{"cells":[{"cell_type":"markdown","metadata":{"id":"GtE5K8jWAhyk"},"source":["# **Optimización del proceso de ejecución de Programa Rural de Ministerio de Vivienda y Urbanismo**"]},{"cell_type":"markdown","metadata":{"id":"qXxczV33XQjp"},"source":["## **Taller de Proyecto de Datos: Hito 3**"]},{"cell_type":"markdown","metadata":{"id":"OMUMWHvHXUVT"},"source":["####**Estudiantes**\n","- Militza Gascon\n","- Dominique Hermosilla\n","- Giuliano Puttini\n","- Gustavo Valdes\n"]},{"cell_type":"markdown","metadata":{"id":"R2oYtcrDwMeY"},"source":["###**Abstracto de la entrega**\n","\n","En este informe se realizará la descripción y presentación de una propuesta experimental para responder a las preguntas planteadas por el equipo.\n","\n","El experimento consta de varias etapas subsecuentes y evolutivas, donde cada paso depende del anterior para su correcto desarrollo. Sin embargo, como en cualquier proceso de investigación, las etapas subsiguientes demandan revisar y replantear los trabajos en base a nuevos descubrimientos e información relevante para el estudio.\n","\n","A continuación, se muestra un estado final de este proceso recurrente, donde se observan las siguientes partes:\n","\n","* <b>Parte 1: Contexto del proyecto y planteamiento del análisis</b>, donde se define qué es el Programa de Habitabilidad Rural y cuáles son las preguntas planteadas por el grupo para el estudio.\n","* <b>Parte 2: Preparación del entorno Python para el procesamiento</b>, donde se detallan las librerías y módulos necesarios para ejecutar los códigos.\n","* <b>Parte 3: ETL y preprocesamiento de datos</b>, donde se carga la base de datos proporcionada por el ministerio y se llevan a cabo estudios de limpieza y calidad de datos. También se realizan exclusiones de variables irrelevantes para el estudio y transformaciones necesarias, además de la creación de variables que se utilizarán en análisis posteriores.\n","* <b>Parte 4: Análisis exploratorio de datos, que consta de dos componentes</b>: un informe estadístico que muestra información como la varianza, desviación estándar y promedios de las variables, así como la identificación de correlaciones entre ellas. Este informe está separado del documento actual.\n","\n","  El segundo componente del análisis exploratorio son visualizaciones de datos que verifican los tipos de proyectos más frecuentes y las regiones más favorecidas por el programa. Se responde a algunas de las preguntas planteadas para el proyecto, observando que las regiones más beneficiadas por el PHR son las del centro (Araucanía, Ñuble y Maule) en comparación con las del extremo del país (Magallanes, Arica, Antofagasta), lo cual es coherente desde el punto de vista demográfico debido a la población y los índices de desarrollo humano (IDH) más bajos en esas regiones.\n","* <b>Parte 5: Modelo de predicción del cumplimiento del nivel de servicio</b>, donde se propone un modelo de regresión logística para evaluar dos categorías distintas: los proyectos que cumplieron con los plazos propuestos por el ministerio para la entrega del proyecto y los que no. Se detalla la variable objetivo basada en el Tipo de Intervención y se justifica el uso de un modelo de regresión logística para predecir el cumplimiento de plazos y evaluar las características que más influyen en el incumplimiento de los mismos.\n","* <b>Parte 6: Análisis de los tiempos de conclusión de los proyectos</b>: Los plazos propuestos para la entrega de los proyectos, especialmente en el caso de Viviendas Nuevas con un período de 4 años, son considerablemente extensos. Esta extensión provoca que muchos de los datos de la base aún no hayan completado su ciclo, lo que los hace no elegibles para un análisis mediante un modelo logístico. Esto ocurre debido a la imposibilidad de calcular la variable objetivo.\n","\n","  Ante este desafío, surge una alternativa: el análisis de una variable objetivo denominada 'Tiempo'. La esencia radica en desarrollar un modelo que responda a la siguiente interrogante: 'Dado el tiempo transcurrido (t) hasta el momento actual en el proyecto, ¿cuánto más tiempo tomará para su conclusión?'\n","\n","  Los modelos que responden a este tipo de problema son del tipo de análisis de supervivencia y se proponen como los próximos pasos del proyecto actual.\"\n","\n","\n","\n","\n","\n","\n","\n","\n"]},{"cell_type":"markdown","metadata":{"id":"MWaTK0qNGkMw"},"source":["### **PARTE 1:Contexto del proyecto**"]},{"cell_type":"markdown","metadata":{"id":"vBb9K6_USc5Z"},"source":["El Programa de Habitabilidad Rural (PHR en adelante), es un programa del Ministerio de Vivienda y Urbanismo que tiene por objetivo mejorar la calidad de vida de las familias que residen en áreas rurales, garantizando que sus viviendas cumplan con los estándares de habitabilidad establecidos por el Ministerio.\n","\n","Este cuenta con tres componentes 1) Construcción de Vivienda Nueva, con las tipologías de proyectos Construcción en Sitio del Residente o Construcción de Conjunto Habitacional; 2) Mejoramiento y/o Ampliación de Vivienda Existente; 3) Mejoramiento de Entorno y Equipamiento Comunitario.\n","\n","Los datos asociados a la ejecución del PHR son consolidados por parte de MINVU en un solo dataset denominado \"Base PHR\", que fue pedida a la institución vía solicitud de información pública en el marco de la Ley de Transparencia.\n","\n","A partir de la observación inicial de los datos contenidos en el dataset se concluyó que los principales desafíos para la institución se encuentran en los tiempos de ejecución de los proyectos, razón por la cual, nuestra motivación será generar una optimización de los mismos.\n","\n","\n","El proyecto tiene como finalidad abordar las siguientes preguntas planteadas en el hito:\n","\n","* ¿Se puede segmentar la información para llevar a cabo un análisis más detallado y descriptivo de cada componente del programa?\n","* ¿Dónde se localizan los cuellos de botella o los puntos críticos en términos de ejecución territorial?\n","* ¿Existen territorios o comunas particularmente desfavorecidos en la ejecución de proyectos, o, por el contrario, se han evaluado positivamente?\n","* ¿Es posible realizar predicciones sobre la cantidad de obras que se iniciarán y su tiempo de ejecución?\n","\n","En resumen, este proyecto tiene como objetivo aprovechar la información recopilada para mejorar la planificación y ejecución del Programa de Habitabilidad Rural, garantizando que las familias rurales tengan acceso a viviendas que cumplan con los estándares de habitabilidad. Las preguntas planteadas buscan optimizar la toma de decisiones, aumentar la eficiencia en la ejecución de proyectos y identificar áreas que requieran atención especial en términos de desarrollo rural.\n"]},{"cell_type":"markdown","source":["### **PARTE 2: Preparación del entorno Python para el procesamiento**"],"metadata":{"id":"bntQgmy1Ew3G"}},{"cell_type":"markdown","source":["#### Intalación de módulos y librerías"],"metadata":{"id":"NvbMaaEjE9Lg"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"xQTE_fy3e9SJ"},"outputs":[],"source":["!pip uninstall pandas"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"E02FnLmpqQD5"},"outputs":[],"source":["#Antes de ejecutar se debe reiniciar el Entorno de Ejecucion .\n","\n","!pip install pandas==1.5.3"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"i1A1XyaxcfO1"},"outputs":[],"source":["!pip install -U ipywidgets ydata_profiling"]},{"cell_type":"markdown","metadata":{"id":"pz4ZtCSW6syA"},"source":["####Importación de librerías Pandas y Numpy, y módulo Datetime"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"TdYn7ijZcUYK"},"outputs":[],"source":["import pandas as pd\n","import numpy as np\n","import datetime as dt\n","#from ydata_profiling import ProfileReport\n","import plotly.express as px\n","import plotly.graph_objects as go\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","import os\n","\n","from google.colab import drive\n","from google.colab import files\n","import io\n","\n","import warnings\n","warnings.filterwarnings(\"ignore\")"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"r0HDYwZ_yB0v"},"outputs":[],"source":["pd.__version__"]},{"cell_type":"markdown","metadata":{"id":"Fqj5_VEIEgYX"},"source":["###**PARTE 3: ETL y preprocesamiento de datos**"]},{"cell_type":"markdown","metadata":{"id":"b6XMKlpnMQqb"},"source":["####Carga de dataset"]},{"cell_type":"markdown","metadata":{"id":"GB6pcdBqDw7f"},"source":["Inicialmente tiene por objetivo crear y montar el GoogleDrive que contiene la Base de Datos, y apuntar el camino donde encuentra el archivo Excel"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"buouMZUrTftA"},"outputs":[],"source":["uploaded = files.upload()\n","path = io.BytesIO(uploaded['Base PHR.xlsm'])\n","#drive.mount('/content/drive',force_remount=True)\n","#path = '/content/drive/MyDrive/Colab_Notebooks/Taller de proyecto de datos. Grupo MINVU/Base PHR.xlsm'\n","#path = '/content/Base PHR.xlsm'"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"zq-UivoKsNTr"},"outputs":[],"source":["#Carga de la tabla con los parametros anteriores\n","\n","# utilidad para mostrar todas las columnas\n","pd.set_option(\"display.max_columns\", None)\n","\n","\n","df = pd.read_excel(path\n","                  , sheet_name=\"PHR\"\n","                  , header=[2]\n","                  , index_col=0\n","                  , na_values=[\"Falta\",\"-\",\"#N/D\",\"00/01/1900\"]\n","                 # , nrows=5000\n","                  )\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"yFPbrBgf028z"},"outputs":[],"source":["# Mostrar las primeras 3 filas del DataFrame. Detalle de lo que tiene el archivo\n","primeras_3_filas = df.head(3)\n","\n","primeras_3_filas\n"]},{"cell_type":"markdown","metadata":{"id":"Tb-OeiKUdkbW"},"source":["Con respecto a los datos, estos se proporcionaron en un archivo Excel que contiene un total de 44,276 registros distribuidos en 153 columnas. La columna \"ID PHR\" identifica a los beneficiarios del programa, quienes tienen la capacidad de presentar solicitudes de proyectos de forma individual o colectiva, y pueden beneficiarse en cualquiera de las tres líneas de atención del Programa de Habitabilidad Rural.\n","\n","La modalidad de las solicitudes se puede determinar a través del análisis de las columnas \"Tipo de Expediente\" y \"N° de Expediente\". En las secciones posteriores, se detallarán los pasos llevados a cabo durante la carga, procesamiento y limpieza de estos datos en un entorno de Jupyter Notebook en Google Colab.\n"]},{"cell_type":"markdown","source":["####Preprocesamiento de datos"],"metadata":{"id":"vdeUE2k2kO2-"}},{"cell_type":"markdown","metadata":{"id":"Jr3XeDF4ETLB"},"source":["#####Corrección de fechas"]},{"cell_type":"markdown","metadata":{"id":"OQBiWW_hNEln"},"source":["Dado que los datos en su mayoria son ingresados manualmente, las fechas que contiene el archivo Excel presentan diversos formatos (como aaaa-mm-dd, mm/dd/yyyy, mm/dd/yy, entre otros).\n","\n","También se identificaron casos en los que, debido a la falta de columnas y/o la imprevisibilidad de nuevas etapas que debían ser registradas, estas se agregaron a la tabla con un separador \"+\".\n","\n","En los casos necesarios, se trabajaron las fechas para ajustarlas al formato datetime.\n","\n","Las variables afectadas por esta situacion son las siguientes:\n","\n","- Fecha Publicación DO\n","- Fecha RE Incr. Obra\n","- Fecha RE Complem.\n","- Fecha RE Aprobación Proyecto DITEC\n","- Fecha Acta Entrega Terreno DITEC"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"x2LMGKM-BV_T"},"outputs":[],"source":["df['Fecha Publicación DO']=df.loc[:,'Fecha Publicación DO'].apply(pd.to_datetime,dayfirst=True)\n","fechas = df.loc[:,['Fecha RE Incr. Obra','Fecha RE Complem.','Fecha RE Aprobación Proyecto DITEC','Fecha Término de Obra  DITEC','Fecha Acta Entrega Terreno DITEC']]\n","mask = fechas['Fecha RE Incr. Obra'].str.find(\"+\")>0\n","fechas[['Fecha_incr_1','Fecha_incr_2']] = fechas.loc[:,'Fecha RE Incr. Obra'].str.split(\"+\",expand=True,).apply(lambda x: pd.to_datetime(x,dayfirst=True))\n","f_incr_aux = fechas.loc[~mask,'Fecha RE Incr. Obra'].apply(lambda x: pd.to_datetime(x,dayfirst=True))\n","fechas = fechas.join(f_incr_aux,how='left',rsuffix='_')\n","fechas['Fecha_incr_1']=np.where(mask,fechas['Fecha_incr_1'],fechas['Fecha RE Incr. Obra_'])\n","mask = fechas['Fecha RE Complem.'].str.find(\"+\")>0\n","fechas[['Fecha_complem_1','Fecha_complem_2','Fecha_complem_3']] = fechas.loc[:,'Fecha RE Complem.'].str.split(\"+\",expand=True).apply(lambda x: x.str.strip()).apply(lambda x: pd.to_datetime(x,dayfirst=True))\n","f_compl_aux = fechas.loc[~mask,'Fecha RE Complem.'].apply(lambda x: pd.to_datetime(x,dayfirst=True))\n","fechas = fechas.join(f_compl_aux,how='left',rsuffix=\"_\")\n","fechas['Fecha_complem_1'] = np.where(mask,fechas['Fecha_complem_1'],fechas['Fecha RE Complem._'])\n","#fechas['Fecha_aprob_proyecto_DITEC'] = fechas['Fecha RE Aprobación Proyecto DITEC'].apply(lambda x: x if isinstance(x,dt.datetime) else np.nan)\n","#fechas['Fecha_term_DITEC']=fechas.loc[:,'Fecha Término de Obra  DITEC'].apply(lambda x: x if isinstance(x,dt.datetime) else np.nan) - dato redundante\n","#fechas['Fecha_acta_entrega_terreno_DITEC']=fechas.loc[:,'Fecha Acta Entrega Terreno DITEC'].apply(lambda x: x if isinstance(x,dt.datetime) else np.nan)\n","#fechas.head()"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"5paYk8xvdo-l"},"outputs":[],"source":["#validación de fechas trabajadas\n","#fechas.loc[['AN1','CO611','LR225','LA3114','AY186','LA3551'],:]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"LWkiuPLDQB8G"},"outputs":[],"source":["#inserción de fechas en la base de datos:\n","lista = ['Fecha_incr_1','Fecha_incr_2','Fecha_complem_1','Fecha_complem_2','Fecha_complem_3']\n","df = df.join(fechas[lista],how='left', rsuffix='_fechas')"]},{"cell_type":"markdown","source":["#####Selección de variables de interés"],"metadata":{"id":"dNi9qtftFxBR"}},{"cell_type":"markdown","metadata":{"id":"7syIyb8XXBGp"},"source":["A pesar de la gran cantidad de variables en la base de datos PHR, a priori, se observa que muchas características son irrelevantes para el estudio propuesto. Esta intuición ha sido confirmada por la experta de la institución que actúa como contarparte, quien nos ha explicitado que los nudos críticos del proceso se encuentran en torno de las fechas de los procesos y los datos de tipo financiero.