etario?"
- ],
- "metadata": {
- "id": "Jlvd07tY0QyB"
- }
+ "data": {
+ "image/png": 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uvt6WW265bOjQoQ1dunRxQ4YMWfXtb3+7DmDcuHGfjzi9++67nXbdddfNRowYMfryyy8fMHPmzC4AkydP/vT222/vA3Ddddf1nTRp0qcAr7zySrfjjz/+s3Cdz1566aXuq1/vwAMPXFhVtf5H8VEBEhERKVOrVq2yZDI57OCDD/7syCOPXLT6/j59+jS+99571RDMFerdu3fjur5GTU3N55OJKyoq6Ny5s1t9vampyQBOPvnkISeddNInb7755vQrrrjivVWrVlUADB8+vKFv376NDzzwQI+pU6d2O/jgg+tae73u3bt/pcStCxUgERGRMpTL5Tj00EOHjhgxYmVtbe3H+cv23nvvRVdffXUfgKuvvrrPPvvss6j543feeeelN998c2+A1157rWbu3Lmdxo4du3JdsixZsqRyyJAhDQA33HBDn/xlRx999Pxjjz120/333/+z1SM748ePX3bNNdf0CvP13nbbbZeuy+uujQqQiIhIGfr3v//d/b777uvzzDPP9Nh8881Hb7755qP//ve/9wS46KKL5j7++OMbDB06dMwTTzyxwUUXXTS3+ePPOeecT3K5nI0YMWL0IYccMuzqq6/OdunSZZ12Hf/Zz34257DDDhu2xRZbjOrTp8+XRpsOO+ywuuXLl1cef/zxC1bf95e//OX9m266qe+IESNG33bbbX2uvPLKD9bldddGu8GLiIgUQfPd4KVlTz31VNfTTz998EsvvTRrfZ6nvbvB61xgIiIi4sV555034IYbbuh3/fXXv9vRr60RIBERkSLQCFDH0oEQRURERFqhAiQiIiKxowIkIiIisaMCJCIiIrGjAiQiIlKmzGybAw44YNPVtxsaGujVq9e4PfbYY7jPXC256qqreo8YMWL0iBEjRo8fP37z//73v11WL7vrrrs2SCQSY4YMGTLmvPPOG1CI19Nu8CIiIh2htuc2hX2+updaW6VLly65WbNmdVm6dKl1797d3XvvvRv079+/oaA5WtDY2Eh7z9c1fPjwVc8+++ysfv36Nd1xxx0bnHDCCUNfe+21mY2NjZx++ulDHnnkkTe/9rWvNYwbN27UxIkTF22zzTbrdFTq1TQCJCIiUsb23HPPujvvvHNDgNtuu633xIkTP1u9bPHixRUHH3xwYssttxw1atSo0TfffPOGAJdffnmfb33rW8N23XXXzYYOHTrmxBNPHLT6MVdffXXvESNGjN5ss822mDx58iar7+/atev44447btDIkSNHP/bYY93Jc9lll/UdM2bMqJEjR47ee++9hy1ZsuQr/WOvvfZa1q9fvyaAPfbYY9m8efM6ATzxxBPdhg4dumr06NH1nTt3dgceeOBnd91114br+7moAImIiJSxI4444rO///3vvZYvX24zZszouuOOOy5bvey8887beI899lg8bdq0GU8//fSs888/f9DixYsrAKZPn971vvvue2fGjBlvPPDAA73eeuut6mw2W11bW7vJE0888eb06dPfeOWVV7rddNNNGwKsWLGiYvvtt182a9as6XvvvfeXzt11+OGHL3z99ddnzJo1a/rIkSNXXH755X3XlvlPf/pT3z322KMO4IMPPui0ySab1K9eNmjQoPqPPvqo0/p+LtoEJiIiUsa23377FR9++GHNX//619577rnnl862/sQTT2zwyCOPbHj55ZcPgODs8W+99VYngF122WVxnz59mgCGDx++8u23366ZP39+1Q477LBk4MCBjQCHHHLIZ08++WT3I444YlFlZSWTJk1a2FKGl156qcsFF1ywyZIlSyqXLVtWudtuu63xrO8PPvhgj5tvvrnvc889N7NQn0FLVIBERETK3D777LPowgsvHPyvf/1r1ieffPL5737nHHfddddb48aNW5W//jPPPNOtU6dOn58qorKy0jU0NNjaXqNTp065Nc37Of744ze966673tpxxx1XXH755X2efPLJHi2tN2XKlC4nnXTS0EwmM3vAgAFNAIMHD/7SiM+HH374pRGhdaVNYCIiImVu8uTJn5511llzJkyYsCL//j322GPxZZdd1j+XywHw7LPPdmnxCUK77rrrsilTpvSYO3duVWNjI3feeWfv3XfffenaHgOwfPnyiiFDhjSsWrXKbr/99t4trTN79uxOBx988LDrrrvu3bFjx35eyHbbbbdl2Wy288yZMzutXLnS7rnnnt4TJ05c1Jb3vTYaARIRESlzw4YNazj//PM/aX5/Op2ec/zxxw/ZfPPNR+dyORs8ePCqxx9//K01Pc/QoUMbLrzwwo922223Ec4523PPPRf98Ic/XNTa66dSqTkTJkwY1bt378att9566dKlSyubr3P++edvvGjRoqpTTjllKEBVVZV7/fXXZ1RXV3PZZZe9v88++4xoamriBz/4wafbbrvteu0BBjoZqoiISFHoZKgdSydDFREREWmFCpCIiIjEjgqQiIiIxI4KkIiISHHkcrncWncdl8IIP+dcex6jAiQiIlIcr8+fP7+nSlBx5XI5mz9/fk/g9fY8TrvBi4iIFEFjY+Ox8+bNu2bevHlj0IBDMeWA1xsbG49tz4O0G7yIiIjEjhqpiIiIxI4KkIiIiMSOCpCIiIjEjgqQiIiIxI4KkIiIiMSOCpCIiIjEjgqQiIiIxI4KkIiIiMSOCpCIiIjEjgqQiIiIxI4KkIiIiMSOCpCIiIjEjgqQiIiIxI4KkIiIiMROle8AIhIfiVSmG9AD2KDZv6sv1UDjWi4NrSxvBOqBBdl0ckFHvS8RiR5zzvnOICIRlUhlOgHDgKFAv/DSN7w0v74hUNmB8eqBecDcVi6fZNPJpg7MJSIlQAVIRNYqkcoYMBgY0cIlQceWmmJoAubz1WL0AfA6MC2bTi7xF09EikEFSEQASKQyvYGRfLXkbAZ08RjNNwe8C7wGvJr37zvZdFL/gYpElAqQSAwlUpmRwC7AjsBoguLT22uo6FlKMEKUX4pe02iRSDSoAImUuUQqUw1sA+xMUHp2JpiTI4XngCxBIVpdiv6bTSfn+AwlIl+lAiRSZhKpzAbATgRlZxdgAvHehFUK3gSeAB4HHs+mkx/7jSMiKkAiEZdIZQYBu/LFCM+W6BhfpW4GXxSiJ7Lp5Hy/cUTiRwVIJGISqUwPIBlevg4M8ZtI1pMDXgEeBv5JsMlMu+WLFJkKkEgEhHtofQeYCOwF1PhNJEW0CHiMoAz9M5tOfug3jkh5UgESKVGJVGYA8D3gQGB3dOT2uHoDuA+4JZtOzvCcRaRsqACJlJBEKjOUYJTnQIJd1DWXR/K9AtwM3JZNJ+f6DiMSZSpAIp6Fx+SZGF629hxHoiEH/Ae4Bbhbxx4SaT8VIBEPEqnMOOAggpGe0Z7jSLStAB4kGBn6ZzadbPCcRyQSVIBEOki499YPgOPRSI8UxwLgDoL5Qs/6DiNSylSARIoskcpsR1B6DgW6e44j8fEucCtwczadnOk7jEipUQESKYLwaMyHA8cB4z3HEXkJuIqgDK3yHUakFKgAiRRQIpUZBfwEOALo5jmOSHPzgCuAq7Lp5Ge+w4j4pAIksp4SqUwFwVGZfwLs6TmOSFssB64HfpdNJ9/xHUbEBxUgkXUUbuY6GjgZGOY5jsi6yAH3Apdm08kpvsOIdCQVIJF2SqQymwJnAJPQpGYpH88CvwUeyKaTOd9hRIpNBUikjRKpzGDgfOAooNpzHJFieRP4PXBjNp1c4TuMSLGoAIm0Ijwn13kEu7LrJKQSF/OBK4E/Z9PJ+b7DiBSaCpDIGiRSmT7AucCPga6e44j4shL4G5DOppPv+g4jUigqQCLNJFKZnsBZwKlAD89xREpFPcEu9L/MppMLfYcRWV8qQCKhRCrTHTgNOBPY0GsYkdL1GfBLgk1j9b7DiKwrFSCJvUQq04VgM9e5QF/PcUSi4m0glU0n7/IdRGRdqABJbCVSmU4EE5vPAzb2HEckqp4Dzsymk//zHUSkPVSAJHYSqUwlwa7s/w8Y4jmOSLm4k2BESEeWlkhQAZJYSaQy2wL/h05QKlIMmigtkaECJLEQnrbiV8BJQIXnOCLlThOlpeSpAEnZS6QyBwF/BAb6ziISM28DP82mk3f6DiLSnAqQlK1EKjMU+DPBmdpFxJ9ngROy6eQbvoOIrKYCJGUnkcpUAacDtegIziKloh64GLg4m042+A4jogIkZSWRyuwAXA2M9Z1FRFr0OnBMNp183ncQiTcVICkLiVRmQ+DXBMf10SRnkdKWI5iXd342nVzuO4zEkwqQRF4ilTkU+D0wwHcWEWmXd4Djsunkf3wHkfhRAZLISqQyXwOuBPb2nUVE1stfgLOy6eQy30EkPlSAJJISqcxJwG+BLr6ziEhBvA38KJtOPuc7iMSDCpBESiKV6QlcC0z0nUVECi4HXApcoAMoSrGpAElkJFKZCcDtwKa+s4hIUb0GHJFNJ1/zHUTKlwqQlLxEKmPAGQR7eVV7jiMiHaMeuBC4JJtO5nyHkfKjAiQlLZHK9AFuAPbzHEVE/HgK+H42nfzYdxApLypAUrISqcwuwG3AIN9ZRMSrj4CJ2XRyiu8gUj5UgKTkJFKZCuCnwEVApec4IlIa6oGTs+nkX30HkfKgAiQlJZHK9AduAvbynUVEStI1BEVole8gEm0qQFIyEqnMN4Bb0BGdRWTtphBsEvvIdxCJLhUg8S6RylQS7O3xM3QeLxFpm48JJkc/5TuIRJMKkHiVSGUGArcCu/nOIiKR0wicmU0nL/cdRKJHBUi8SaQy44EHgU18ZxGRSLsZOD6bTq7wHUSiQwVIvEikMvsT7OLezXcWESkLrwAHZtPJrO8gEg2abyEdLpHKnAbch8qPiBTOeODFRCqjPUilTTQCJB0mnOx8OXCS7ywiUraagJ9l08nf+A4ipU0FSDpEIpXpAfwd+LbvLCISC7cAk7