\n","\n","Adicionalmente, la base cuenta con diversas informaciones de números de requerimiento interno (RE), que identifican los procesos o solicitudes ingresadas. Estos datos no se considerarán por ser de tipo categórico nominal. Como se explicó anteriormente, la variable `N° de Expediente` es relevante para identificar grupos de solicitudes de modalidad colectiva.\n","\n","Por otro lado, la tabla cuenta con diversas informaciones de detalles de m² de obras, o los detalles de valores de cada etapa de la obra, pero no han sido confirmados por la experta como datos imprescindibles.\n","\n","Así, las características a ser trabajadas pueden ser reducidas en gran cantidad, mantenendo solamente las informaciones relevantes para análisis.\n","\n","El grupo de informaciones _Homologación_ _de_ _Subsidio_ _(RE 833/2023)_ conforman una nueva etapa dentro del proceso, pero dado la recién incorporación de este proceso dentro del Programa Rural, no se cuenta con gran poblamiento de datos. Así, ese grupo de informaciones quedarán excluídas de los análisis."]},{"cell_type":"markdown","metadata":{"id":"mL-50zBWDmxh"},"source":["> Nota (GF): Después de algunas análisis, se verificó que las fechas: Fecha Recepción SERVIU,\tFecha Recepción DOM y Fecha Término de Obra  DITEC, Fecha Aprobación Terreno DITEC, Fecha Acta Entrega Terreno DITEC son irrelevante para el análisis por agregaren poca información y estaren con datos reduntantes, con otras (como por ejemplo la fecha del Térmido de Obra).\n","\n","> Así, para mejor refletir las etapas del proceso esas no será consideradas."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"bZkTHXt4-dCM"},"outputs":[],"source":["# Creación de un diccionário de datos:\n","\n","dic = {'Identificación del Subsidio':['Postula Con Proyecto Desarrollado',\t'Año Programa',\t'N° RE Llamado',\t'Fecha Publicación DO']\n","       ,'Datos Generales':['Región Ejecución',\t'Provincia',\t'Comuna',\t'Localidad',\t'Factor Localidad',\t'Tipo de Expediente',\t'Tipología Madre',\t'Tipo de Intervención',\t'N° Expediente']\n","       ,'Dimensión':['m² Vivienda Nueva',\t'm² Ampliac. Cocina',\t'm² Ampliac. Baño',\t'm² Ampliac. Dormitorio',\t'm² Ampliac. Recinto Complem.',\t'Tipo de Recinto Complem.',\t'Total m² Proyecto']\n","       ,'Vivienda Nueva': ['CCH', 'CSR']\n","       ,'Mejoramiento': ['Mejoram. Vivienda',\t'Servicios Básicos',\t'Acond. Térmico',\t'Eficiencia Energ.']\n","       ,'Ampliación':['Cocina',\t'Baño',\t'Tercer Dormit.',\t'Recinto Complem.']\n","       ,'Entorno':['Inmediato',\t'Equip. Comunit.']\n","       ,'Complementario':['Mejoram. Terreno',\t'Solución Sanit. y/o Dotación Energía',\t'Arq. Local',\t'Discapacidad / Mov. Reducida',\t'Regulariz.',\t'Equip. y Espacio Público']\n","       ,'Ahorro':['Ahorro Eximido (Aporte MINVU)',\t'Ahorro Familia',\t'Otros Aportes Adicion.',\t'Origen Aportes Adicionales']\n","       ,'Total Obra':['Total Asignado Proyecto MINVU',\t'Total Presup. Proyecto']\n","       ,'Assistencia Técnica':['AT',\t'FTO',\t'CBR', 'Total AT + FTO + CBR']\n","       ,'Incremento Regular Obra':['Monto Incr. Obra',\t'Año Imputación Incr. Obra',\t'N° RE Incr. Obra',\t'Fecha RE Incr. Obra',\t'Concepto Incremento Obra']\n","       ,'Incremento Regular AT + FTO + CBR':['Monto Incr. AT + FTO + CBR',\t'Año Imputación Incr. AT + FTO + CBR',\t'N° RE Incr. AT + FTO + CBR',\t'Fecha RE Incr. AT + FTO + CBR',\t'Concepto Incremento AT + FTO + CBR', 'Total Incremento']\n","       ,'COMPLEMENTARIO SEREMI (RE 6042/2016)':['Complem. Mejoram. Terreno',\t'Complem. Solución Sanit. y/o Dotación Energía',\t'Complem. Arq. Local',\t'Complem. Discapacidad / Mov. Reducida',\t'Complem. Regulariz.',\t'Complem. Equip. y Espacio Público',\t'Complem. AT',\t'Complem. FTO',\t'Año Imputación Complem.',\t'N° RE Complem.',\t'Fecha RE Complem.']\n","       ,'Total Complem.':['Total Complem.']\n","       ,'INCREMENTO ALZA MATERIALES (RE 1448/2021)':['Monto 1er Incr. Alza Materiales',\t'Año Imputación 1er Incr. Alza Materiales',\t'N° RE 1er Incr. Alza Materiales',\t'Fecha RE 1er Incr. Alza Materiales',\t'Monto 2do Incr. Alza Materiales',\t'Año Imputación 2do Incr. Alza Materiales',\t'N° RE 2do Incr. Alza Materiales',\t'Fecha RE 2do Incr. Alza Materiales',\t'Monto 3er Incr. Alza Materiales',\t'Año Imputación 3er Incr. Alza Materiales',\t'N° RE 3er Incr. Alza Materiales',\t'Fecha RE 3er Incr. Alza Materiales', 'Total Alza Materiales']\n","       ,'HOMOLOGACIÓN DE SUBSIDIO (RE 833/2023)':{'Vivienda Nueva':['Homolog. CCH',\t'Homolog. CSR']\n","                                                  ,'Mejoramiento':['Homolog. Mejoram. Vivienda', 'Homolog. Servicios Básicos',\t'Homolog. Acond. Térmico',\t'Homolog. Eficiencia Energ.']\n","                                                  ,'Ampliación':['Homolog. Cocina',\t'Homolog. Baño',\t'Homolog. Tercer Dormitorio',\t'Homolog. Recinto Complem.']\n","                                                  ,'Entorno':['Homolog. Inmediato',\t'Homolog. Equip. Comunit.']\n","                                                  ,'Complementario':['Homolog. Mejoram. Terreno',\t'Homolog. Solución Sanit. y/o Dotación Energía',\t'Homolog. Arq. Local',\t'Homolog. Discapacidad / Mov. Reducida',\t'Homolog. Regulariz.',\t'Homolog. Equip. y Espacio Público']\n","                                                  ,'AT y FTO':['Homolog. AT',\t'Homolog. FTO']\n","                                                  ,'Homologacion':['Año Imputación Homolog.',\t'N° RE Homolog.', \t'Fecha RE Homolog.']\n","                                                  ,'Total Homolog.':['Total Homolog']\n","                                                  }\n","       ,'Alberge Transitorio':['Monto 1er Albergue Tansitorio',\t'Año Imputación 1er Albergue Transitorio',\t'RE 1er Albergue Transitorio',\t'Fecha RE 1er Albergue Transitorio',\t'Monto 2do Albergue Tansitorio',\t'Año Imputación 2do Albergue Transitorio',\t'RE 2do Albergue Transitorio',\t'Fecha RE 2do Albergue Transitorio',\t'Monto 3er Albergue Tansitorio',\t'Año Imputación 3er Albergue Transitorio',\t'RE 3er Albergue Transitorio',\t'Fecha RE 3er Albergue Transitorio', 'Total Albergue Transitorio']\n","       ,'TOTALES':['Total Aporte MINVU Original',\t'Total Aporte MINVU Final (incluye incrementos)',\t'Total Disponible Proyecto (incl. ahorro familia)']\n","       ,'Ejecución de Obras':['Proyección Inicio Obra (año/semestre)',\t'Incremento Requerido para Iniciar Obras',\t'N° RE Aprobación Proyecto',\t'Fecha RE Aprobación Proyecto',\t'N° RE Aprobación Proyecto DITEC',\t'Fecha RE Aprobación Proyecto DITEC',\t'Fecha Acta Entrega Terreno',\t'Fecha Acta Entrega Terreno DITEC',\t'Nombre Constructora',\t'Nombre Constructora DITEC',\t'Fecha Recepción SERVIU',\t'Fecha Recepción DOM',\t'Fecha Término de Obra',\t'Comparar Actualización Término de Obra DITEC',\t'Fecha Término de Obra  DITEC',\t'Año Término',\t'Cumple Término PEH']\n","       ,'ESTADO PROYECTO':['% Avance Físico',\t'ESTADO PROYECTO',\t'% Avance Físico DITEC',\t'ESTADO PROYECTO DITEC',\t'SUBESTADO PROYECTO DITEC',\t'% Corregido',\t'Estado beneficiario DITEC',\t'N° RE Renuncia / Eliminación',\t'Fecha RE Renuncia / Eliminación',\t'Observación DPH',\t'Observación Región']\n","       }"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"m70C7IKydflt"},"outputs":[],"source":["keys = ['Identificación del Subsidio','Datos Generales','Ahorro','Total Obra','Total Complem.', 'TOTALES', 'Ejecución de Obras', 'ESTADO PROYECTO']\n","lista=[]\n","for key in keys:\n","  for item in dic[key]:\n","    lista.append(item)\n","fechas = ['Fecha_incr_1','Fecha_incr_2','Fecha_complem_1','Fecha_complem_2','Fecha_complem_3']\n","for item in fechas:\n","  lista.append(item)\n","otros = ['Monto Incr. Obra', 'Concepto Incremento Obra', 'Total Incremento', 'Fecha RE 1er Incr. Alza Materiales', 'Fecha RE 2do Incr. Alza Materiales', 'Fecha RE 3er Incr. Alza Materiales', 'Total Alza Materiales', 'RE 1er Albergue Transitorio',\t'Fecha RE 1er Albergue Transitorio', 'Fecha RE 2do Albergue Transitorio', 'Fecha RE 3er Albergue Transitorio', 'Total Albergue Transitorio']\n","for item in otros:\n","  lista.append(item)\n","retirar = ['Comuna', 'Localidad', 'Factor Localidad', 'N° RE Aprobación Proyecto', 'N° RE Aprobación Proyecto DITEC','Fecha RE Aprobación Proyecto DITEC','Fecha Recepción SERVIU',\t'Fecha Recepción DOM', 'Comparar Actualización Término de Obra DITEC', 'Fecha Término de Obra  DITEC', 'Fecha Acta Entrega Terreno DITEC', 'Año Término']\n","for item in retirar:\n","  lista.remove(item)\n","lista\n","\n","df_f = df[lista]\n","\n","#df_f.head(3)\n"]},{"cell_type":"markdown","source":["#####Exclusión de informaciones\n"],"metadata":{"id":"B0pVZG7iF4TP"}},{"cell_type":"markdown","metadata":{"id":"NYaJkETYo-ej"},"source":["\n","En algunos casos, las informaciones son incoherentes o erróneas, sea por problemas sistémicos, o por la extración de los datos del sistema origen.\n","\n","Cuando no se puede averiguar la corrección de los datos desde la fuente, puede ser mejor excluirlos de los análisis para no inducir variabilidad proveniente de problemas sistémicos ajnos al problema de estudio.\n","\n","En este proyecto fueron identificados casos en que la fecha de conclusión de obras estaban marcados como **anteriores** a la fecha de inicio de la postulación. Así, esos casos fueron excluidos del análisis."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"8BxHy_QFqL6h"},"outputs":[],"source":["dif = (df_f['Fecha Término de Obra'] - df_f['Fecha Publicación DO']).dt.days / 365\n","mask = dif < 0\n","#código abajo sirve para averiguar quienes son - no necesário para análisis\n","#df_f[mask]\n","\n","#ese código filtra los datos incoerentes\n","df_f = df_f[~mask]\n","print(df_f.shape)\n","#en los casos en que no hay Fecha Publicación, sustituir por el Año del Programa\n","dif = df_f['Fecha Término de Obra'].dt.year - df_f['Año Programa']\n","mask = dif < 0\n","df_f = df_f[~mask]\n","print(df_f.shape)"]},{"cell_type":"markdown","metadata":{"id":"4S47RcvqnBkX"},"source":["####Creación de variables adicionales\n"]},{"cell_type":"markdown","source":["\n","Grande parte de los análisis estadísticos consisten en crear nuevas variables basadas en los datos.\n","\n","Para este proyecto, el interés principal está en la duración de tiempo toma desde la entrada del proyecto hasta la fecha de término. Para el Ministerio, eso cuantifica sus indicadores de performance y miden el retraso del proceso de entrega de los beneficios.\n","\n","Otra variable de interés tiene que a ver con la cantidad de etapas que cada proyecto tiene desde el comienzo hasta la publicación. Se espera que, etapas adicionales evidencian complejidades para el proceso y pueden consistir en fallas o problemas en las entregas dentro del plazo esperado."],"metadata":{"id":"UKNbqe7YGFLH"}},{"cell_type":"markdown","metadata":{"id":"lw0R2aH-y50Z"},"source":["#####**Duración del proceso hasta conclusión (en años)**"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"qITZ53vffGaP"},"outputs":[],"source":["#En los casos que la Fecha Publicación DO no esta cargada en la tabla, se sugiere utilizar el Año Programa para cálculo\n","#de la duración\n","mask=df_f['Fecha Publicación DO'].isnull()\n","df_f[mask]\n","df_f['Duracion (años)'] = np.where(mask\n","                                   ,df_f['Fecha Término de Obra'].dt.year - df_f['Año Programa']\n","                                   ,(df_f['Fecha Término de Obra'] - df_f['Fecha Publicación DO']).dt.days / 365\n","                                  )\n","\n","# Estadísticas descriptivas en años\n","estadisticas_duracion_anual = df_f['Duracion (años)'].describe()\n","\n","# Crear un DataFrame para mostrar las estadísticas en años\n","df_estadisticas_duracion_anual = pd.DataFrame(estadisticas_duracion_anual)\n","df_estadisticas_duracion_anual.reset_index(inplace=True)\n","df_estadisticas_duracion_anual.columns = ['Métrica', 'Duración (años)']\n","\n","# Mostrar las estadísticas descriptivas en años\n","print(df_estadisticas_duracion_anual)"]},{"cell_type":"markdown","metadata":{"id":"5Q5MwPPlAjvX"},"source":["#####**Cantidad de etapas en el proceso**"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"T_gMItPxE770"},"outputs":[],"source":["df_f['cantidad_etapas'] = (df_f\n","    .filter(regex='^Fecha')\n","    .drop(columns=['Fecha Publicación DO', 'Fecha RE Renuncia / Eliminación', 'Fecha Término de Obra'])\n","    .notnull()\n","    .sum(axis=1)\n",")"]},{"cell_type":"markdown","metadata":{"id":"fY6kgY4FIOBc"},"source":["#####**Etapas que tienen más tiempo**\n"]},{"cell_type":"markdown","source":["\n","Esa variable mide, para cada instancia, cuáles fueron las dos etapas que llevaron más tiempo (en días) dentro del proceso. Es decir, que entre todas las fechas encontradas para un proceso se ordenan las etapas y se hacen las diferencias, hasta que se verifique la de mayor duración. El resultado son dos variables: una que mide el tiempo en días y la otra de formato texto que muestra la etapa anterior y la etapa posterior.\n","\n","Para los casos en los que no hay una fecha final, es decir, que no hay entrega del proyecto o desistimiento, la fecha máxima es la fecha de obtención de la base de datos, el 31/08/2023.\n"],"metadata":{"id":"A-rHVtNEGTbu"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"j0fUv07WR5Rg"},"outputs":[],"source":["#mask=df_f['Fecha Publicación DO'].isnull()\n","#df_f[mask]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"lPUgh4gAQSBV"},"outputs":[],"source":["#En los casos en que no hay la Fecha de Publicación DO, será utilizado la mínima fecha DO del mismo Año Programa\n","gb = df_f.rename(columns={'Fecha Publicación DO':'FechaDO'}).groupby('Año Programa')['FechaDO'].agg([np.min, np.max]).reset_index()\n","gb['amin'].fillna(gb.amax.shift(1),inplace=True)\n","gb.rename(columns={'amin':'FechaDO'},inplace=True)\n","gb.drop(columns=['amax'],inplace=True)\n","#gb\n","data = pd.merge(df_f.reset_index(), gb, how = 'left', left_on = 'Año Programa', right_on = 'Año Programa')\n","#data.head()\n","data['Fecha Publicación DO'].fillna(data['FechaDO'],inplace = True)\n","data.index = data['ID PHR']\n","data.drop(columns=['ID PHR'], inplace=True)\n","#data[mask].head()\n","#data.head()\n","#mask2=data['Fecha Publicación DO'].isnull()\n","#data[mask2]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"q0QajhKk8GEr"},"outputs":[],"source":["#Teste para verificación de creación de la fecha fin\n","#data['Fecha_fin']=np.where(data['Fecha RE Renuncia / Eliminación'].isnull() & data['Fecha Término de Obra'].isnull(),pd.to_datetime('31-08-2023',dayfirst=True),np.nan)\n","#data.loc[['AN1','CO611','LR225','LA3114','AY186','LA3551'],['Fecha_fin','Fecha RE Renuncia / Eliminación','Fecha Término de Obra']]"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"yOu1Qv9DIidD"},"outputs":[],"source":["#Creación de uma variable de fecha fim para los que no fueron Renunciados ni con Término de obras\n","data['Fecha_fin'] = np.where(data['Fecha RE Renuncia / Eliminación'].isnull() & data['Fecha Término de Obra'].isnull(),pd.to_datetime('31-08-2023',dayfirst=True),np.nan)\n","#Tranponiendo la base de datos\n","d_aux = (pd.melt(data\n","    .filter(regex='^Fecha')\n","    .drop(columns=['FechaDO'])\n","#    .head(20)\n","    ,ignore_index=False\n","    ,value_name='Fechas'\n"," ).dropna()\n","  .reset_index()\n","  .sort_values(by = ['ID PHR', 'Fechas'])\n","  .assign(fecha_ant = lambda x: x.Fechas.shift(1)\n","          ,etapa_ant = lambda x: x.variable.shift(1)\n","          ,idx_ant = lambda x: x['ID PHR'].shift(1)\n","          )\n",").dropna()\n","d_aux=d_aux[d_aux[\"ID PHR\"] == d_aux.idx_ant]\n","d_aux['dif_fechas'] = (d_aux.Fechas - d_aux.fecha_ant).dt.days\n","d_aux=pd.merge(d_aux, d_aux.groupby(by='ID PHR')['dif_fechas'].agg(np.max), how = 'inner', left_on = ['ID PHR','dif_fechas'], right_on = ['ID PHR','dif_fechas'])\n","d_aux['etapa']=d_aux['etapa_ant'].astype(str) + ' - ' + d_aux['variable'].astype(str)\n","d_aux.index = d_aux['ID PHR']\n","d_aux.drop(columns=['ID PHR'], inplace=True)\n","\n","#d_aux.head()\n","data=data.join(other=d_aux.loc[:,['dif_fechas','etapa']], on='ID PHR', how='left')\n","#data.head()\n","data['index'] = data.index\n","data = data.drop_duplicates(subset='index', keep='first')\n","del data['index']\n","data.sort_index(inplace=True)\n","#data=data.drop(columns=['FechaDO','Fecha_fin'])\n","data=data.drop(columns=['FechaDO'])"]},{"cell_type":"markdown","source":["#####**Criación de variables de etapas**\n"],"metadata":{"id":"mVBfCR8ybET9"}},{"cell_type":"markdown","source":["\n","Esa variable crea columnas donde interesa verificar cuáles son las etapas y los tiempos entre cada una de ellas. El propósito no es clasificar los eventos, sino más bien ordenarlos desde el tiempo 0 (la fecha de publicación DO) hasta la última etapa del proceso (entre las 15 posibles), en orden cronológico.\n","\n","Así, la `etapa_1` muestra cuál fue el evento que ocurrió después de la Fecha de Publicación DO y `duracao_1` indica cuántos días han pasado hasta esa etapa. De igual manera, `etapa_2` representa el próximo evento que ocurrió y `duracao_2`.  indica cuántos días han pasado desde la `etapa_1`, y así sucesivamente hasta la última etapa.\n","\n","Cuando no hay etapas o eventos, la tabla muestra NaN para las duraciones y espacios en blanco para las etapas.\n","\n","Al final, se proporciona un ejemplo de la tabla con las primeras 3 variables de ese conjunto."],"metadata":{"id":"HJUxo3HAGYQ7"}},{"cell_type":"code","source":["columnas = {'ID PHR':'object','etapa_1':'object','duracao_1':'int64','etapa_2':'object','duracao_2':'int64','etapa_3':'object','duracao_3':'int64'\n","  ,'etapa_4':'object','duracao_4':'int64','etapa_5':'object','duracao_5':'int64','etapa_6':'object','duracao_6':'int64'\n","  ,'etapa_7':'object','duracao_7':'int64','etapa_8':'object','duracao_8':'int64','etapa_9':'object','duracao_9':'int64'\n","  ,'etapa_10':'object','duracao_10':'int64','etapa_11':'object','duracao_11':'int64','etapa_12':'object','duracao_12':'int64'\n","  ,'etapa_13':'object','duracao_13':'int64','etapa_14':'object','duracao_14':'int64','etapa_15':'object','duracao_15':'int64'}\n","etapas=pd.DataFrame(columns=columnas.keys()).astype(columnas)\n","#aux2\n","aux = data.filter(regex='^Fecha').drop(columns=['Fecha_fin'])#.sample(20).filter(regex='^Fecha')\n","#print(len(aux))\n","i=0\n","#print(aux2.iloc[i,:])\n","while i < len(aux):\n","  #print(i)\n","  #print(aux.iloc[i])\n","  aux2=(aux.iloc[i,:]).sort_values().diff().dt.days\n","  aux3 = aux2[1::]\n","  #print(aux3)\n","  etapas\n","  j=0\n","  lista=[]\n","  lista.append(aux3.name)\n","  while j <len(aux3):\n","    if np.isnan(aux3[j]) == False:\n","      lista.append(aux3.index[j])\n","      lista.append(aux3[j])\n","    else:\n","      lista.append('')\n","      lista.append(np.nan)\n","    j+=1\n","  etapas.loc[i]=lista\n","  i+=1\n","#etapas.sample(10)\n","#esa parte sirve para eliminar las variables de etapas que son completamente nulas\n","#identifica cual variable \"etapa_n\" que no contienve valores non nulos\n","a = etapas.notnull().sum().shift(-1)\n","b=a[a==0].head(1).index.to_list()\n","#acá se excluyen todas las columnas desde la que contiene valores nulos hasta la última (duracao_15)\n","etapas=etapas.drop(etapas.loc[:,str(b[0]):'duracao_15'].columns.to_list(),axis=1)\n","#renombra el valor del indice\n","etapas.index=etapas['ID PHR']\n","#exclui la columna apos definir como índice\n","etapas.drop('ID PHR',axis=1,inplace=True)"],"metadata":{"id":"JWZvortQwFw9"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#inserción de las etapas en la base de datos:\n","data = data.join(etapas,on='ID PHR',how='left')\n","data.loc[:,'etapa_1':'duracao_3'].sample(2)"],"metadata":{"id":"_kMhI_rQTRon"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["#####**Variable objetivo**\n","\n"],"metadata":{"id":"fGrRiFjeTQQl"}},{"cell_type":"markdown","source":["Según la experta del Ministerio de Vivienda y Urbanismo, el programa cuenta con 2 objetivos temporales para la entrega de los proyectos ingresados.\n","\n","Los proyectos del 'Tipo de Intervención': 'Mejoramiento' son menos complejos y deben tener una expectativa de 1 año para su conclusión y entrega. En cambio, los proyectos de 'Vivienda Nueva' abarcan más etapas y formalidades, lo que aumenta su complejidad. Para proyectos de este tipo, el objetivo del Ministerio es de 4 años entre la fecha de ingreso y la entrega.\n","\n","Con base en esta información, se creará la variable  `target` que representará 1 si el plazo de entrega fue cumplido, o 0 en caso contrario.\n","\n","Dado que se está evaluando un proceso a lo largo del tiempo, puede que algunas entradas de datos no tengan el tiempo suficiente para una evaluación total. En esos casos, serán tratados como '_censurados_' en el análisis."],"metadata":{"id":"OQaF5cqqGkXe"}},{"cell_type":"code","source":["#target=data[['Tipo de Intervención','Fecha Publicación DO','Fecha_fin','Fecha RE Renuncia / Eliminación','Fecha Término de Obra','Duracion (años)']].sample(10)\n","#Consolidación de todos los fines de proceso en una única sola columna Fecha_final\n","data['Fecha_final']=data.loc[:,['Fecha_fin','Fecha RE Renuncia / Eliminación','Fecha Término de Obra']].max(axis=1)\n","data['Duracion_total'] = (data['Fecha_final'] - data['Fecha Publicación DO']).dt.days / 365\n","#para simplificacion de visualizacion:\n","#Vivienda Nueva: objetivo < 4 años\n","regla_vivienda_nueva = (data['Tipo de Intervención']=='Vivienda Nueva') & (data['Duracion_total'] <=4)\n","#Mejoramiento: objetivo < 1 año\n","regla_mejoramiento = (data['Tipo de Intervención']=='Mejoramiento') & (data['Duracion_total'] <=1)\n","#Creación variable\n","data['target']=np.where((regla_vivienda_nueva | regla_mejoramiento),1,0)\n","data.drop(columns='Fecha_fin')\n","data[['Tipo de Intervención','Fecha Publicación DO','Fecha RE Renuncia / Eliminación','Fecha Término de Obra','Fecha_final','Duracion_total','target']].sample(10)"],"metadata":{"id":"Vath7cxgWsLi"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["#####**Variable censura**\n","\n"],"metadata":{"id":"_QCVnhGn9IsZ"}},{"cell_type":"markdown","source":["Para el análisis propuesto, es crucial identificar si el proceso experimentó una falla (es decir, si el objetivo no fue cumplido) o si el proceso todavía se encuentra dentro del plazo, pero no fue posible observar todo el tiempo debido al corte de la base de datos.\n","\n","En problemas de análisis de supervivencia, estos casos se definen como '_censurados_'.\n","\n","Para el problema en cuestión, se considerarán como censurados los siguientes casos:\n","\n","1. Casos que no presenten la `Fecha de Término de Obra`.\n","2. Casos que presenten la `Fecha RE Renuncia / Eliminación`, ya que estos indican que el proceso fue interrumpido por motivos ajenos al mismo.\n","\n","Es importante señalar que los casos que no presenten la `Fecha de Término de Obra`, pero cuya duración supere los 4 años para Vivienda Nueva (o 1 año en el caso de Mejoramiento), no serán considerados censurados. En estos casos, se trata de una situación que representa la falla del proceso."],"metadata":{"id":"RDVVvORPGo82"}},{"cell_type":"code","source":["#censura = data[['Tipo de Intervención','Fecha Término de Obra','Fecha RE Renuncia / Eliminación','Duracion_total']].sample(20)\n","#Regla Censura 1: Se Tipo de Interverción = 'Vivienda Nueva' & Fécha Termino de Obra es Nulo & Duracion_Total<=4\n","regla_censura_1 = ((data['Tipo de Intervención'] == 'Vivienda Nueva')\n","                   & (data['Fecha Término de Obra'].isnull())\n","                   & (data['Duracion_total'] <= 4))\n","#Regla Censura 2: Se Tipo de Interverción = 'Mejoramiento' & Fécha Termino de Obra es Nulo & Duracion_Total<=1\n","regla_censura_2 = ((data['Tipo de Intervención'] == 'Mejoramiento')\n","                   & (data['Fecha Término de Obra'].isnull())\n","                   & (data['Duracion_total'] <= 1))\n","#Regla Censura 3: Se Fecha RE Renuncia / Eliminación no es Nulo\n","regla_censura_3 = data['Fecha RE Renuncia / Eliminación'].notnull()\n","data['censura'] = np.where(regla_censura_1 | regla_censura_2 | regla_censura_3,1,0)\n","data[['Tipo de Intervención','Fecha Término de Obra','Fecha RE Renuncia / Eliminación','Duracion_total','censura']].sample(5)"],"metadata":{"id":"Gk0Ab2i3Cv30"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"kBwNkgC0e_ET"},"source":["\n","###**PARTE 4: Análisis exploratorio de datos**"]},{"cell_type":"markdown","source":["####Utilización de Pacote Y_data_profiling para crear un archivo de análisis descritivo completo\n","\n"],"metadata":{"id":"YCpPLSf9dEc3"}},{"cell_type":"markdown","source":["El paquete y_data_profiling permite hacer un análisis completo de las variables permitiendo encuentrar padrones de dados nulos, estadísticas básicas de las variables numéricas (max, min, promedio), además de correlaciones entre todas las variables.