LpZKPvIFKaVICk6BKpzCAgA4z1nUVEYiUDHKzJ0dISFSApqkQqMxp4BJ3PS0T8eArYP5tOLvYdREqLJkFL0SRSmZ2AZ1D5ERF/vg78J5HK9PUdREqLCpAURbib+6NAL99ZRCT2tgGeSqQyOuaYfE4FSAoukcocA9wLdPGdRUQkNAp4JpHKDPcdREqDCpAUVCKVOZ/gbM2VvrOIiDSTAJ5OpDJb+g4i/mkStBRMIpW5HDjFdw4RkVYsBPbNppP/8x1E/NEIkBREIpX5Iyo/IhINvYBHE6nMnr6DiD8qQLLeEqnMb4Cf+M4hItIO3YCHEqnM93wHET9UgGS9JFKZWuAc3zlERNZBDXBnIpU50ncQ6XgqQLLOEqlMCrjQdw4RkfVQCVyfSGU0ih0zKkCyThKpzKnAr33nEBEpAAP+GP5RJzGhvcCk3RKpzInAVb5ziIgUwXHZdPIa3yGk+FSApF0Sqcwk4DqCv5hERMpNEzAxm07e7zuIFJcKkLRZIpU5FLgFbToVkfK2EvhWNp182ncQKR4VIGmTcFfRO4Aq31lERDrAImDXbDr5uu8gUhwqQNKqRCqzL8G5vTr5ziIi0oHmADtl08n3fAeRwtOmDFmr8Eipd6PyIyLxMxB4JJHK9PEdRApPBUjWKJHKfB24H+jsO4uIiCcjgX8kUpluvoNIYakASYsSqcx44CGgq+8sIiKeTQDuSqQymgNZRlSA5CsSqcxGBCM/PXxnEREpEfsA1yVSGR0CpEyoAMmXJFKZTsA9wGDfWURESswRwKW+Q0hhqABJc1cCO/sOISJSos5MpDJn+w4h60+7wcvnwpMB/tF3DhGREueASdl08m++g8i6UwESABKpzDeBf6IDHYqItEUjsF82nXzEdxBZNypAQiKVGQY8D/T2nUVEJEIWAttl08m3fQeR9tMcoJhLpDI9gAdQ+RERaa9ewD2JVEaHC4kgFaAYS6QyFcCtwGjfWUREImos8FffIaT9VIDi7ZfAfr5DiIhE3A8SqcxpvkNI+2gOUEwlUplDgdt85xARKRONwDez6eRTvoNI26gAxVAildkGeBro4juLiEgZ+RjYJptOfuQ7iLROm8BiJpHKDADuQ+VHRKTQ+hOcM6zadxBpnQpQjCRSmRqC01wM8p1FRKRM7QD8xncIaZ0KULxcCuzoO4SISJk7PZHKfMd3CFk7zQGKiUQqsxfwCKAzGYuIFN9CYKtsOvm+7yDSMhWgGEikMr2AacAmvrOIiMTIf4GvZ9PJRt9B5Ku0CSwe/ozKj4hIR9sRuNh3CGmZRoDKXCKVOQS43XcOEZGYcgQnTf2H7yDyZSpAZSyRygwEXic4X42IiPixABin4wOVFm0CK2/XofIjIuJbH+Bq3yHky0qmAJnZYDN73Mymm9kbZnZq3rLeZvZvM5sd/qtf6q1IpDKTgb195xAREQCSiVTmMN8h5AslswnMzDYGNnbOvWxmPYCXgO8656ab2SXAZ865tJmlgF7OuXO9Bm4nM6tyznXIngCJVGYzYCrQtSNeT0RE2mQ+MCqbTi7wHURKaATIOTfXOfdyeH0JMIMv9lw6ALgxvH4j8N3mjzezzmZ2vZlNM7NXzGyPFtbZ3cyeNLP7zewdM0ub2eFm9nz4uGHhevub2ZTweR41s/5mVhGOQPUL16kws7fMrJ+ZJczsP2b2mpk9ZmZDwnVuMLO/mNkU4JLCfmItS6QylcBNqPyIiJSafsAffIeQQMkUoHxmlgDGA1PCu/o75+aG1+cRnG+luR8Dzjm3JXAYcKOZdW5hvXHAicAo4AhghHNuAnANcEq4zjPADs658QR7UJ3jnMsBNwOHh+vsCbzqnJsP/Am40Tk3FrgFuDzv9QYBOznnzmjHR7A+fgps30GvJSIi7fPDRCqzj+8QUoIFyMy6A3cDpznnFjdf7oJtdi1tt9uFoKDgnJsJvAeMaGG9F8LRplXA28C/wvunAYnw+iDgETObBpwNbBHefx3wo/D60cD14fUdgVvD6zeFWVa70znXtKb3W0iJVGZr4IKOeC0REVlnVydSme6+Q8RdSRUgM6smKD+3OOfuyVv0cThHaPVcoU/W42VW5V3P5d3OAVXh9T8BV4SjSScAnQGccx+EWb4BTAAebsPrLVuPrG2WSGU6ExRAnYVYRKS0DUEHSPSuZAqQmRlwLTDDOfe7ZosfAI4Mrx8J3N/CUzxNuHnKzEYQfIPNWsc4PYHVx2s4stmyawiKRv7IznPAoeH1w8MsHe3XBJv1RESk9P04kcro5NQelUwBAnYmmJPzDTObGl72DZelgb3MbDbB3Jt0C4+/EqgIN1v9HZgUbuZaF7XAnWb2EvBps2UPAN35YvMXBHOHjjKz18L3cCodKJHK7NHRrykiIuulArg2kcrU+A4SVyWzG3xUmNm2wO+dc7v6zgKQSGU6Ecxfamm+k4iIlLZfZNNJzd30oJRGgEpeeAyiuwn2tCoVp6PyIyISValEKrOl7xBxpBGgCEukMpsAMwk2yYmISDQ9D+yYTSdzvoPEiUaAou0yVH5ERKJuAprH2eE0AhRRiVRmd+Bx3zlERKQglgNjsunku76DxIVGgCIokcpUERyrSEREykNXdMb4DqUCFE0nA2N8hxARkYLaK5HKfNt3iLjQJrCISaQy/YDZBAdrFBGR8vIqMD6bTuqXc5FpBCh6LkLlR0SkXI0DfuA7RBxoBChCEqnMKIKDHlb6ziIiIkXzLrB5Np2s9x2knGkEKFouReVHRKTcbUpwIm4pIo0ARUQilfkm8KjvHCIi0iE+AYZl08mlvoOUK40ARUAilakgOOihiIjEw0bAmb5DlDMVoGg4kmBinIiIxMeZ4Z6/UgQqQCUukcp0A37pO4eIiHS4HsDPfIcoVypApe8UYKDvECIi4sXkRCqT8B2iHKkAlbBEKtMZOM13DhER8aYT8HPfIcqRClBpOxro7zuEiIh4dXgildnSd4hyowJUosITnp7tO4eIiHhXAfzad4hyowJUug4FEr5DiIhISUgmUpldfYcoJypAJSiRyhhwru8cIiJSUn7jO0A5UQEqTfsBY3yHEBGRkrJjIpXZ13eIcqECVJp+6juAiIiUpNN8BygXOhdYiUmkMrsBT/jOISIiJWuLbDo53XeIqNMIUOnR6I+IiKzNT3wHKAcaASohiVRmPPCy7xwiIlLSlgODsunkQt9BokwjQKUl5TuAiIiUvK7Acb5DRJ1GgEpEIpXZDJiJSqmIiLTufeBr2XSyyXeQqNIv29JxDvp6iIhI2wwBvuc7RJTpF24JSKQyA4Ef+c4hIiKRcqrvAFGmAlQaziA446+IiEhb7ZJIZbb2HSKqVIA8S6Qy3YETfOcQEZFI0ijQOlIB8u9goLvvECIiEkmHJlKZ/r5DRJEKkH+TfAcQEZHI6gRM9h0iirQbvEeJVOZrwFuA+c4iIiKR9TEwJJtO1vsOEiUaAfLrSFR+RERk/fQHDvUdImpUgDxJpDKGdn0XEZHC0GTodlIB8md3IOE5g4iIlIetE6nMzr5DRIkKkD+TfAcQEZGycqTvAFGiSdAehMf+mQd0851FRETKxkJggCZDt41GgPz4Pio/IiJSWL2AfX2HiAoVID8m+Q4gIiJl6XDfAaJCm8A6WCKVGQbMRru/i4hI4a0E+mfTycW+g5Q6jQB1PB37R0REiqUzMNF3iChQAepAOvaPiIh0AG0GawMVoI61BzDUdwgRESlreyRSmYG+Q5S6Kt8BYmaS7wBRt/iF+1j66r/AoLpfgr77nsaCf11F/bzZAFT3Gkif5OlUdOrypcetmjOLBY9cEdxwjg13+QFdR+wEQG7lUhY8fDn1n74PQN99T6Vmk1Ed96ZERAqrAjgY+KPvIKVMk6A7iI79s/4al3zKvFvOZeAxV1JRXcP8+9J0GbYtXUfsREVNVwA+e+yvVHbbkJ47HPylx+YaVmKV1VhFJY1LP2Pu9acw6Md/wyoq+TTzO2oGbUGPcXvjmhpwDauo6Nzdx1sUESmUp7Pp5Nd9hyhl2gTWcb6Nys/6yzXhGutxuSZc4yoqu/f+vPw453CN9bQ0x7yiujNWURmsl7dObtUyVn7wBt3HfgsAq6xW+RGRcrBzIpXp7ztEKdMmsI7zbd8Boq6qR182mPA9PrrqKKyqE503HU+XTbcG4NPMH1jxzotU9x1Mr28c0+LjV82ZxYJ//JHGxZ/Qd78zsIpKGhZ9TGXXDVjwjz9Q/8m71AwYTq9vHk9Fp84d+dZERAqtAvge8BffQUqVRoA6QLj31z6+c0Rd08qlLJ89hU1OvJZBP/4brmEVS994HIC+ydMY9OMbqe4zmOUznm7x8TUDRzLw2CvZ+Ee/p+5/d34+klQ/7216jN+XgUddjlXXsPh/d3bk2xIRKRbtDr8WKkAdYxywse8QUbcyO5Wqnv2p7NoTq6yi64gdWfXRjM+XW0Ul3UZ9neVvPrfW56nuOxir7kL9/Peo6tGXyh59qRk4EoCuI3em/uO3i/o+REQ6yO6JVKa37xClSgWoY2jzVwFUbdCP+jmzyDWsxDnHyvdepbrPYBoWzgGCOUArZk+huvegrzy2YdE8XK4JgMa6T2j87EOqem5EZfdeVG3Ql4YFHwIEz9l3SMe9KRGR4qkCDvAdolRpDlDH0OavAqgZOJKuI3dm7g2nYRUVdOo/jB7j9uHj288jt2o54KjeaFP6fOvHACyfPYX6ebPZcNcfsurD6cz/311QWYlZBb33mkxl154A9N7zRD596Le4pkaqNhxAn31P8/cmRUQKayJwve8QpUi7wRdZIpXpCXyKyqaIiHS8eqBPNp1c6jtIqdEmsOLbE5UfERHxoxOwq+8QpUgFqPg0/0dERHza3XeAUqQCVHya/yMiIj7t7jtAKdIcoCJKpDJbAq/5ziEiIrHWCPTOppNLfAcpJRoBKi5t/hIREd+qgF18hyg1KkDFpQIkIiKlYHffAUqNClCRJFKZHsDOvnOIiIigAvQVKkDFsydQ7TuEiIgIsHX4h7mEVICKR3t/iYhIqdA8oGZUgIpH839ERKSU7O47QClRASqCRCozDBjsO4eIiEie3X0HKCUqQMWxve8AIiIizWgeUB4VoOKY4DuAiIhIM1XovGCfUwEqDo0AiYhIKdrdd4BSoQJUYIlUphrYyncOERGRFuzuO0CpaHMBMrNqM/uJmd0VXk4xMx3n5qvGAp19hxAREWmB5gGF2jMCdBWwDXBleNk6vE++TJu/RESkVFWi4wEBwYSottrOOTcu7/Z/zOzVQgcqA5oALSIipWxr4GHfIXxrzwhQk5kNW33DzL4GNBU+UuRt5zuAiIjIWoz2HaAUtGcE6GzgcTN7BzBgKHBUUVJFVCKV6Qps7juHiIjIWmzhO0ApMOdc21c2qwFGhjdnOedWFSVVRCVSmQnAFN85RERE1mIl0C2bTuZ8B/GpzSNAZtYZOIlg8pQDnjazvzjnVhYrXASNa30VERERrzoDXwPe8h3Ep/bMAfobwbDZn4Arwus3FSNUhKkAiYhIFMR+M1h75gCNcc7lT5x63MymFzpQxKkAiYhIFIwG7vcdwqf2jAC9bGY7rL5hZtsDLxY+UjQlUhkjOAiiiIhIqYv9nmDtGQHaBnjOzN4Pbw8BZpnZNMA55+L+yz8BbOA7hIiISBtoE1g71t2naCnKgzZ/iYhIVGyeSGUq4rwnWHsKUIv7yzvn3m/p/hja0ncAERGRNupCsOXiHc85vGlPAcoQlCAj2IVuU2AWGkZbbVPfAURERNphC1SAWuec+9IIh5ltTXBcIAkM9h1ARESkHUYDD/oO4Ut79gL7Eufcy+jM5/lUgEREJEpivSdYe44EfUbezQqCs8nOKXii6FIBEhGRKIn1FJb2jAD1yLvUEMwJOqAYoaImkcr0Brr6ziEiItIOm4fHsIulNo0AmVkl0MM5d1aR80TVEN8BRERE2qkbMBTIes7hRZtGgJxzTcDORc4SZdr8JSIiUTTCdwBf2rMb/FQzewC4E1i2+k7n3D0FTxU9KkAiIhJFG/kO4Et7ClBnYAHwjbz7HKACpAIkIiLR1M93AF/acxygo4oZJOJUgEREJIpUgFpjZpe3cHcd8KJz7v7CRYokTYIWEZEoim0Bas9u8J2BrYDZ4WUsMAg4xsz+UPBk0aIRIBERiaLYFqD2zAEaC+wc7hGGmV0FPA3sAkwrQrZISKQyFcAmvnOIiIisg9gWoPaMAPUCuufd7gb0DgvRqoKmipb+QLXvECIiIusgtgWoPSNAlxDsCv8EwRnhvw5cbGbdgEeLkC0qtPlLRESiKrYFyJxzbV/ZbGNgQnjzBefcnLxlWzjn3ihwvpKXSGUmAnf5ziEiIrKOOmXTyQbfITpae0aAcM7NBda0x9dNBCdIjRvtASYiIlHWF5jrO0RHa88coNbE9YRqsT2KpoiIlIVYbgYrZAFq+7a08qKzwIuISJSpAMk66ew7gIiIyHpQAVpP9QV8rihRARIRkShTAVobC/zQzC4Ibw8xs9V7hOGc26EYASNABUhERKJMBagVVwI7AoeFt5cAfy54ouhRARIRkSiLZQFqz27w2zvntjazVwCccwvNrFORckWJCpCIiERZLAtQe0aAGsysknBvLzPrB+SKkipaVIBERCTKNvAdwIf2FKDLgXuBjczsV8AzwMVFSRUtKkAiIhJllb4D+NCmTWBmVgG8C5wDfJPgoIffdc7NKGK2qOjiO4CIiMh6aNdZIcpFm960cy5nZn92zo0HZhY5U9RoBEhERKIslgWoPZvAHjOziWYW11NerIkKkIiIRFksN4G1pwCdANwJrDKzxWa2xMwWFylXlKgAiYhIlMVyBKjNb9o516OYQSJMBUhERKIsliNArRYgM9t6bcudcy8XLk4kqQCJiEiUaQRoDS4L/+0MbAu8SrAX2FjgRYKjQ8dSIpWpAKp95xAREVkPKkAtcc7tAWBm9wBbO+emhbfHALVFTVf6NPojUmTfr3z8+Uuq/zqh9TVFZN3V+Q7Q4dozCXrk6vID4Jx7HRhV+EiRogIkUmR3NO0x4RPX8yXfOUTKWJPvAD60pwC9ZmbXmNnu4eWvwGvFChYROhWISAeYVH/uhs7R6DuHSJlSAWrFUcAbwKnhZXp4X5wt8R1AJA6mu8SwKW7Uc75ziJSpWBYgc875zhBpiVRmOTodhkjRbcDSuqk1JzRWmOvjO4tImXmR2rrtfIfoaG0eATKzzczsLjObbmbvrL4UM1xEaBRIpAMspnvPq5v2m+47h0gZiuV0jvZsArseuApoBPYA/gbcXIxQEaMCJNJBLmk8ZOflrtMs3zlEykwsN4G1pwB1cc49RrDZ7D3nXC2QLE6sSFnqO4BIXDgqKk5pOGWF7xwiZWal7wA+tKcArTKzCmC2mZ1sZt8DuhcpV5RoBEikAz2W22arbK7//3znECkjC30H8KE9BehUoCvwE2Ab4AjgyGKEihgVIJEO9qOG1CDn0EiQSGGoAK2Nc+4F59xS59yHzrmjnHMHOuf0V5gKkEiHe9/1H/TP3HbP+84hUiYW+Q7gQ3v2AtvWzO41s5fN7LXVl2KGiwgVIBEPzmg4abtGVzHXdw6RMqARoFbcQrAn2ERg/7xL3KkAiXiwgpquv2k87F3fOUTKgApQK+Y75x5wzr0b7gX2nnPuvaIliw7tBSbiyV+bkjstct00Ei2yflSAWnFheC6ww8zswNWXoiWLDo0AiXh0bP1Z1c7F80BuIgUSywJU1Y51jwI2B6r54qiRDrin0KEiRgVIxKMX3chRr7tNn9nS3t3FdxaRiFIBasV2zrmRRUsSXSpAIp4dVX/2yBdqTlpsxga+s4hE0CLfAXxozyaw58xsdNGSRJcKkIhnn7Jhv9uavvGK7xwiERXLEaD2FKAdgKlmNivcBX6adoMHVIBESsIFjZN2qndV2itMpP1iWYDaswlsn7UtNLNezrk4fogqQCIloJGq6nMbjvv0952u2tR3FpEIWUZtXYPvED6050jQ77V0yVvlsSLkiwIdiE2kRNyb23W7ea7Xi75ziERIHAcugPZtAmuNFfC5omQOEMv2LFKKjqw/t49z+pkUaaNPfQfwpZAFyBXwuSIjm07mgI985xCRwCw3ZNNncmOe851DJCJiO2+ukAUoznREbJESclLDqVvlnM33nUMkAlSACiCum8AA3vcdQES+sIRuPf/cdMBM3zlEIuAd3wF8abUAmVnvtV3yVv1mEXOWOo0AiZSY3zUetPMyVzPDdw6REqcCtBYvAS+G/84H3gRmh9dfWr2Sc+6zYgSMCI0AiZQYR0XFjxtO1WRokbVTAVoT59ymzrmvAY8C+zvn+jrn+gD7Af8qdsCI0AiQSAl6IrfV2LdyG2tCtEjLHJD1HcKXdh0J2jn3j9U3nHMPAzsVPlIkqQCJlKhJDamEcyz3nUOkBM2htm6V7xC+tKcAzTGz880sEV5+RnAMHAlm0Tf5DiEiX/Wh6zfwodwOz/vOIVKCYrv5C9pXgA4D+gH3hpeNwvtiL5tO1qN5QCIl6+yGE7ZvdBUf+s4hUmJUgNrCOfeZc+5U59z48HJqzCc+N/em7wAi0rKV1HT5ReMPP/CdQ6TExPYYQNCOAmRm/czsUjP7h5n9Z/WlmOEiZrbvACKyZjc27bPjQtd9qu8cIiVEI0BtdAswE9gUuIhg5vgLRcgUVRoBEilxR9Wf08U5cr5ziJQIFaA26uOcuxZocM496Zw7GvhGkXJFkUaARErcVDd85FQ37BnfOURKhApQG60+oNhcM0ua2Xig99oeEDMaARKJgGPqz9rCOep85xDxbCkwz3cIn9pTgH5pZj2BM4GzgGuA04uSKpreA+p9hxCRtfuMnn3+1vStqb5ziHg2ldo65zuET+ZcrN9/QSVSmdeBLXznEJG1q6SpcXrN0e/VWMMw31lEPPkjtXWn+Q7hU1VrK5jZnwgOl90i59xPCpoo2p5HBUik5DVRWXVmw4mLruj0J99RRHx5qfVVyltbNoGtPhFqZ2Brgsm+s4GtgE5FSxZNU3wHEJG2eSi34zYfuT46QrTEVewLUKsjQM65GwHMbDKwi3OuMbz9F+Dp4saLnP/5DiAibfej+lT/RzudXW+mP+YkVpYTHNYm1tozCboXsEHe7e7hffKF14FlvkOISNu87TYZ+kRunM4WL3Ezldq62B8Pqz0FKA28bGY3mNmNwMvAxcWJFU3ZdLKJYJOhiETEyQ0/2abJ2Se+c4h0oNhv/oL2FaAbgAuAscDdwG7AjCJkijptBhOJkGV06fHHxok6jpfEiQoQ7StAVwLbA12ccw8AS4A/FyVVtGkitEjEXN70vZ2Xus7TfecQ6SAqQLSvAG3vnPsxsBLAObcQ7QXWEo0AiUSO2QkNZ+ScW/MhP0TKxHK09QZo56kwzKyS8JhAZtYPdFLB5rLp5Fzgfd85RKR9ns2NGfOmG6QJ0VLuXqW2rsl3iFLQngJ0OXAvsJGZ/Qp4Bk2CXhNtBhOJoEn15w5zTntySll72XeAUtHmAuScuwU4B/g1MBf4rnPuzmIFizhtBhOJoLn0GXBvbpcXfOcQKSLN/wm1eiDEfM65mejgSW2hAiQSUamG43bcv+K/H1Rb02DfWUSKQFsoQu3ZBCZt9zLQ4DuEiLRfPdU1tY1HzvGdQ6QI5lJbp70dQypARZBNJ1cCr/rOISLr5pamPbdf4Hq84juHSIE96jtAKVEBKh4NM4pE2KT6c7s7h/aWkXKiApRHBah4NA9IJMKmua9t9qIb8azvHCIFpAKURwWoeP7rO4CIrJ/j6s/cMudY6DuHSAFMp7ZOc9vyqAAVSTadfBt4x3cOEVl3i+jR67qmb0/znUOkAP7tO0CpUQEqrgd9BxCR9XNx4+E7r3TVs33nEFlP2vzVjApQcT3gO4CIrJ8cFZWnNvx4qe8cIuuhAXjCd4hSowJUXE8Bi3yHEJH180huwvj3c/20Y4NE1RRq61Tim1EBKqJsOtkIPOw7h4isvx81pDZxjlW+c4isA83/aYEKUPFpM5hIGci6jQc/mts69nt3Hn3/Cja6dAljrvzygMKfptSz+RVL2eLKpZzz75UtPnbRSsdBdyxn8yuWMurPS/nvB41fWn7Zc6uwixbz6fJc0fLHlOb/tKBd5wKTdfIwwfbXat9BRGT9nNpw8nbTKo6ZV2lugO8svkzaqpqTJ3TiR/eu+Py+x99t5P5ZDbx6YjdqqoxPlrVcYE7950r2GV7FXd/vRH2TY3neCYM+qMvxr3caGdLTiv0W4mYx8LzvEKVII0BFlk0n6wjmAolIxC2nc7ffNn7/bd85fPr60Cp6d/lySbnqxXpSu9RQUxXcv1G3r/5qqVvpeOq9Ro4ZH/wt2KnS2LDzF89z+iMruWTPzqj+FNwT1NY1tr5a/KgAdQxtBhMpE1c1fWenxa7L675zlJI3F+R4+r1Gtr9mKbvdsIwXPvrqGUTeXZSjX1fjqPtXMv7qpRz7wAqW1TsA7p/ZwCY9Khg3oLKjo8eBfv+sgQpQx9A3oEjZMDuu/swK53C+k5SKxhx8tsLxv2O6celenfn+Xctxzn1lnZfn5pi8bTWvnNCdbtVG+plVLG9wXPzMKn6+R42n9GWtAbjXd4hSpQLUAbLpZBbQ0WRFysQUN3r0DDdE5wkLDdrAOHBUNWbGhE0qqTD4dLn7yjqDNjC2HxRMPT1odBUvz8vx9mc53l3oGPeXpST+sIQPFzu2vnoZ85ZqInQBPEpt3We+Q5QqFaCOo1EgkTJyVP05I5xjie8cpeC7m1fzeDaYZvLmgibqm6Bv1y/P5hnQvYLBPSuY9WmweeyxdxsZ3beCLftX8snZPcieFlwGbWC8fEI3BnTXr6cC+LvvAKVM32EdRwVIpIx8TO+N7mza7WXfOTraYXcvZ8drlzFrQY5Bv1vCtS/Xc/T4at5Z6Bhz5VIOvWsFN363C2bGnCU59r1l+eeP/dO3O3P4PSsYe9VSps7Lcd6u2uxVRPXAfb5DlDJrvp1WiiORyhjwEbCx7ywiUhjVNNa/UXPU3E7WNNR3FpFmHqS27ju+Q5QyjQB1kGw66YCHfOcQkcJpoKrT+Y1Hf+w7h0gLtPmrFSpAHUubwUTKzB1Ne0z4xPV8yXcOkTwr0e+bVqkAdaxHgWW+Q4hIYR1Zn9rQOXSwOSkVD1Nbpwn6rVAB6kDZdHIlcJfvHCJSWDPc0GFT3KjnfOcQCWnzVxuoAHW8v/oOICKFd3z96eNyzhb4ziGxtxzNN20TFaAOlk0nnwWm+84hIoW1mO49r27aTz/b4luG2jpNtWgDFSA/NAokUoYuaTxk5+Wu0yzfOSTWtPmrjVSA/PgbsMp3CBEpLEdFxSkNp6zwnUNiqw74h+8QUaEC5EE2nfwMuNt3DhEpvMdy22z1bq7/f33nkFj6G7V1KuBtpALkz//5DiAixXFkQ2qwc+gXkXS0K30HiBIVIE+y6eSTwJu+c4hI4b3v+g/6Z267533nkFh5nNq6mb5DRIkKkF+aDC1Sps5oOGm7Rlcxx3cOiQ2N/rSTCpBfNxKcsVdEyswKarqmGw/L+s4hsTAHnfm93VSAPMqmk/PRN61I2bqmKbnTItftNd85pOxdQ22dTsXSTipA/mkzmEgZO7b+rGrnyPnOIWWrEe1Us05UgPx7DHjHdwgRKY4X3chRr7tNdZ4wKZYHqK37yHeIKFIB8iybTjrgGt85RKR4jqo/e6Rz1PnOIWVJk5/XkQpQabieYBhTRMrQp2zY79amb0z1nUPKzizgP75DRJUKUAnIppPzgAd95xCR4rmwcdJOq1zVu75zSFn5C7V1zneIqFIBKh0axhQpY41UVacajlvgO4eUjeXADb5DRJkKUInIppOPAi/6ziEixXNvbtdt57le+jmXQriF2rpFvkNEmQpQabnYdwARKa4j68/t4xwNvnNIpDUBv/EdIupUgErLfcB03yFEpHhmuSGbPpMbo93iZX3cSm3d275DRJ0KUAkJd4lP+84hIsV1UsOpW+WczfedQyIpB/zSd4hyoAJUem4DtKeISBlbQreeVzQdMMt3Domkv1Nb96bvEOVABajEZNPJRuAS3zlEpLh+33jQTstczQzfOSRSNPpTQCpApel6YK7vECJSPI6KiskNp2kytLTH3dTWaZ5ogagAlaBsOrkKuNR3DhEprqdy48a+ldtYE6KlLRzwC98hyokKUOn6CxoFEil7R9anNnWO5b5zSMm7j9q6ab5DlBMVoBKVTSdXoOMCiZS9j+i38YO5HV/wnUNK3s99Byg3KkCl7a/AB75DiEhxndNw/IRGV/Gh7xxSsh6ktm6q7xDlRgWohIVzgTTjX6TMraSmyy8aj1ABkjXR3J8iUAEqfdej4wKJlL0bm/beYaHrPtV3Dik5/6S2TptIi0AFqMRl08kGtO1XJBaOqj+ni3M0+c4hJcMBF/oOUa5UgKLhJkBH/hQpc1Pd8JFT3XDtFi+r3U5t3fO+Q5QrFaAIyKaTTcD5vnOISPEdU3/maOeo851DvFsJpHyHKGcqQBGRTSfvBB7znUNEiuszeva5selbr/rOId79ntq6932HKGcqQNFyMqBD54uUuV80HrHTKlf9tu8c4s3HwK99hyh3KkARkk0nZwK/951DRIqricqqMxtOXOQ7h3hzIbV1S3yHKHcqQNHzc0DHCxEpcw/ldtzmI9dHE2Dj53XgGt8h4kAFKGKy6eQy4AzfOUSk+H5Un+rvHPW+c0iHOoXaOh0KoQOoAEVQOCH6375ziEhxve02GfpEbtx/feeQDvN3auue8B0iLlSAousU0F+GIuXu5IafbN3k7BPfOaTolgFn+Q4RJypAEZVNJ2cBv/OdQ0SKaxldevyxcaIOhFr+Lqa2TvM7O5AKULT9Ep0tXqTsXd70vZ2Xus7TfeeQonkLuMx3iLhRAYowTYgWiQuzExrOyDmH851EiuJUautWFevJzcyZ2c15t6vMbL6ZPVSs11xXZna4mb1mZtPM7DkzG5e3bB8zm2Vmb5nZeh8lWwUo4rLp5F3Av3znEJHiejY3ZsybbpDOE1Z+bqG27h9Ffo1lwBgz6xLe3gv4qMiviZlVrsPD3gV2c85tCfwC+L+85/oz8G1gNHCYmY1en3wqQOVBE6JFYmBS/bnDnGOp7xxSMPOAn3TQa/0DSIbXDwNuW73AzLqZ2XVm9ryZvWJmB4T3TzKze8zsn2Y228wuyXvMYeEozetm9pu8+5ea2WVm9iqwY34AMzvOzF4ws1fN7G4z69o8pHPuOefcwvDm/4BB4fUJwFvOuXecc/XA7cAB6/OBqACVgWw6+SbafixS9ubSZ8C9uV1e8p1DCuZEaus+66DXuh041Mw6A2OBKXnLfgb8xzk3AdgDuNTMuoXLtgIOAbYEDjGzwWY2EPgN8I1w+XZm9t1w/W7AFOfcOOfcM80y3OOc2845Nw6YARzTSuZjgIfD65vw5TmvH4b3rTMVoPLxS0AnzhMpc6mG43ZocJXa+SH6bqG27v6OejHn3GtAgmD0p/kmt28BKTObCjwBdAaGhMsec87VOedWAtOBocB2wBPOufnOuUbgFuDr4fpNwN1riDHGzJ42s2nA4cAWa8prZnsQFKBz2/E220UFqExk08nldNxQqoh4Uk91zYWNRxZ9/oYUVUdu+sr3APBb8jZ/hQyY6JzbKrwMcc7NCJflT85uAqpaeY2Vzrk1Hcn6BuDkcH7PRQRF6yvMbCzB6UAOcM4tCO/+CBict9og1nMekwpQGcmmk/cD1/nOISLFdWvTnjt86jZ42XcOWWcndOCmr3zXARc556Y1u/8R4BQzMwAzG9/K8zwP7GZmfcPJyYcBT7bh9XsAc82smmAE6CvMbAhwD3CEcy7/+FcvAJuZ2aZm1gk4lKDQrTMVoPLzE0AHTRMpc0fVn9PDOXTOqOi5hdq69frFva6ccx865y5vYdEvgGrgNTN7I7y9tueZC6SAx4FXgZecc23ZnPf/COYePQvMXMM6FwB9gCvNbKqZvRi+ZiNwMkFZmwHc4Zx7ow2vuUbmnA4rUW4SqczWwH+BTr6ziEjx3Nnpoqe2q5j19dbXlBIxD9jC0+iPNKMRoDKUTSdfBs73nUNEiuu4+jO2zDkWtr6mlAhfm76kBSpA5eu3wKO+Q4hI8SyiR6/rmvZtPp9DStPNvjZ9Scu0CayMJVKZjYHXgL6+s4hIcVSQa5pec9Q7na1hM99ZZI3mAaOprdNoXQnRCFAZy6aTc4GjfecQkeLJUVF5asOPdXTo0nacyk/pUQEqc9l08kHgSt85RKR4HslNGP9+rt+U1tcUD35LbV3JnXRUVIDi4kxgvXYXFJHS9qOG1EDnKNoZxWWdPA381HcIaZkKUAxk08mVBAeqWuk7i4gUR9ZtPPjR3Nb/9Z1DPvcxcAi1dY2+g0jLNAk6RhKpzClASwfBEpEy0JWVy6bVHLOk0twA31lirgn4FrV1//EdRNZMI0Axkk0n/wRkfOcQkeJYTudulzYe8rbvHMKFKj+lTwUofo4i2CVTRMrQX5r232mx66pjA/mTAS72HUJapwIUM9l0cj5wJKBtnyJlyey4+jMqndPPuAdZ4Ahq6/TZR4AKUAxl08l/ARf6ziEixTHFjR493Q191neOmKkHDtbxfqJDBSimsunkL4CbfOcQkeI4uv7sEc6xxHeOGDmd2roXfYeQtlMBirdjCY5TISJl5mN6b3RH024v+c4RE7dSW6cDzkaMdoOPuUQq0weYAgzznUVECquaxvo3ao6a28mahvrOUsamAxOorVvmO4i0j0aAYi6bTi4AksAiz1FEpMAaqOr0s8ZjPvado4x9Auyn8hNNKkBCNp2cBUwEGnxnEZHCurNp9wmfuA01N6XwlhOUn3d9B5F1owIkAGTTyf8Ak33nEJHCO7L+3F7OoVMyFE4TcCi1dS/4DiLrTgVIPpdNJ68FLvWdQ0QKa4YbOux/uVHaLb5wfkJt3YO+Q8j6UQGS5s4F7vUdQkQK64SG07fKOVvgO0cZuFR7fJUHFSD5kmw66YAfApozIFJGFtO959VN+73hO0fE/Z3gj0QpA9oNXlqUSGU2Jtg9frDvLCJSGEYu90bN0bO7Wv1I31ki6GlgL2rrVvkOIoWhESBpUTadnAvsDyz1nUVECsNRUXFKwykrfOeIoJnAASo/5UUFSNYom06+ChxKsMeDiJSBx3LbbPVurv9/feeIkI+BfXWOr/KjAiRrlU