\n","\n","El proceso también crea gráficos de barras para cada una de las variables de la base (numéricas y categóricas).\n","\n","La salida de y_data_profiling es un archivo tipo .html interativo que permite también seleccionar las variables o visualizaciones que sean interesante para el usuário.\n","\n","Acá será demonstrado el código que generó la base y las principales conclusiones acerca del resultado.\n","\n","El archivo vá anexado a ese reporte."],"metadata":{"id":"ugLP9963Hdsj"}},{"cell_type":"code","source":["#This code creates de Profiling reports for Exploratory Analysis\n","\n","profile = ProfileReport(\n","    data,\n","    title=\"Taller Datos Python\",\n","    explorative=True,\n","    vars={\"num\": {\"low_categorical_threshold\": 0}},  # resolver problema #954\n",")\n","\n","# Problema 954:\n","# https://github.com/ydataai/pandas-profiling/issues/954\n","file = os.path.join(os.path.abspath(os.path.curdir), \"Taller_EDA.html\")\n","\n","profile.to_file(file)"],"metadata":{"id":"DDxScMW2p0DO"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["####Exclusíon de Datos II\n","\n"],"metadata":{"id":"38kKDCHuAqW-"}},{"cell_type":"markdown","source":["En esta etapa, se avalia el reporte de profiling para averiguar cuales otras mejorias se pueden obtener reduciendo la cantidad de atributos de la base de datos.\n","\n","La base procesada es exportada a un archivo plano para reducir tiempos de procesamiento de las etapas anteriores.\n","\n","Los casos que serán removidos en esta etapa serán:\n","\n","* `Fecha_complem3` por valor constante.\n","* `Fecha_fin` por valor constante.\n","* `% Avance Físico DITEC` por alta correlación con `% Avance Físico`\n","* `% Avance Físico` por alta correlación con `% Corregido`\n","* `RE 1er Albergue Transitorio` por no ser relevante\n","* `N° RE Renuncia / Eliminación` por no ser relevante\n","* `Otros Aportes Adicion.` por cantidad de nulos (>99,9%)\n","* `Origen Aportes Adicionales` por cantidad de nulos (>99,9%)\n","* `N° RE Llamado` por no ser relevante\n","* `Nombre Constructora DITEC` por ser ambíguo a `Nombre Construtora`\n","* `Fecha_incr_1`\n","* `Fecha_incr_2`\n","* `Fecha_complem_1`\n","* `Fecha_complem_2`\n","* `Fecha RE 1er Incr. Alza Materiales`\n","* `Fecha RE 2do Incr. Alza Materiales`\n","* `Fecha RE 3er Incr. Alza Materiales`\n","* `Fecha RE 1er Albergue Transitorio`\n","* `Fecha RE 2do Albergue Transitorio`\n","* `Fecha RE 3er Albergue Transitorio`\n","* Las **fechas** poseen cantidade de nulos alta y ya fueron utilizadas en la creación variables de duración de etapas\n","\n","\n"],"metadata":{"id":"luDe21g1HnWi"}},{"cell_type":"code","source":["data.drop(columns=['Fecha_complem_3','Fecha_fin','% Avance Físico DITEC','% Avance Físico','RE 1er Albergue Transitorio','N° RE Renuncia / Eliminación'\n","                   ,'Otros Aportes Adicion.','Origen Aportes Adicionales','N° RE Llamado','Nombre Constructora DITEC','Fecha_incr_1','Fecha_incr_2'\n","                   ,'Fecha_complem_1', 'Fecha_complem_2','Fecha RE 1er Incr. Alza Materiales','Fecha RE 2do Incr. Alza Materiales','Fecha RE 3er Incr. Alza Materiales'\n","                   ,'Fecha RE 1er Albergue Transitorio','Fecha RE 2do Albergue Transitorio','Fecha RE 3er Albergue Transitorio'],inplace=True)"],"metadata":{"id":"Q0Zxu-kZNvxT"},"execution_count":null,"outputs":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"K8eZhTRlqPXA"},"outputs":[],"source":["data.info()"]},{"cell_type":"code","source":["#Reducción de las variables numéricas para mejoria de performance:\n","int=list(data.select_dtypes(include=['int64']).columns)\n","data[int]=data[int].apply(lambda x: pd.to_numeric(x, downcast='integer'))\n","float=list(data.select_dtypes(include=['float64']).columns)\n","data[float]=data[float].apply(lambda x: pd.to_numeric(x, downcast='float'))\n","data.info()"],"metadata":{"id":"YxROnh_6WPRF"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["#exporta la base de datos para un archivo Excel para evitar el reprocessamiento contínuo\n","#de las etapas anteriores de procesamiento y limpeza de datos:\n","data.to_excel(\"base_PHR.xlsx\")\n","files.download(\"base_PHR.xlsx\")\n"],"metadata":{"id":"wcEJP_YBgpr7"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["####Carga de datos preprocesada"],"metadata":{"id":"6t3l-8NYeqDj"}},{"cell_type":"code","source":["uploaded = files.upload()\n","archivo = io.BytesIO(uploaded['base_PHR.xlsx'])"],"metadata":{"id":"pu_x2ihfeo2T","colab":{"base_uri":"https://localhost:8080/","height":74},"outputId":"0f94de76-65bb-4759-9562-607eb679e9d6"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","     <input type=\"file\" id=\"files-65e3f328-2d94-4188-bb92-0e91ea7ea8a6\" name=\"files[]\" multiple disabled\n","        style=\"border:none\" />\n","     <output id=\"result-65e3f328-2d94-4188-bb92-0e91ea7ea8a6\">\n","      Upload widget is only available when the cell has been executed in the\n","      current browser session. 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Proyecto                            44264 non-null  float32       \n"," 14  Total Complem.                                    44264 non-null  float32       \n"," 15  Total Aporte MINVU Original                       44264 non-null  float32       \n"," 16  Total Aporte MINVU Final (incluye incrementos)    44264 non-null  float32       \n"," 17  Total Disponible Proyecto (incl. ahorro familia)  44264 non-null  float32       \n"," 18  Proyección Inicio Obra (año/semestre)             2911 non-null   object        \n"," 19  Incremento Requerido para Iniciar Obras           1063 non-null   object        \n"," 20  Fecha RE Aprobación Proyecto                      26616 non-null  datetime64[ns]\n"," 21  Fecha Acta Entrega Terreno                        23504 non-null  datetime64[ns]\n"," 22  Nombre Constructora                               15214 non-null  object        \n"," 23  Fecha Término de Obra                             12219 non-null  datetime64[ns]\n"," 24  Cumple Término PEH                                5504 non-null   object        \n"," 25  ESTADO PROYECTO                                   44264 non-null  object        \n"," 26  ESTADO PROYECTO DITEC                             44247 non-null  object        \n"," 27  SUBESTADO PROYECTO DITEC                          44247 non-null  object        \n"," 28  % Corregido                                       44087 non-null  float32       \n"," 29  Estado beneficiario DITEC                         44247 non-null  object        \n"," 30  Fecha RE Renuncia / Eliminación                   1299 non-null   datetime64[ns]\n"," 31  Observación DPH                                   2090 non-null   object        \n"," 32  Observación Región                                1546 non-null   object        \n"," 33  Monto Incr. Obra                                  1549 non-null   float32       \n"," 34  Concepto Incremento Obra                          1472 non-null   object        \n"," 35  Total Incremento                                  44264 non-null  float32       \n"," 36  Total Alza Materiales                             44264 non-null  float32       \n"," 37  Total Albergue Transitorio                        44264 non-null  int16         \n"," 38  Duracion (años)                                   12219 non-null  float32       \n"," 39  cantidad_etapas                                   44264 non-null  int8          \n"," 40  dif_fechas                                        44264 non-null  int32         \n"," 41  etapa                                             44264 non-null  object        \n"," 42  etapa_1                                           28444 non-null  object        \n"," 43  duracao_1                                         28444 non-null  float32       \n"," 44  etapa_2                                           25296 non-null  object        \n"," 45  duracao_2                                         25296 non-null  float32       \n"," 46  etapa_3                                           20426 non-null  object        \n"," 47  duracao_3                                         20426 non-null  float32       \n"," 48  etapa_4                                           7162 non-null   object        \n"," 49  duracao_4                                         7162 non-null   float32       \n"," 50  etapa_5                                           1996 non-null   object        \n"," 51  duracao_5                                         1996 non-null   float32       \n"," 52  etapa_6                                           568 non-null    object        \n"," 53  duracao_6                                         568 non-null    float32       \n"," 54  etapa_7                                           119 non-null    object        \n"," 55  duracao_7                                         119 non-null    float32       \n"," 56  Fecha_final                                       44264 non-null  datetime64[ns]\n"," 57  Duracion_total                                    44264 non-null  float32       \n"," 58  target                                            44264 non-null  int8          \n"," 59  censura                                           44264 non-null  int8          \n","dtypes: datetime64[ns](6), float32(21), int16(2), int32(1), int8(3), object(27)\n","memory usage: 15.2+ MB\n"]}]},{"cell_type":"markdown","metadata":{"id":"g2cVp1Xee_ET"},"source":["Se presenta un análisis inicial de la base de datos que, tras haber pasado por el proceso de Extracción, Transformación y Carga (ETL), ahora consta de 44,264 registros y 60 variables.\n","\n","Con respecto a los datos nulos, es importante destacar que las variables más relevantes para este estudio se encuentran completas. Esto incluye la identificación del tipo de subsidio, abarcando variables como \"Tipo de Intervención,\" \"Tipología Madre\" y \"Tipo de Expediente.\"\n","\n","Además, otras variables de gran relevancia están relacionadas con la ubicación geográfica de los subsidios, tales como \"Región de Ejecución,\" \"Provincia,\" \"Comuna\" y \"Localidad.\" Estas variables son críticas para comprender la distribución geográfica de los subsidios y su impacto en diferentes áreas.\n","\n","Finalmente, las variables que informan sobre el estado del proyecto y las fechas que marcan los hitos del proceso de cada subsidio son igualmente esenciales. Estas variables permitirán al proyecto llevar a cabo análisis en profundidad y responder de manera efectiva a las preguntas planteadas, ya que proporcionarán información detallada sobre el progreso y desarrollo de los proyectos de subsidio.\n","\n","\n","\n","\n","\n"]},{"cell_type":"markdown","metadata":{"id":"TrmCbgJMxIv1"},"source":["#### Análisis de los componentes del Programa de Habitabilidad Rural\n","\n"]},{"cell_type":"markdown","metadata":{"id":"AGAgOb_1EdZp"},"source":["\n","En el análisis de los datos, se observa que la variable \"Tipo de Intervención\" se divide en dos categorías principales: \"Vivienda Nueva\" con una frecuencia de 23,093, representando el 52.17% de los casos, y \"Mejoramiento\" con una frecuencia de 21,171, que equivale al 47.83% de los casos. Esto sugiere que la mayoría de los registros corresponden a proyectos de \"Vivienda Nueva,\" mientras que el resto se refiere a proyectos de \"Mejoramiento.\" Estos hallazgos son fundamentales para comprender la distribución de los tipos de intervención en la base de datos.\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"R5z-x8vrUT4E","colab":{"base_uri":"https://localhost:8080/","height":112},"outputId":"7b6a2b5f-e474-413b-f8ac-328de2e0a1a2"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["                Frecuencia  Proporción\n","Vivienda Nueva       23093       52.17\n","Mejoramiento         21171       47.83"],"text/html":["\n","  <div id=\"df-3b3bba39-70fb-47ad-9d58-6e61fbf023e2\" 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 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>Frecuencia</th>\n","      <th>Proporción</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Vivienda Nueva</th>\n","      <td>23093</td>\n","      <td>52.17</td>\n","    </tr>\n","    <tr>\n","      <th>Mejoramiento</th>\n","      <td>21171</td>\n","      <td>47.83</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3b3bba39-70fb-47ad-9d58-6e61fbf023e2')\"\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 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\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","    .colab-df-buttons div {\n","      margin-bottom: 4px;\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-3b3bba39-70fb-47ad-9d58-6e61fbf023e2 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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La mayoría de ellos son de tipo \"Colectivo\" (11,329), seguidos por una cantidad significativa de proyectos \"Individual\" (5,948).\n","\n","La categoría \"MAVE\" (mejoramiento y/o Ampliacion de Vivienda Existente)  cuenta con un total de 20,172 proyectos. La gran mayoría son \"Colectivos\" (16,760), seguidos por proyectos \"Individual\" (3,412).\n","\n","En la categoría \"MEEC\"v (Mejoramiento del Entorno y Equipamiento Comunitario)  se registra un total de 999 proyectos, y todos ellos son de tipo \"Colectivo.\" ya que la normativa no permite proyectos de tipo \"Individual\" en esta modalidad.\n","\n","En resumen, este análisis revela la distribución de proyectos según su \"Tipología Madre\" y el \"Tipo de Expediente.\" La mayoría de los proyectos en estas categorías son de tipo \"Colectivo,\" con un número muy limitado de proyectos \"Individual.\" Esto proporciona información útil para comprender la estructura de los proyectos."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"iZCsETd9EB1y","outputId":"b222a1ce-8af5-4eab-d439-433ee7ba5114","colab":{"base_uri":"https://localhost:8080/","height":238}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["                        Subsidios  Proporción\n","OBRA TERMINADA              12217       27.60\n","OBRA EN EJECUCIÓN           11249       25.41\n","PROYECTO APROBADO            6806       15.38\n","SIN PROYECTO INGRESADO       6743       15.23\n","PROYECTO EN EVALUACIÓN       5638       12.74\n","ELIMINADO/RENUNCIADO         1611        3.64"],"text/html":["\n","  <div id=\"df-00d40863-adf0-4a10-a1fb-a03a08257a92\" 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 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>Subsidios</th>\n","      <th>Proporción</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>OBRA TERMINADA</th>\n","      <td>12217</td>\n","      <td>27.60</td>\n","    </tr>\n","    <tr>\n","      <th>OBRA EN EJECUCIÓN</th>\n","      <td>11249</td>\n","      <td>25.41</td>\n","    </tr>\n","    <tr>\n","      <th>PROYECTO APROBADO</th>\n","      <td>6806</td>\n","      <td>15.38</td>\n","    </tr>\n","    <tr>\n","      <th>SIN PROYECTO INGRESADO</th>\n","      <td>6743</td>\n","      <td>15.23</td>\n","    </tr>\n","    <tr>\n","      <th>PROYECTO EN EVALUACIÓN</th>\n","      <td>5638</td>\n","      <td>12.74</td>\n","    </tr>\n","    <tr>\n","      <th>ELIMINADO/RENUNCIADO</th>\n","      <td>1611</td>\n","      <td>3.64</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-00d40863-adf0-4a10-a1fb-a03a08257a92')\"\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 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\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","    .colab-df-buttons div {\n","      margin-bottom: 4px;\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-00d40863-adf0-4a10-a1fb-a03a08257a92 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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La categoría \"Obra Terminada\" cuenta con la frecuencia más alta, representando el 27.60% de los casos, seguida de cerca por \"Obra en Ejecución,\" que abarca el 25.41%. \"Proyecto Aprobado\" y \"Sin Proyecto Ingresado\" constituyen el 15.38% y el 15.23% de los registros, respectivamente. Mientras tanto, \"Proyecto en Evaluación\" comprende el 12.74% de los casos, y \"Eliminado/Renunciado\" representa el 3.64%. Estos resultados indican que la mayoría de los subsidios en la base de datos se encuentran en etapas de \"Obra Terminada\" o \"Obra en Ejecución,\" mientras que las categorías \"Proyecto Aprobado\" y \"Sin Proyecto Ingresado\" también tienen una representación significativa. Las categorías restantes, aunque menos frecuentes, también aportan información valiosa sobre el estado de los proyectos de subsidio."]},{"cell_type":"code","execution_count":null,"metadata":{"id":"1bz9NUjGHOM2","colab":{"base_uri":"https://localhost:8080/","height":300},"outputId":"52fe2256-f54f-4627-e595-08e10f320ab7"},"outputs":[{"output_type":"execute_result","data":{"text/plain":["Tipología Madre          CCH    CSR   MAVE  MEEC    All\n","ESTADO PROYECTO                                        \n","ELIMINADO/RENUNCIADO     166    526    906    13   1611\n","OBRA EN EJECUCIÓN       1458   4493   5298     0  11249\n","OBRA TERMINADA          1162   4340   6630    85  12217\n","PROYECTO APROBADO         27   3666   3046    67   6806\n","PROYECTO EN EVALUACIÓN  1106   2286   1920   326   5638\n","SIN PROYECTO INGRESADO  1897   1966   2372   508   6743\n","All                     5816  17277  20172   999  44264"],"text/html":["\n","  <div id=\"df-1f9e074a-3dd8-4950-be87-bf776041ca40\" 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Los tipos \"CCH\" (Construccion de Conjunto Habitacional) y \"CSR\" (Construccion en Sitio del Residente) también tienen una presencia considerable en varios estados, mientras que \"MEEC\" es menos común en general.\n"]},{"cell_type":"markdown","metadata":{"id":"IJ_jeEjqxfmk"},"source":["#### Análisis Territorial del Programa de Habitabilidad Rural\n"]},{"cell_type":"markdown","metadata":{"id":"OOUNPAK0NLVk"},"source":["Este resultado refleja la distribución de los subsidios según la variable \"Región de Ejecución\". La región de La Araucanía tiene la mayor cantidad de registros con 11,221 beneficiarios, seguida de Maule con 7,667 y Ñuble con 6,275. En contraste, las regiones de Arica y Antofagasta tienen la menor representación con 34 y 75 casos, respectivamente. Estos datos indican que la mayoría de los registros provienen de las regiones de Araucanía, Maule y Ñuble, lo que puede ser relevante para analizar la distribución geográfica de los proyectos en la base de datos."]},{"cell_type":"code","source":["# Calcular frecuencias\n","subsidios_region = data['Región Ejecución'].value_counts()\n","\n","df_subsidios_region = pd.DataFrame(subsidios_region)\n","df_subsidios_region"],"metadata":{"id":"6MNaLXIioXi-","outputId":"949d7abd-6dd4-43fd-e9c5-370a095704c6","colab":{"base_uri":"https://localhost:8080/","height":551}},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["               Región Ejecución\n","Araucanía                 11221\n","Maule                      7667\n","Ñuble                      6275\n","Los Lagos                  3391\n","Los Ríos                   3348\n","Biobío                     2582\n","O'higgins                  2200\n","Metropolitana              2173\n","Valparaíso                 2109\n","Coquimbo                   1925\n","Aysén                       803\n","Atacama                     276\n","Magallanes                   93\n","Tarapacá                     92\n","Antofagasta                  75\n","Arica                        34"],"text/html":["\n","  <div id=\"df-47e4c053-9783-45f5-881f-b4ef80fccf85\" 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 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>Región Ejecución</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Araucanía</th>\n","      <td>11221</td>\n","    </tr>\n","    <tr>\n","      <th>Maule</th>\n","      <td>7667</td>\n","    </tr>\n","    <tr>\n","      <th>Ñuble</th>\n","      <td>6275</td>\n","    </tr>\n","    <tr>\n","      <th>Los Lagos</th>\n","      <td>3391</td>\n","    </tr>\n","    <tr>\n","      <th>Los Ríos</th>\n","      <td>3348</td>\n","    </tr>\n","    <tr>\n","      <th>Biobío</th>\n","      <td>2582</td>\n","    </tr>\n","    <tr>\n","      <th>O'higgins</th>\n","      <td>2200</td>\n","    </tr>\n","    <tr>\n","      <th>Metropolitana</th>\n","      <td>2173</td>\n","    </tr>\n","    <tr>\n","      <th>Valparaíso</th>\n","      <td>2109</td>\n","    </tr>\n","    <tr>\n","      <th>Coquimbo</th>\n","      <td>1925</td>\n","    </tr>\n","    <tr>\n","      <th>Aysén</th>\n","      <td>803</td>\n","    </tr>\n","    <tr>\n","      <th>Atacama</th>\n","      <td>276</td>\n","    </tr>\n","    <tr>\n","      <th>Magallanes</th>\n","      <td>93</td>\n","    </tr>\n","    <tr>\n","      <th>Tarapacá</th>\n","      <td>92</td>\n","    </tr>\n","    <tr>\n","      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Por otro lado, regiones como Arica y Magallanes tienen una presencia más limitada en la base de datos, con un número considerablemente menor de proyectos, y en algunos casos, los proyectos se encuentran en la etapa de \"Proyecto en Evaluación\" o \"Sin Proyecto Ingresado.\"\n","\n","Este análisis detallado de la distribución de proyectos según el estado y la región de ejecución brinda información valiosa para comprender cómo están distribuidos geográficamente y en qué etapas se encuentran. Además, se observa que la categoría \"Eliminado/Renunciado\" está presente en varias regiones, lo que podría requerir una evaluación adicional para comprender las razones detrás de estos proyectos en ese estado"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"1dGBMFje6rbw","outputId":"bb7f6479-1191-4f07-f953-d77c62ad7089","colab":{"base_uri":"https://localhost:8080/","height":600}},"outputs":[{"output_type":"execute_result","data":{"text/plain":["ESTADO PROYECTO Región Ejecución  ELIMINADO/RENUNCIADO  OBRA EN EJECUCIÓN  \\\n","0                    Antofagasta                    14                  0   \n","1                      Araucanía                   289               2218   \n","2                          Arica                     0                  0   \n","3                        Atacama                    16                128   \n","4                          Aysén                    98                185   \n","5                         Biobío                    52                829   \n","6                       Coquimbo                    98                241   \n","7                      Los Lagos                   138                471   \n","8                       Los Ríos                    85                733   \n","9                     Magallanes                     5                  0   \n","10                         Maule                   326               1938   \n","11                 Metropolitana                   187                381   \n","12                     O'higgins                    87                475   \n","13                      Tarapacá                     1                  3   \n","14                    Valparaíso                   173                556   \n","15                         Ñuble                    42               3091   \n","16                           All                  1611              11249   \n","\n","ESTADO PROYECTO  OBRA TERMINADA  PROYECTO APROBADO  PROYECTO EN EVALUACIÓN  \\\n","0                            23                 34                       0   \n","1                          2891               2141                    1880   \n","2                             0                  0                      34   \n","3                           114                  1                       1   \n","4                           337                118                      60   \n","5                           338                395                     418   \n","6                           589                148                     437   \n","7                          1222                734                     384   \n","8                          1053                358                     855   \n","9                            15                  0                      73   \n","10                         2895                662                     450   \n","11                          903                432                     104   \n","12                          301                121                     449   \n","13                           30                  0                      21   \n","14                          613                310                     244   \n","15                          893               1352                     228   \n","16                        12217               6806                    5638   \n","\n","ESTADO PROYECTO  SIN PROYECTO INGRESADO    All  \n","0                                     4     75  \n","1                                  1802  11221  \n","2                                     0     34  \n","3                                    16    276  \n","4                                     5    803  \n","5                                   550   2582  \n","6                                   412   1925  \n","7                                   442   3391  \n","8                                   264   3348  \n","9                                     0     93  \n","10                                 1396   7667  \n","11                                  166   2173  \n","12                                  767   2200  \n","13                                   37     92  \n","14                                  213   2109  \n","15                                  669   6275  \n","16                                 6743  44264  "],"text/html":["\n","  <div id=\"df-db8f30a4-2906-4ce8-9446-76916d83cb54\" 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 th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th>ESTADO PROYECTO</th>\n","      <th>Región Ejecución</th>\n","      <th>ELIMINADO/RENUNCIADO</th>\n","      <th>OBRA EN EJECUCIÓN</th>\n","      <th>OBRA TERMINADA</th>\n","      <th>PROYECTO APROBADO</th>\n","      <th>PROYECTO EN EVALUACIÓN</th>\n","      <th>SIN PROYECTO INGRESADO</th>\n","      <th>All</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>Antofagasta</td>\n","      <td>14</td>\n","      <td>0</td>\n","      <td>23</td>\n","      <td>34</td>\n","      <td>0</td>\n","      <td>4</td>\n","      <td>75</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>Araucanía</td>\n","      <td>289</td>\n","      <td>2218</td>\n","      <td>2891</td>\n","      <td>2141</td>\n","      <td>1880</td>\n","      <td>1802</td>\n","      <td>11221</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>Arica</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>34</td>\n","      <td>0</td>\n","      <td>34</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>Atacama</td>\n","      <td>16</td>\n","      <td>128</td>\n","      <td>114</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>16</td>\n","      <td>276</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>Aysén</td>\n","      <td>98</td>\n","      <td>185</td>\n","      <td>337</td>\n","      <td>118</td>\n","      <td>60</td>\n","      <td>5</td>\n","      <td>803</td>\n","    </tr>\n","    <tr>\n","      <th>5</th>\n","      <td>Biobío</td>\n","      <td>52</td>\n","      <td>829</td>\n","      <td>338</td>\n","      <td>395</td>\n","      <td>418</td>\n","      <td>550</td>\n","      <td>2582</td>\n","    </tr>\n","    <tr>\n","      <th>6</th>\n","      <td>Coquimbo</td>\n","      <td>98</td>\n","      <td>241</td>\n","      <td>589</td>\n","      <td>148</td>\n","      <td>437</td>\n","      <td>412</td>\n","      <td>1925</td>\n","    </tr>\n","    <tr>\n","      <th>7</th>\n","      <td>Los Lagos</td>\n","      <td>138</td>\n","      <td>471</td>\n","      <td>1222</td>\n","      <td>734</td>\n","      <td>384</td>\n","      <td>442</td>\n","      <td>3391</td>\n","    </tr>\n","    <tr>\n","      <th>8</th>\n","      <td>Los Ríos</td>\n","      <td>85</td>\n","      <td>733</td>\n","      <td>1053</td>\n","      <td>358</td>\n","      <td>855</td>\n","      <td>264</td>\n","      <td>3348</td>\n","    </tr>\n","    <tr>\n","      <th>9</th>\n","      <td>Magallanes</td>\n","      <td>5</td>\n","      <td>0</td>\n","      <td>15</td>\n","      <td>0</td>\n","      <td>73</td>\n","      <td>0</td>\n","      <td>93</td>\n","    </tr>\n","    <tr>\n","      <th>10</th>\n","      <td>Maule</td>\n","      <td>326</td>\n","      <td>1938</td>\n","      <td>2895</td>\n","      <td>662</td>\n","      <td>450</td>\n","      <td>1396</td>\n","      <td>7667</td>\n","    </tr>\n","    <tr>\n","      <th>11</th>\n","      <td>Metropolitana</td>\n","      <td>187</td>\n","      <td>381</td>\n","      <td>903</td>\n","      <td>432</td>\n","      <td>104</td>\n","      <td>166</td>\n","      <td>2173</td>\n","    </tr>\n","    <tr>\n","      <th>12</th>\n","      <td>O'higgins</td>\n","      <td>87</td>\n","      <td>475</td>\n","      <td>301</td>\n","      <td>121</td>\n","      <td>449</td>\n","      <td>767</td>\n","      <td>2200</td>\n","    </tr>\n","    <tr>\n","      <th>13</th>\n","      <td>Tarapacá</td>\n","      <td>1</td>\n","      <td>3</td>\n","      <td>30</td>\n","      <td>0</td>\n","      <td>21</td>\n","      <td>37</td>\n","      <td>92</td>\n","    </tr>\n","    <tr>\n","      <th>14</th>\n","      <td>Valparaíso</td>\n","      <td>173</td>\n","      <td>556</td>\n","      <td>613</td>\n","      <td>310</td>\n","      <td>244</td>\n","      <td>213</td>\n","      <td>2109</td>\n","    </tr>\n","    <tr>\n","      <th>15</th>\n","      <td>Ñuble</td>\n","      <td>42</td>\n","      <td>3091</td>\n","      <td>893</td>\n","      <td>1352</td>\n","      <td>228</td>\n","      <td>669</td>\n","      <td>6275</td>\n","    </tr>\n","    <tr>\n","      <th>16</th>\n","      <td>All</td>\n","      <td>1611</td>\n","      <td>11249</td>\n","      <td>12217</td>\n","      <td>6806</td>\n","      <td>5638</td>\n","      <td>6743</td>\n","      <td>44264</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-db8f30a4-2906-4ce8-9446-76916d83cb54')\"\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 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    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A su vez, cada región se presenta con la cantidad de proyectos demendados del tipo \"Vivienda nueva\" y \"Mejoramiento\".\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"K3THjzAutAsc","outputId":"ca80cb2f-b942-440a-a6fa-9e424998f768","colab":{"base_uri":"https://localhost:8080/","height":717}},"outputs":[{"output_type":"display_data","data":{"text/html":["<html>\n","<head><meta charset=\"utf-8\" /></head>\n","<body>\n","    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n","        <script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-2.24.1.min.js\"></script>                <div 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'Arica']\n","orden_especifico_estado_proyecto = ['SIN PROYECTO INGRESADO', 'PROYECTO EN EVALUACIÓN', 'PROYECTO APROBADO', 'OBRA EN EJECUCIÓN', 'OBRA TERMINADA', 'ELIMINADO/RENUNCIADO']\n","\n","crosstab_result = pd.crosstab(data['Región Ejecución'], data['ESTADO PROYECTO'], margins=True).reset_index()\n","\n","# Convierte el resultado en un DataFrame y restablece los índices\n","df_heatmap = pd.DataFrame(crosstab_result)\n","\n","# Elimina la última fila (All) que contiene el total\n","df_heatmap = df_heatmap.iloc[:-1]\n","\n","# Elimina la última columna (All) que contiene el total\n","df_heatmap = df_heatmap.iloc[:, :-1]\n","\n","# Recupera la columna 'Región Ejecución'\n","#df_heatmap['Región Ejecución'] = region_column\n","\n","# Ordena la columna 'Región Ejecución' según el orden específico\n","df_heatmap['Región Ejecución'] = pd.Categorical(df_heatmap['Región Ejecución'], categories=orden_especifico_regiones, ordered=True)\n","df_heatmap = df_heatmap.sort_values('Región 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Esta relación de asignación se evidencia a través de la asignación de colores diferentes a las áreas geográficas según su desempeño. Las áreas con más Subsidios asignados  destacan en colores calidos, mientras que los terriotorios desfavorecidas se destacan en colores frios."]},{"cell_type":"code","source":["\n","\n","# Tu DataFrame original\n","mapa_chile = {\n","    'Región Ejecución': ['Araucanía', 'Maule', 'Ñuble', 'Los Lagos', 'Los Ríos', 'Biobío', \"O'Higgins\", 'Metropolitana', 'Valparaíso', 'Coquimbo', 'Aysén', 'Atacama', 'Magallanes', 'Tarapacá', 'Antofagasta', 'Arica'],\n","    'Longitud': [-72.331113, -71.663052, -72.085266, -73.429945, -72.498180, -73.051162, -71.481101, -70.648921, -71.141128, -71.337116, -72.141346, -70.328648, -70.903694, -69.127321, -69.336438, -70.321258],\n","    'Latitud': [-38.948290, -35.457834, -36.624533, -41.386588, -39.927567, -36.819894, -34.663655, -33.462456, -32.919042, -29.959104, -45.526300, -27.376232, -53.162590, -20.218180, -24.776108, -18.478518],\n","    'Estado Proyecto': 'Total',\n","}\n","\n","df_puntos = pd.DataFrame(mapa_chile)\n","\n","# Calcular la cantidad de proyectos por región\n","proyectos_por_region = data['Región Ejecución'].value_counts().reset_index()\n","proyectos_por_region.columns = ['Región Ejecución', 'Cantidad de Proyectos']\n","\n","# Agregar una columna que muestre el estado del proyecto en cada región\n","proyectos_por_region['Estado del Proyecto'] = df_puntos.groupby('Región Ejecución')['Estado Proyecto'].first().values\n","\n","# Variable de color basada en la cantidad de proyectos\n","color_variable = proyectos_por_region['Cantidad de Proyectos']\n","\n","fig = go.Figure()\n","\n","# Agregar capa de regiones\n","fig.add_trace(\n","    go.Choroplethmapbox(\n","        geojson=subsidios_region,\n","        locations=df_puntos['Región Ejecución'],\n","        z=color_variable,  # Usar la cantidad de proyectos por región para determinar el color de los círculos\n","        text=proyectos_por_region['Región Ejecución'],  # Muestra el nombre de la región en el mapa\n","        colorscale=\"Viridis\",\n","        colorbar_title=\"Cantidad de Proyectos\",\n","    )\n",")\n","\n","# Agregar marcadores para los puntos\n","fig.add_trace(\n","    go.Scattermapbox(\n","        lat=df_puntos['Latitud'],\n","        lon=df_puntos['Longitud'],\n","        mode='markers',\n","        marker=dict(\n","            size=10,  # Tamaño de los círculos\n","            color=color_variable,\n","            colorscale=\"Bluered\",\n","            opacity=0.7,\n","            colorbar=dict(title=\"Cantidad de Proyectos\"),\n","        ),\n","        text=proyectos_por_region['Estado del Proyecto'] + ' - ' + proyectos_por_region['Cantidad de Proyectos'].astype(str),  # Muestra el estado del proyecto y la cantidad de proyectos en la región\n","    )\n",")\n","\n","fig.update_layout(\n","    mapbox_style=\"carto-positron\",\n","    mapbox_zoom=3.5,  # Ajusta el nivel de zoom según tus necesidades\n","    mapbox_center={\"lat\": -35, \"lon\": -70},  # Coordenadas para centrar el mapa en Chile\n","    title=\"Cantidad de asignacion de subsidio del Programa de Habitabilidad Rural a nivel nacional\",\n",")\n","\n","# Configurar la información emergente de los círculos\n","fig.update_traces(\n","    hoverinfo='text'\n",")\n","\n","fig.show()\n"],"metadata":{"id":"oft4j6D9cCwX","outputId":"1752ce1f-bc98-42e0-c2c1-587ff0f6f260","colab":{"base_uri":"https://localhost:8080/","height":542}},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/html":["<html>\n","<head><meta charset=\"utf-8\" /></head>\n","<body>\n","    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n","        <script charset=\"utf-8\" 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de asignacion de subsidio del Programa de Habitabilidad Rural a nivel nacional\"}},                        {\"responsive\": true}                    ).then(function(){\n","                            \n","var gd = document.getElementById('b8359f6c-73bd-4804-9a3b-0a789eafceef');\n","var x = new MutationObserver(function (mutations, observer) {{\n","        var display = window.getComputedStyle(gd).display;\n","        if (!display || display === 'none') {{\n","            console.log([gd, 'removed!']);\n","            Plotly.purge(gd);\n","            observer.disconnect();\n","        }}\n","}});\n","\n","// Listen for the removal of the full notebook cells\n","var notebookContainer = gd.closest('#notebook-container');\n","if (notebookContainer) {{\n","    x.observe(notebookContainer, {childList: true});\n","}}\n","\n","// Listen for the clearing of the current output cell\n","var outputEl = gd.closest('.output');\n","if (outputEl) {{\n","    x.observe(outputEl, {childList: 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Además, se percibe que, teniendo a la Araucanía como punto central, los proyectos se vuelven más escasos a medida que nos desplazamos hacia las regiones más extremas de la región central.\n","\n","Desde el punto de vista de las necesidades económicas, las decisiones son acertadas, ya que estas regiones son las que tienen una cantidad razonable de población y los índices más bajos de Índice de Desarrollo Humano (IDH), según la tabla de IDH por regiones disponible en el sitio de Wikipedia."],"metadata":{"id":"KtZn6Rsoj0CF"}},{"cell_type":"markdown","source":["<table class=\"wikitable sortable col1izq col2cen col3cen col4cen col5cen col6cen col7cen jquery-tablesorter\">\n","\n","<thead><tr>\n","<th class=\"headerSort\" tabindex=\"0\" role=\"columnheader button\" title=\"Orden ascendente\">Región\n","</th>\n","<th class=\"headerSort\" tabindex=\"0\" role=\"columnheader button\" title=\"Orden ascendente\">IDH 1990<sup id=\"cite_ref-Radboud_University,_2019_1-0\" class=\"reference separada\"><a href=\"#cite_note-Radboud_University,_2019-1\"><span class=\"corchete-llamada\">[</span>1<span class=\"corchete-llamada\">]</span></a></sup>​\n","</th>\n","<th class=\"headerSort\" tabindex=\"0\" role=\"columnheader button\" title=\"Orden ascendente\">IDH 2000<sup id=\"cite_ref-Radboud_University,_2019_1-1\" class=\"reference separada\"><a href=\"#cite_note-Radboud_University,_2019-1\"><span class=\"corchete-llamada\">[</span>1<span class=\"corchete-llamada\">]</span></a></sup>​\n","</th>\n","<th class=\"headerSort\" tabindex=\"0\" role=\"columnheader button\" title=\"Orden ascendente\">IDH 2010<sup id=\"cite_ref-Radboud_University,_2019_1-2\" class=\"reference separada\"><a href=\"#cite_note-Radboud_University,_2019-1\"><span class=\"corchete-llamada\">[</span>1<span class=\"corchete-llamada\">]</span></a></sup>​\n","</th>\n","<th class=\"headerSort\" tabindex=\"0\" role=\"columnheader button\" title=\"Orden ascendente\">IDH 2019<sup id=\"cite_ref-Radboud_University,_2019_1-3\" class=\"reference separada\"><a href=\"#cite_note-Radboud_University,_2019-1\"><span class=\"corchete-llamada\">[</span>1<span class=\"corchete-llamada\">]</span></a></sup>​\n","</th>\n","<th class=\"headerSort headerSortUp\" tabindex=\"0\" role=\"columnheader button\" title=\"Orden descendente\"><b>IDH 2021<sup id=\"cite_ref-:12_2-0\" class=\"reference separada\"><a href=\"#cite_note-:12-2\"><span class=\"corchete-llamada\">[</span>2<span class=\"corchete-llamada\">]</span></a></sup>​</b>\n","</th>\n","<th class=\"headerSort\" tabindex=\"0\" role=\"columnheader button\" title=\"Orden ascendente\">Población (2017)<sup id=\"cite_ref-Censo_2017_3-0\" class=\"reference separada\"><a href=\"#cite_note-Censo_2017-3\"><span class=\"corchete-llamada\">[</span>3<span class=\"corchete-llamada\">]</span></a></sup>​\n","</th>\n","<th class=\"headerSort\" tabindex=\"0\" role=\"columnheader button\" title=\"Orden ascendente\">País comparable\n","</th></tr></thead><tbody>\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","\n","<tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_La_Araucan%C3%ADa_Region.