0nM8BpvnOISOEc2ZAa7BwaCWqdjvVTxlSApFXZdPIKIOU7h4gUxvuu/6CHcxOm+M5R4hqA7+sEp+VLk6ClzRKpzAXARb5ziMj668Kq5dNqjllUZbmBvrOUoAbgYGrr7vcdRIpHI0DSZtl08ufAL33nEJH1t4KarunGw7K+c5Sg1SM/Kj9lTiNA0m6JVOYS4GzfOURk/U2tOe61DW3ZWN85SsTq8nOf7yBSfBoBknbLppPnAH/0nUNE1t+x9WdVO0fOd44S0AAcovITHypAsk6y6eRpgA4HLxJxL7qRo6a5TeN+nrAGgpOb6jRAMaICJOvjZOAK3yFEZP0cXX/25s5R5zuHJ40E5ece30GkY6kAyTrLppMum06eAlzmO4uIrLtP2bDfLU3fnOo7hweNBJu9VH5iSJOgpSASqcyvgPN85xCRdVNFY8MbNUd/WGONm/rO0kFWj/zc7TuI+KERICmIbDr5M+AC3zlEZN00UlWdajhuge8cHUTlR1SApHCy6eQvgHN95xCRdXNvbtdt57leL/jOUWSrUPkRVICkwLLp5CXo3GEikfWj+lRf52jwnaNIFgLfUvkRUAGSIsimk38EJgH1nqOISDu96QZv+kxuy+d85yiC94Cdqa17yncQKQ2aBC1Fk0hlvg7cA/TxnUVE2q47yxe/VnPcqgpz/XxnKZBXgCS1dXN9B5HSoREgKZpsOvkUsAMwy3cWEWm7pXTd4IqmA8rl5/afwNdVfqQ5jQBJ0SVSmQ2Bu4Bveo4iIm1k5HKv1xwzq5utGuU7y3q4FjiR2rpG30Gk9GgESIoum04uAvYB/uo5ioi0kaOiYnLDaVGeDH0htXXHqvzImmgESDpUIpU5A7gUlW+RSHi001nPDa+Ys5PvHO3QABxPbd0NvoNIaVMBkg6XSGW+A9wKdPOdRUTWbhPmz32m5tSeZnT1naUNlgATqa37t+8gUvr0V7h0uGw6+QCwC/Ch7ywisnYf0W/jB3M7RuHgiHOAXVV+pK00AiTeJFKZjYEHgG19ZxGRNevMqhWv1xyzoMpyg3xnWYMnCY7uPM93EIkOjQCJN9l0ci6wG6CjsoqUsJXUdPlF4xGlOGLrgN8A31T5kfbSCJB4l0hlDLgYSPnOIiJr9nLNCVN725KtfOcI1QFHUlt3v+8gEk0qQFIyEqnMkcBVQBffWUTkq7ayt2bd2+mC4WZUeo4yFTiI2rq3PeeQCNMmMCkZ2XTyRoL5QK/5ziIiXzXVDR/5ihv+rOcY1wE7qvzI+tIIkJScRCpTA6SBUwHzHEdE8vSmbsGLNZMrK4wNO/ilVwInU1t3bQe/rpQpFSApWYlUZm/gBmCA5ygikqe26oanJlX96+sd+JLvEGzyeqUDX1PKnAqQlLREKtOPYMh7P99ZRCRQSVPjGzVHv9fZGoZ1wMs9QDDZeVEHvJbEiOYASUnLppPzs+nk/sCPgRW+84gINFFZdVbDiYuK/DL1wLnAd1V+pBg0AiSRkUhlRgO3AWN9ZxEReLbmlOc3sQUTivDULxOM+rxehOcWATQCJBGSTSenAxOAPxAcAE1EPDqi/qf9naO+gE/ZAFwAbK/yI8WmESCJJE2QFikN11f/5sk9Kl/drQBPNRWYRG3dqwV4LpFWqQBJZGmCtIh/3Vix5LWaY1dUmttoHZ+ikeBI8L+ktq6hgNFE1koFSCIvkcqcBPwWHUFaxItTKu959szqu3Zeh4dOIxj1ebnQmURaowIkZSGRygwD/ggkfWcRiR/nptUcO72HrdiijQ9oIjiJ6UXU1hVyDpFIm6kASVlJpDL7ExShTX1nEYmTnStef/3m6ou3MGv16O1vEIz6vNgRuUTWRHuBSVnJppMPAqOBWoJD54tIB3g2N2bMm27Qc2tZpR74FbCNyo+UAo0ASdlKpDKbEuwy/x3PUURiYWMWzHuu5pTuZnRvtuhh4FRq62b7yCXSEhUgKXuJVGZf4HKgIw7bLxJrv6u+8skDK59ZvVv8O8Dp1NY94DOTSEtUgCQWwjPMnw2ch/YWEymaTjSsmlZzzHs11ngLcAm1ddoULSVJBUhiJZHKDAV+D3zPdxaRMuSA2zdi4bnPp3/4ge8wImujAiSxFB5J+nJghO8sImXiOeCMbDo5xXcQkbZQAZLYSqQynYAzgPOBbp7jiETVu0Aqm07e4TuISHuoAEnsJVKZTQjmBh0LdPIcRyQq6gh2a788m06u8h1GpL1UgERCiVRmCMFo0CSg2m8akZK1HPgr8MtsOvmp7zAi60oFSKSZ8PhBFwBHAJWe44iUikXAn4E/ZtPJ+Z6ziKw3FSCRNUikMpsRFKEfoKOmS3x9TLDn5FXZdHKx7zAihaICJNKKRCozEkgBh6NNYxIf7wGXAtdm00kdy0fKjgqQSBuFc4TOIpgsrYMpSrmaAaSBW7PpZKPvMCLFogIk0k6JVKYfcBrwY6Cn3zQiBfMC8Gvgvmw6qV8MUvZUgETWUSKV2QCYDJwO9PccR2RdPQ5cnE0nH/UdRKQjqQCJrKfwgIrfA44DvgGY30QirXLAg8Cvs+nk/3yHEfFBBUikgBKpzNeAY4CjgI09xxFpbi5wE3B9Np2c6TuMiE8qQCJFkEhlqoAkwYTpb6PjCYk/9cADwPXAI9l0sslzHpGSoAIkUmThqTaODi8Jv2kkRl4hKD23ZtPJBb7DiJQaFSCRDpJIZSqAPQnmCh2AjikkhfcpcDPBJq7XfIcRKWUqQCIehLvSH0mwiWyk5zgSbY3AwwSjPQ9l08kGz3lEIkEFSMSzRCqzK/BDYD9goOc4Eh1vADcAN2XTyY89ZxGJHBUgkRKRSGUM2AbYP7yM95tIStAbBKM9d2TTyRd8hxGJMhUgkRKVSGUGEYwKfYfg+EI1fhOJB8uAx4B/AA9n08n3PecRKRsqQCIRkEhlugF7EYwM7Qds5DeRFNFMglGefwBPZdPJes95RMqSCpBIxIR7k03gi01lW/pNJOtpOcHpKFaP8rzrOY9ILKgAiURcIpVJEIwK7QVsj85LFgWz+WKU58lsOrnScx6R2FEBEikziVRmKEERWn3ZGujiNVS85YAZwJTw8p9sOvmW30giogIkUubC03KM5culaCQ6aWuxzOOLsjMFeDGbTi72G0lEmlMBEomhRCqzIbAdwVyi1aVIE6vb7z1gKvBq+O9L2lNLJBpUgEQE+Hwu0XbA5sBmeZc+HmOVioXAu8BrBEVnKvBqNp1c5C+SiKwPFSARWatEKtMLGM4XhWg4MCS8bEL0z2lWD3wIvN/C5QPg/Ww6udRfPBEpBhUgEVln4S75A/iiEA0O/x0A9AC6h5f8690o/vwjB6wEVoSXeayh3ADzsumk/iMUiRkVIBHpUOEpP7rScjnq3ux+44sSs/qyspXbK7Lp5KqOe0ciEkUqQCIiIhI7Fb4DiIiIiHQ0FSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiR0VIBEREYkdFSARERGJHRUgERERiZ3/D9fpGpYe92oKAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<Figure size 720x720 with 1 Axes>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "etiquetas= [\"20 o mayor\", \"Menor a 20\"]\n",
+ "nac_sofia_rango_edad.plot(kind='pie', y='nacimientos_cantidad', figsize=(10, 10),autopct='%.2f',title = \"Proporción de madres tuvo hijos antes de los 20\",labels=etiquetas)\n",
+ "\n",
+ "plt.legend([\"20 o mayor\", \"Menor a 20\"])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "Gyor1fguGMyw"
+ },
+ "source": [
+ "Luego agrupamos los nacimientos en dos categorÃas, basado en si cumple o no la condición: Si está en los grupos \" Menor de 15\" o \"15 a 19\", ponerlos en un grupo, sino en otro grupo. (la | es el equivalente a un \"o\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "metadata": {
+ "id": "KzbpAR3kGMPo"
+ },
+ "outputs": [],
+ "source": [
+ "nac_madre_menor_20 = nac_madre_menor_20.groupby(\n",
+ " (nac_madre_menor_20.edad_madre_grupo == \" Menor de 15\") \n",
+ " | (nac_madre_menor_20.edad_madre_grupo == \"15 a 19\"))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "a-9-o4q3MGjm"
+ },
+ "source": [
+ "Luego sumamos los nacimientos de cada grupo:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 143
},
+ "id": "3HFy7OavMCJU",
+ "outputId": "a9c476c6-c382-4746-958e-d08e03c0facd"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Primero obtenemos la información necesaria para responder la pregunta, esta está en las columnas: instruccion_madre , edad_madre_grupo y nacimientos_cantidad"
- ],
- "metadata": {