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de La Araucanía\"><img alt=\"Bandera de la Región de La Araucanía\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/f/fd/Flag_of_La_Araucan%C3%ADa_Region.svg/20px-Flag_of_La_Araucan%C3%ADa_Region.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/f/fd/Flag_of_La_Araucan%C3%ADa_Region.svg/30px-Flag_of_La_Araucan%C3%ADa_Region.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/f/fd/Flag_of_La_Araucan%C3%ADa_Region.svg/40px-Flag_of_La_Araucan%C3%ADa_Region.svg.png 2x\" data-file-width=\"1136\" data-file-height=\"756\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_La_Araucan%C3%ADa\" title=\"Región de La Araucanía\">Araucanía</a></b>\n","</th>\n","<td style=\"color:#FFFF00\"><b>0,651</b>\n","</td>\n","<td style=\"color:#FFFF00;\"><b>0,699</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,742</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,786</b>\n","</td>\n","<td><b><span style=\"color: #32CD32\">0,790</span></b>\n","</td>\n","<td>957 224\n","</td>\n","<td><span style=\"display:none;\">Cuba</span><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/b/bd/Flag_of_Cuba.svg/20px-Flag_of_Cuba.svg.png\" decoding=\"async\" width=\"20\" height=\"10\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/b/bd/Flag_of_Cuba.svg/30px-Flag_of_Cuba.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/b/bd/Flag_of_Cuba.svg/40px-Flag_of_Cuba.svg.png 2x\" data-file-width=\"1200\" data-file-height=\"600\"></span></span>&nbsp;</span><a href=\"/wiki/Cuba\" title=\"Cuba\">Cuba</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Maule,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región del Maule\"><img alt=\"Bandera de la Región del Maule\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/6/6a/Flag_of_Maule%2C_Chile.svg/20px-Flag_of_Maule%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/6/6a/Flag_of_Maule%2C_Chile.svg/30px-Flag_of_Maule%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/6/6a/Flag_of_Maule%2C_Chile.svg/40px-Flag_of_Maule%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_del_Maule\" title=\"Región del Maule\">Maule</a></b>\n","</th>\n","<td style=\"color:#FFFF00;\"><b>0,655</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,702</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,746</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,790</b>\n","</td>\n","<td><b><span style=\"color: #32CD32\">0,794</span></b>\n","</td>\n","<td>1 044 950\n","</td>\n","<td><span style=\"display:none;\">Albania</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/20px-Flag_of_Albania.svg.png\" decoding=\"async\" width=\"20\" height=\"14\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/30px-Flag_of_Albania.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/40px-Flag_of_Albania.svg.png 2x\" data-file-width=\"700\" data-file-height=\"500\"></span></span> <a href=\"/wiki/Albania\" title=\"Albania\">Albania</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Los_Lagos_Region,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Los Lagos\"><img alt=\"Bandera de la Región de Los Lagos\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/16/Flag_of_Los_Lagos_Region%2C_Chile.svg/20px-Flag_of_Los_Lagos_Region%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/16/Flag_of_Los_Lagos_Region%2C_Chile.svg/30px-Flag_of_Los_Lagos_Region%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/1/16/Flag_of_Los_Lagos_Region%2C_Chile.svg/40px-Flag_of_Los_Lagos_Region%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Los_Lagos\" title=\"Región de Los Lagos\">Los Lagos</a></b>\n","</th>\n","<td style=\"color:#FFFF00;\"><b>0,659</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,706</b>\n","</td>\n","<td style=\"color:#00F900;;\"><b>0,750</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,795</b>\n","</td>\n","<td><b><span style=\"color: #32CD32\">0,799</span></b>\n","</td>\n","<td>828 708\n","</td>\n","<td><span style=\"display:none;\">Albania</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/20px-Flag_of_Albania.svg.png\" decoding=\"async\" width=\"20\" height=\"14\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/30px-Flag_of_Albania.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/40px-Flag_of_Albania.svg.png 2x\" data-file-width=\"700\" data-file-height=\"500\"></span></span> <a href=\"/wiki/Albania\" title=\"Albania\">Albania</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Los_R%C3%ADos,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Los Ríos\"><img alt=\"Bandera de la Región de Los Ríos\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/a/ac/Flag_of_Los_R%C3%ADos%2C_Chile.svg/20px-Flag_of_Los_R%C3%ADos%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/a/ac/Flag_of_Los_R%C3%ADos%2C_Chile.svg/30px-Flag_of_Los_R%C3%ADos%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/a/ac/Flag_of_Los_R%C3%ADos%2C_Chile.svg/40px-Flag_of_Los_R%C3%ADos%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Los_R%C3%ADos\" title=\"Región de Los Ríos\">Los Ríos</a></b>\n","</th>\n","<td colspan=\"2\"><center><i><small>Perteneciente a Los Lagos</small></i></center>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,750</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,795</b>\n","</td>\n","<td><b><span style=\"color: #32CD32\">0,799</span></b>\n","</td>\n","<td>384 837\n","</td>\n","<td><span style=\"display:none;\">Albania</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/20px-Flag_of_Albania.svg.png\" decoding=\"async\" width=\"20\" height=\"14\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/30px-Flag_of_Albania.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/3/36/Flag_of_Albania.svg/40px-Flag_of_Albania.svg.png 2x\" data-file-width=\"700\" data-file-height=\"500\"></span></span> <a href=\"/wiki/Albania\" title=\"Albania\">Albania</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Aysen,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región Aysén del General Carlos Ibáñez del Campo\"><img alt=\"Bandera de la Región Aysén del General Carlos Ibáñez del Campo\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/0/0d/Flag_of_Aysen%2C_Chile.svg/20px-Flag_of_Aysen%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/0/0d/Flag_of_Aysen%2C_Chile.svg/30px-Flag_of_Aysen%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/0/0d/Flag_of_Aysen%2C_Chile.svg/40px-Flag_of_Aysen%2C_Chile.svg.png 2x\" data-file-width=\"600\" data-file-height=\"400\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_Ays%C3%A9n_del_General_Carlos_Ib%C3%A1%C3%B1ez_del_Campo\" class=\"mw-redirect\" title=\"Región Aysén del General Carlos Ibáñez del Campo\">Aisén</a></b>\n","</th>\n","<td style=\"color:#FFFF00;\"><b>0,669</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,717</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,762</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,807</b>\n","</td>\n","<td><b><span style=\"color: #3CB371\">0,811</span></b>\n","</td>\n","<td>103 158\n","</td>\n","<td><span style=\"display:none;\">Serbia</span><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Serbia.svg\" class=\"mw-file-description\" title=\"Bandera de Serbia\"><img alt=\"Bandera de Serbia\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/f/ff/Flag_of_Serbia.svg/20px-Flag_of_Serbia.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/f/ff/Flag_of_Serbia.svg/30px-Flag_of_Serbia.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/f/ff/Flag_of_Serbia.svg/40px-Flag_of_Serbia.svg.png 2x\" data-file-width=\"1350\" data-file-height=\"900\"></a></span>&nbsp;</span><a href=\"/wiki/Serbia\" title=\"Serbia\">Serbia</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_O%27Higgins_Region,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región del Libertador General Bernardo O'Higgins\"><img alt=\"Bandera de la Región del Libertador General Bernardo O'Higgins\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/2/26/Flag_of_O%27Higgins_Region%2C_Chile.svg/20px-Flag_of_O%27Higgins_Region%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/2/26/Flag_of_O%27Higgins_Region%2C_Chile.svg/30px-Flag_of_O%27Higgins_Region%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/2/26/Flag_of_O%27Higgins_Region%2C_Chile.svg/40px-Flag_of_O%27Higgins_Region%2C_Chile.svg.png 2x\" data-file-width=\"600\" data-file-height=\"400\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_del_Libertador_General_Bernardo_O%27Higgins\" title=\"Región del Libertador General Bernardo O'Higgins\">O'Higgins</a></b>\n","</th>\n","<td style=\"color:#FFFF00;\"><b>0,681</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,729</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,774</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,820</b>\n","</td>\n","<td><b><span style=\"color: #3CB371\">0,824</span></b>\n","</td>\n","<td>914 555\n","</td>\n","<td><span style=\"display:none;\">Turquía</span><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Turkey.svg\" class=\"mw-file-description\" title=\"Bandera de Turquía\"><img alt=\"Bandera de Turquía\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/b/b4/Flag_of_Turkey.svg/20px-Flag_of_Turkey.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/b/b4/Flag_of_Turkey.svg/30px-Flag_of_Turkey.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/b/b4/Flag_of_Turkey.svg/40px-Flag_of_Turkey.svg.png 2x\" data-file-width=\"1200\" data-file-height=\"800\"></a></span>&nbsp;</span><a href=\"/wiki/Turqu%C3%ADa\" title=\"Turquía\">Turquía</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_%C3%91uble_Region,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Ñuble\"><img alt=\"Bandera de la Región de Ñuble\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/30/Flag_of_%C3%91uble_Region%2C_Chile.svg/20px-Flag_of_%C3%91uble_Region%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/30/Flag_of_%C3%91uble_Region%2C_Chile.svg/30px-Flag_of_%C3%91uble_Region%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/3/30/Flag_of_%C3%91uble_Region%2C_Chile.svg/40px-Flag_of_%C3%91uble_Region%2C_Chile.svg.png 2x\" data-file-width=\"600\" data-file-height=\"400\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_%C3%91uble\" title=\"Región de Ñuble\">Ñuble</a></b>\n","</th>\n","<td colspan=\"3\"><center><i><small>Perteneciente a Biobío</small></i></center>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,826</b>\n","</td>\n","<td><b><span style=\"color: #3CB371\">0,829</span></b>\n","</td>\n","<td>480 609\n","</td>\n","<td><span style=\"display:none;\">Kazajistán</span><span typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/d/d3/Flag_of_Kazakhstan.svg/20px-Flag_of_Kazakhstan.svg.png\" decoding=\"async\" width=\"20\" height=\"10\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/d/d3/Flag_of_Kazakhstan.svg/30px-Flag_of_Kazakhstan.