- "id": "g7S4DRKWT5_Y"
- }
+ "data": {
+ "text/plain": [
+ "nacimientos_cantidad 11287855\n",
+ "dtype: int64"
+ ]
+ },
+ "execution_count": 26,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_madre_menor_20 = nac_madre_menor_20.sum()\n",
+ "nac_madre_menor_20.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "DFLoNabhMQG5"
+ },
+ "source": [
+ "Hay un problema con esta información, en la columna de grupo dece \"True\" y \"False\", esto es por la operación de clasificación de más arriba. Hay que renombrarlos para que true sea: Menor a 20 (osea que estaba en uno de los rangos etarios de nuestra condición) o \"20 o mayor\" (osea que estaba en uno de los otros rangos etarios):"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 143
},
+ "id": "IiU4eCi_MwbO",
+ "outputId": "0284be02-58d8-4262-f45b-2c57750d6772"
+ },
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nac_edad_edu_madre= nacimientos.loc[:,[\"instruccion_madre\",\"edad_madre_grupo\",\"nacimientos_cantidad\"]]\n",
- "nac_edad_edu_madre.head()"
- ],
- "metadata": {
- "colab": {
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- "2 Secundaria/Polimodal Completa 25 a 29 6\n",
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+ "text/plain": [
+ "nacimientos_cantidad 11287855\n",
+ "dtype: int64"
]
+ },
+ "execution_count": 27,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_madre_menor_20 = nac_madre_menor_20.rename({True:'Menor a 20',False:'20 o mayor'})\n",
+ "nac_madre_menor_20.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "UQj6wVmoNjq5"
+ },
+ "source": [
+ "Finalmente, graficamos con un gráfico de torta para mostrar la propoción visualmente, agregando algunas cosas como los porcentajes (con autopct ='%.2f'), el tÃtulo y el tamaño."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
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{
- "cell_type": "markdown",
- "source": [
- "Como en la pregunta anterior hay dos campos que tienen \"sin especificar\", los ignoramos:"
- ],
- "metadata": {
- "id": "4rh4mxCDT5GQ"
- }
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x7fb5787ce990>"
+ ]
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
},
{
- "cell_type": "code",
- "source": [
- "nac_edad_edu_madre.drop(nac_edad_edu_madre.index[nac_edad_edu_madre['edad_madre_grupo'] == \"Sin especificar\"], inplace = True)\n",
- "nac_edad_edu_madre.drop(nac_edad_edu_madre.index[nac_edad_edu_madre['instruccion_madre'] == \"Sin especificar\"], inplace = True)\n",
- "nac_edad_edu_madre.head()"
- ],
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- "id": "don6Rac5TPkY",
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- "0 Secundaria/Polimodal Incompleta 30 a 34 1\n",
- "1 Primaria/C. EGB Completa 30 a 34 2\n",
- "2 Secundaria/Polimodal Completa 25 a 29 6\n",
- "3 Secundaria/Polimodal Incompleta 30 a 34 5\n",
- "4 Secundaria/Polimodal Completa 25 a 29 1"
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- "metadata": {},
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\n",
+ "text/plain": [
+ "<Figure size 1080x1080 with 1 Axes>"
]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "nac_madre_menor_20.plot(kind= \"pie\", y='nacimientos_cantidad', figsize=(15, 15),autopct='%.2f',title = \"Proporción de madres tuvo hijos antes de los 20\",ylabel=\"\")\n",
+ "plt.legend([\"20 o mayor\", \"Menor a 20\"])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "Jlvd07tY0QyB"
+ },
+ "source": [
+ "Pregunta: Para cada nivel de instrucción/educación, ¿Cuántos nacimientos hubo en cada grupo etario?"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "g7S4DRKWT5_Y"
+ },
+ "source": [
+ "Primero obtenemos la información necesaria para responder la pregunta, esta está en las columnas: instruccion_madre , edad_madre_grupo y nacimientos_cantidad"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 206
},
+ "id": "eqcTPtN1TPxQ",
+ "outputId": "40babb56-7be5-42ec-f88b-c2aa204db691"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Agrupamos por instrucción/educación de la madre y grupo etario, luego se suma la cantidad de nacimientos por esas categorÃas:"
+ "data": {
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+ " <div class=\"colab-df-container\">\n",
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+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>instruccion_madre</th>\n",
+ " <th>edad_madre_grupo</th>\n",
+ " <th>nacimientos_cantidad</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>Secundaria/Polimodal Incompleta</td>\n",
+ " <td>30 a 34</td>\n",
+ " <td>1</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>Primaria/C. EGB Completa</td>\n",
+ " <td>30 a 34</td>\n",
+ " <td>2</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>Secundaria/Polimodal Completa</td>\n",
+ " <td>25 a 29</td>\n",
+ " <td>6</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>Secundaria/Polimodal Incompleta</td>\n",
+ " <td>30 a 34</td>\n",
+ " <td>5</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>Secundaria/Polimodal Completa</td>\n",
+ " <td>25 a 29</td>\n",
+ " <td>1</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
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+ " .colab-df-container {\n",
+ " display:flex;\n",
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+ " gap: 12px;\n",
+ " }\n",
+ "\n",
+ " .colab-df-convert {\n",
+ " background-color: #E8F0FE;\n",
+ " border: none;\n",
+ " border-radius: 50%;\n",
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+ " }\n",
+ "\n",
+ " .colab-df-convert:hover {\n",
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+ " box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+ " fill: #174EA6;\n",
+ " }\n",
+ "\n",
+ " [theme=dark] .colab-df-convert {\n",
+ " background-color: #3B4455;\n",
+ " fill: #D2E3FC;\n",
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+ "\n",
+ " [theme=dark] .colab-df-convert:hover {\n",
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+ "\n",
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+ " document.querySelector('#df-febd9050-c339-440e-bbba-1d647cfda90d button.colab-df-convert');\n",
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+ " '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
+ " </div>\n",
+ " </div>\n",
+ " "
],
- "metadata": {
- "id": "jZRnk0HlT6ch"
- }
+ "text/plain": [
+ " instruccion_madre edad_madre_grupo nacimientos_cantidad\n",
+ "0 Secundaria/Polimodal Incompleta 30 a 34 1\n",
+ "1 Primaria/C. EGB Completa 30 a 34 2\n",
+ "2 Secundaria/Polimodal Completa 25 a 29 6\n",
+ "3 Secundaria/Polimodal Incompleta 30 a 34 5\n",
+ "4 Secundaria/Polimodal Completa 25 a 29 1"
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_edad_edu_madre= nacimientos.loc[:,[\"instruccion_madre\",\"edad_madre_grupo\",\"nacimientos_cantidad\"]]\n",
+ "nac_edad_edu_madre.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "4rh4mxCDT5GQ"
+ },
+ "source": [
+ "Como en la pregunta anterior hay dos campos que tienen \"sin especificar\", los ignoramos:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 215
},
+ "id": "don6Rac5TPkY",
+ "outputId": "bcba689b-0288-4564-e8ff-76b9367d6121"
+ },
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nac_edad_edu_madre = nac_edad_edu_madre.groupby([\"instruccion_madre\",\"edad_madre_grupo\"]).sum()\n",
- "nac_edad_edu_madre.head()"
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+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
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+ " element.appendChild(docLink);\n",
+ " }\n",
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- " nacimientos_cantidad\n",
- "instruccion_madre edad_madre_grupo \n",
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- " + ' to learn more about interactive tables.';\n",
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- "metadata": {},
- "execution_count": 21
- }
+ "text/plain": [
+ " instruccion_madre edad_madre_grupo nacimientos_cantidad\n",
+ "0 Secundaria/Polimodal Incompleta 30 a 34 1\n",
+ "1 Primaria/C. EGB Completa 30 a 34 2\n",
+ "2 Secundaria/Polimodal Completa 25 a 29 6\n",
+ "3 Secundaria/Polimodal Incompleta 30 a 34 5\n",
+ "4 Secundaria/Polimodal Completa 25 a 29 1"
]
+ },
+ "execution_count": 20,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_edad_edu_madre.drop(nac_edad_edu_madre.index[nac_edad_edu_madre['edad_madre_grupo'] == \"Sin especificar\"], inplace = True)\n",
+ "nac_edad_edu_madre.drop(nac_edad_edu_madre.index[nac_edad_edu_madre['instruccion_madre'] == \"Sin especificar\"], inplace = True)\n",
+ "nac_edad_edu_madre.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "jZRnk0HlT6ch"
+ },
+ "source": [
+ "Agrupamos por instrucción/educación de la madre y grupo etario, luego se suma la cantidad de nacimientos por esas categorÃas:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 238
},
+ "id": "0oQCwFn2TSd5",
+ "outputId": "8ade4190-9f50-4ef9-8d2c-50776ae80bcf"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Como Agrupamos por dos categorÃas usamos unstack para graficar los datos más facilmente:"
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+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
+ " const docLink = document.createElement('div');\n",
+ " docLink.innerHTML = docLinkHtml;\n",
+ " element.appendChild(docLink);\n",
+ " }\n",
+ " </script>\n",
+ " </div>\n",
+ " </div>\n",
+ " "
],
- "metadata": {
- "id": "n9cVIZ3pT6yI"
- }
+ "text/plain": [
+ " nacimientos_cantidad\n",
+ "instruccion_madre edad_madre_grupo \n",
+ "Primaria/C. EGB Completa Menor de 15 13561\n",
+ " 15 a 19 447330\n",
+ " 20 a 24 687506\n",
+ " 25 a 29 594204\n",
+ " 30 a 34 449616"
+ ]
+ },
+ "execution_count": 21,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_edad_edu_madre = nac_edad_edu_madre.groupby([\"instruccion_madre\",\"edad_madre_grupo\"]).sum()\n",
+ "nac_edad_edu_madre.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "n9cVIZ3pT6yI"
+ },
+ "source": [
+ "Como Agrupamos por dos categorÃas usamos unstack para graficar los datos más facilmente:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 269
},
+ "id": "hHta7iM9T0B2",
+ "outputId": "4017426a-ab33-47e4-ad10-d70045e890d6"
+ },
+ "outputs": [
{
- "cell_type": "code",
- "source": [
- "nac_edad_edu_madre = nac_edad_edu_madre.unstack()\n",
- "nac_edad_edu_madre.head()"
+ "data": {
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+ " + ' to learn more about interactive tables.';\n",
+ " element.innerHTML = '';\n",
+ " dataTable['output_type'] = 'display_data';\n",
+ " await google.colab.output.renderOutput(dataTable, element);\n",
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],
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- "data": {
- "text/plain": [
- " nacimientos_cantidad \\\n",
- "edad_madre_grupo Menor de 15 15 a 19 20 a 24 25 a 29 \n",
- "instruccion_madre \n",
- "Primaria/C. EGB Completa 13561 447330 687506 594204 \n",
- "Primaria/C. EGB Incompleta 13424 171170 172795 128707 \n",
- "Secundaria/Polimodal Completa 348 224291 862070 875452 \n",
- "Secundaria/Polimodal Incompleta 13535 679556 722392 481346 \n",
- "Sin instrucción 455 6851 10413 10255 \n",
- "\n",
- " \n",
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- "instruccion_madre \n",
- "Primaria/C. EGB Completa 449616 271336 87279 6532 \n",
- "Primaria/C. EGB Incompleta 95095 60494 22362 1998 \n",
- "Secundaria/Polimodal Completa 655385 334111 80448 5187 \n",
- "Secundaria/Polimodal Incompleta 305220 160782 44473 2972 \n",
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- ]
- },
- "metadata": {},
- "execution_count": 22
- }
+ "text/plain": [
+ " nacimientos_cantidad \\\n",
+ "edad_madre_grupo Menor de 15 15 a 19 20 a 24 25 a 29 \n",
+ "instruccion_madre \n",
+ "Primaria/C. EGB Completa 13561 447330 687506 594204 \n",
+ "Primaria/C. EGB Incompleta 13424 171170 172795 128707 \n",
+ "Secundaria/Polimodal Completa 348 224291 862070 875452 \n",
+ "Secundaria/Polimodal Incompleta 13535 679556 722392 481346 \n",
+ "Sin instrucción 455 6851 10413 10255 \n",
+ "\n",
+ " \n",
+ "edad_madre_grupo 30 a 34 35 a 39 40 a 44 De 45 y más \n",
+ "instruccion_madre \n",
+ "Primaria/C. EGB Completa 449616 271336 87279 6532 \n",
+ "Primaria/C. EGB Incompleta 95095 60494 22362 1998 \n",
+ "Secundaria/Polimodal Completa 655385 334111 80448 5187 \n",
+ "Secundaria/Polimodal Incompleta 305220 160782 44473 2972 \n",
+ "Sin instrucción 8756 6030 2618 317 "
]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "nac_edad_edu_madre = nac_edad_edu_madre.unstack()\n",
+ "nac_edad_edu_madre.head()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "YIh4bD50T7VR"
+ },
+ "source": [
+ "Finalmente graficamos con un gáfico de barras, donde cada grupo corresponde a un nivel de educación y cada barra a un grupo etario, mientras más alta la barra, más nacimientos. También agregamos un tÃtulo y la leyenda:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "colab": {
+ "base_uri": "https://localhost:8080/",
+ "height": 946
},
+ "id": "bf6v9x7gAwku",
+ "outputId": "7f8bec90-7f0c-462d-877f-42317d86ee19"
+ },
+ "outputs": [
{
- "cell_type": "markdown",
- "source": [
- "Finalmente graficamos con un gáfico de barras, donde cada grupo corresponde a un nivel de educación y cada barra a un grupo etario, mientras más alta la barra, más nacimientos. También agregamos un tÃtulo y la leyenda:"
- ],
- "metadata": {
- "id": "YIh4bD50T7VR"
- }
+ "data": {
+ "text/plain": [
+ "<matplotlib.legend.Legend at 0x7fb576ec7650>"
+ ]
+ },
+ "execution_count": 23,
+ "metadata": {},
+ "output_type": "execute_result"
},
{
- "cell_type": "code",
- "source": [
- "nac_edad_edu_madre.plot.bar(figsize= (25,13),xlabel=\"\",title = \"Cantidad de nacimientos por grupo etario y educación de la madre\")\n",
- "plt.legend([\"Menor de 15\", \"15 a 19\", \"20 a 24\", \"25 a 29\", \"30 a 34\", \"35 a 39\", \"40 a 44\", \"De 45 y más\"])"
- ],
- "metadata": {
- "id": "bf6v9x7gAwku",
- "colab": {
- "base_uri": "https://localhost:8080/",
- "height": 946
- },
- "outputId": "7f8bec90-7f0c-462d-877f-42317d86ee19"
- },
- "execution_count": null,
- "outputs": [
- {
- "output_type": "execute_result",
- "data": {
- "text/plain": [
- "<matplotlib.legend.Legend at 0x7fb576ec7650>"
- ]
- },
- "metadata": {},
- "execution_count": 23
- },
- {
- "output_type": "display_data",
- "data": {
- "text/plain": [
- "<Figure size 1800x936 with 1 Axes>"
- ],
- "image/png": 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\n"
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\n",
+ "text/plain": [
+ "<Figure size 1800x936 with 1 Axes>"
]
+ },
+ "metadata": {
+ "needs_background": "light"
+ },
+ "output_type": "display_data"
}
- ]
-}
\ No newline at end of file
+ ],
+ "source": [
+ "nac_edad_edu_madre.plot.bar(figsize= (25,13),xlabel=\"\",title = \"Cantidad de nacimientos por grupo etario y educación de la madre\")\n",
+ "plt.legend([\"Menor de 15\", \"15 a 19\", \"20 a 24\", \"25 a 29\", \"30 a 34\", \"35 a 39\", \"40 a 44\", \"De 45 y más\"])"
+ ]
+ }
+ ],
+ "metadata": {
+ "colab": {
+ "collapsed_sections": [],
+ "name": "Demo_CDS_nacimientos.ipynb",
+ "provenance": []
+ },
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.4"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}