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/d/d3/Flag_of_Kazakhstan.svg/40px-Flag_of_Kazakhstan.svg.png 2x\" data-file-width=\"1000\" data-file-height=\"500\"></span></span> <a href=\"/wiki/Kazajist%C3%A1n\" title=\"Kazajistán\">Kazajistán</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Biob%C3%ADo_Region,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región del Biobío\"><img alt=\"Bandera de la Región del Biobío\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/c/cd/Flag_of_Biob%C3%ADo_Region%2C_Chile.svg/20px-Flag_of_Biob%C3%ADo_Region%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/c/cd/Flag_of_Biob%C3%ADo_Region%2C_Chile.svg/30px-Flag_of_Biob%C3%ADo_Region%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/c/cd/Flag_of_Biob%C3%ADo_Region%2C_Chile.svg/40px-Flag_of_Biob%C3%ADo_Region%2C_Chile.svg.png 2x\" data-file-width=\"600\" data-file-height=\"400\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_del_Biob%C3%ADo\" title=\"Región del Biobío\">Bío Bío</a></b>\n","</th>\n","<td style=\"color:#FFFF00;\"><b>0,685</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,734</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,779</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,826</b>\n","</td>\n","<td><b><span style=\"color: #3CB371\">0,829</span></b>\n","</td>\n","<td>1 556 805\n","</td>\n","<td><span style=\"display:none;\">Kazajistán</span><span typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/d/d3/Flag_of_Kazakhstan.svg/20px-Flag_of_Kazakhstan.svg.png\" decoding=\"async\" width=\"20\" height=\"10\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/d/d3/Flag_of_Kazakhstan.svg/30px-Flag_of_Kazakhstan.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/d/d3/Flag_of_Kazakhstan.svg/40px-Flag_of_Kazakhstan.svg.png 2x\" data-file-width=\"1000\" data-file-height=\"500\"></span></span> <a href=\"/wiki/Kazajist%C3%A1n\" title=\"Kazajistán\">Kazajistán</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Coquimbo_Region,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Coquimbo\"><img alt=\"Bandera de la Región de Coquimbo\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/d/d7/Flag_of_Coquimbo_Region%2C_Chile.svg/20px-Flag_of_Coquimbo_Region%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/d/d7/Flag_of_Coquimbo_Region%2C_Chile.svg/30px-Flag_of_Coquimbo_Region%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/d/d7/Flag_of_Coquimbo_Region%2C_Chile.svg/40px-Flag_of_Coquimbo_Region%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Coquimbo\" title=\"Región de Coquimbo\">Coquimbo</a></b>\n","</th>\n","<td style=\"color:#FFFF00;\"><b>0,688</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,738</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,783</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,830</b>\n","</td>\n","<td><b><span style=\"color: #3CB371\">0,834</span></b>\n","</td>\n","<td>757 583\n","</td>\n","<td><span style=\"display:none;\">Montenegro</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/6/64/Flag_of_Montenegro.svg/20px-Flag_of_Montenegro.svg.png\" decoding=\"async\" width=\"20\" height=\"10\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/6/64/Flag_of_Montenegro.svg/30px-Flag_of_Montenegro.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/6/64/Flag_of_Montenegro.svg/40px-Flag_of_Montenegro.svg.png 2x\" data-file-width=\"1200\" data-file-height=\"600\"></span></span> <a href=\"/wiki/Montenegro\" title=\"Montenegro\">Montenegro</a>\n","</td></tr><tr bgcolor=\"E6E6FA\">\n","<td><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de Chile\"><img alt=\"Bandera de Chile\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/7/78/Flag_of_Chile.svg/20px-Flag_of_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/7/78/Flag_of_Chile.svg/30px-Flag_of_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/7/78/Flag_of_Chile.svg/40px-Flag_of_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b>Total nacional</b>\n","</td>\n","<td style=\"color:#D3FF00;\"><b>0,707</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,757</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,803</b>\n","</td>\n","<td style=\"color:#007F00;\"><b>0,851</b>\n","</td>\n","<td><b><span style=\"color:green\">0,855</span></b>\n","</td>\n","<td>17 574 003\n","</td>\n","<td><span class=\"flagicon\"><span style=\"display:none;\">Croacia</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/1b/Flag_of_Croatia.svg/20px-Flag_of_Croatia.svg.png\" decoding=\"async\" width=\"20\" height=\"10\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/1b/Flag_of_Croatia.svg/30px-Flag_of_Croatia.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/1/1b/Flag_of_Croatia.svg/40px-Flag_of_Croatia.svg.png 2x\" data-file-width=\"1200\" data-file-height=\"600\"></span></span></span>&nbsp;<a href=\"/wiki/Croacia\" title=\"Croacia\">Croacia</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Atacama,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Atacama\"><img alt=\"Bandera de la Región de Atacama\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/38/Flag_of_Atacama%2C_Chile.svg/20px-Flag_of_Atacama%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/3/38/Flag_of_Atacama%2C_Chile.svg/30px-Flag_of_Atacama%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/3/38/Flag_of_Atacama%2C_Chile.svg/40px-Flag_of_Atacama%2C_Chile.svg.png 2x\" data-file-width=\"744\" data-file-height=\"496\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Atacama\" title=\"Región de Atacama\">Atacama</a></b>\n","</th>\n","<td style=\"color:#D3FF00;\"><b>0,710</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,760</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,807</b>\n","</td>\n","<td style=\"color:#007F00;\"><b>0,855</b>\n","</td>\n","<td><b><span style=\"color:green\">0,859</span></b>\n","</td>\n","<td>286 168\n","</td>\n","<td><span style=\"display:none;\">Hungría</span><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/c/c1/Flag_of_Hungary.svg/20px-Flag_of_Hungary.svg.png\" decoding=\"async\" width=\"20\" height=\"10\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/c/c1/Flag_of_Hungary.svg/30px-Flag_of_Hungary.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/c/c1/Flag_of_Hungary.svg/40px-Flag_of_Hungary.svg.png 2x\" data-file-width=\"1200\" data-file-height=\"600\"></span></span>&nbsp;</span><a href=\"/wiki/Hungr%C3%ADa\" title=\"Hungría\">Hungría</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Magallanes,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Magallanes y de la Antártica Chilena\"><img alt=\"Bandera de la Región de Magallanes y de la Antártica Chilena\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/8/8d/Flag_of_Magallanes%2C_Chile.svg/20px-Flag_of_Magallanes%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/8/8d/Flag_of_Magallanes%2C_Chile.svg/30px-Flag_of_Magallanes%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/8/8d/Flag_of_Magallanes%2C_Chile.svg/40px-Flag_of_Magallanes%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Magallanes_y_de_la_Ant%C3%A1rtica_Chilena\" title=\"Región de Magallanes y de la Antártica Chilena\">Magallanes</a></b>\n","</th>\n","<td style=\"color:#D3FF00;\"><b>0,717</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,768</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,815</b>\n","</td>\n","<td style=\"color:#007F00;\"><b>0,864</b>\n","</td>\n","<td><b><span style=\"color:green\">0,867</span></b>\n","</td>\n","<td>166 533\n","</td>\n","<td><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Portugal.svg\" class=\"mw-file-description\" title=\"Bandera de Portugal\"><img alt=\"Bandera de Portugal\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/5/5c/Flag_of_Portugal.svg/20px-Flag_of_Portugal.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/5/5c/Flag_of_Portugal.svg/30px-Flag_of_Portugal.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/5/5c/Flag_of_Portugal.svg/40px-Flag_of_Portugal.svg.png 2x\" data-file-width=\"600\" data-file-height=\"400\"></a></span>&nbsp;</span><a href=\"/wiki/Portugal\" title=\"Portugal\">Portugal</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Valparaiso_Region,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Valparaíso\"><img alt=\"Bandera de la Región de Valparaíso\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/5/50/Flag_of_Valparaiso_Region%2C_Chile.svg/20px-Flag_of_Valparaiso_Region%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/5/50/Flag_of_Valparaiso_Region%2C_Chile.svg/30px-Flag_of_Valparaiso_Region%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/5/50/Flag_of_Valparaiso_Region%2C_Chile.svg/40px-Flag_of_Valparaiso_Region%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Valpara%C3%ADso\" title=\"Región de Valparaíso\">Valparaíso</a></b>\n","</th>\n","<td style=\"color:#D3FF00;\"><b>0,720</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,771</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,818</b>\n","</td>\n","<td style=\"color:#007F00;\"><b>0,867</b>\n","</td>\n","<td><b><span style=\"color:green\">0,871</span></b>\n","</td>\n","<td>1 815 902\n","</td>\n","<td><span style=\"display:none;\">Letonia</span><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Latvia.svg\" class=\"mw-file-description\" title=\"Bandera de Letonia\"><img alt=\"Bandera de Letonia\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/8/84/Flag_of_Latvia.svg/20px-Flag_of_Latvia.svg.png\" decoding=\"async\" width=\"20\" height=\"10\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/8/84/Flag_of_Latvia.svg/30px-Flag_of_Latvia.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/8/84/Flag_of_Latvia.svg/40px-Flag_of_Latvia.svg.png 2x\" data-file-width=\"1200\" data-file-height=\"600\"></a></span>&nbsp;</span><a href=\"/wiki/Letonia\" title=\"Letonia\">Letonia</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Antofagasta_Region,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Antofagasta\"><img alt=\"Bandera de la Región de Antofagasta\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/c/cc/Flag_of_Antofagasta_Region%2C_Chile.svg/20px-Flag_of_Antofagasta_Region%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/c/cc/Flag_of_Antofagasta_Region%2C_Chile.svg/30px-Flag_of_Antofagasta_Region%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/c/cc/Flag_of_Antofagasta_Region%2C_Chile.svg/40px-Flag_of_Antofagasta_Region%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Antofagasta\" title=\"Región de Antofagasta\">Antofagasta</a></b>\n","</th>\n","<td style=\"color:#D3FF00;\"><b>0,729</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,781</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,829</b>\n","</td>\n","<td style=\"color:#007F00;\"><b>0,875</b>\n","</td>\n","<td><b><span style=\"color:green\">0,876</span></b>\n","</td>\n","<td>607 534\n","</td>\n","<td><span class=\"flagicon\"><span style=\"display:none;\">Polonia</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/12/Flag_of_Poland.svg/20px-Flag_of_Poland.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/12/Flag_of_Poland.svg/30px-Flag_of_Poland.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/1/12/Flag_of_Poland.svg/40px-Flag_of_Poland.svg.png 2x\" data-file-width=\"640\" data-file-height=\"400\"></span></span>&nbsp;</span><a href=\"/wiki/Polonia\" title=\"Polonia\">Polonia</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Arica_y_Parinacota,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Arica y Parinacota\"><img alt=\"Bandera de la Región de Arica y Parinacota\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/f/fa/Flag_of_Arica_y_Parinacota%2C_Chile.svg/20px-Flag_of_Arica_y_Parinacota%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/f/fa/Flag_of_Arica_y_Parinacota%2C_Chile.svg/30px-Flag_of_Arica_y_Parinacota%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/f/fa/Flag_of_Arica_y_Parinacota%2C_Chile.svg/40px-Flag_of_Arica_y_Parinacota%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Arica_y_Parinacota\" title=\"Región de Arica y Parinacota\">Arica y Parinacota</a></b>\n","</th>\n","<td colspan=\"2\"><center><i><small>Perteneciente a Tarapacá</small></i></center>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,832</b>\n","</td>\n","<td style=\"color:#007F00;\"><b>0,882</b>\n","</td>\n","<td><b><span style=\"color:green\">0,882</span></b>\n","</td>\n","<td>226 068\n","</td>\n","<td><span class=\"flagicon\"><span style=\"display:none;\">Lituania</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/20px-Flag_of_Lithuania.svg.png\" decoding=\"async\" width=\"20\" height=\"12\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/30px-Flag_of_Lithuania.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/40px-Flag_of_Lithuania.svg.png 2x\" data-file-width=\"1000\" data-file-height=\"600\"></span></span>&nbsp;</span><a href=\"/wiki/Lituania\" title=\"Lituania\">Lituania</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_Tarapaca,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región de Tarapacá\"><img alt=\"Bandera de la Región de Tarapacá\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/8/87/Flag_of_Tarapaca%2C_Chile.svg/20px-Flag_of_Tarapaca%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/8/87/Flag_of_Tarapaca%2C_Chile.svg/30px-Flag_of_Tarapaca%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/8/87/Flag_of_Tarapaca%2C_Chile.svg/40px-Flag_of_Tarapaca%2C_Chile.svg.png 2x\" data-file-width=\"600\" data-file-height=\"400\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_de_Tarapac%C3%A1\" title=\"Región de Tarapacá\">Tarapacá</a></b>\n","</th>\n","<td style=\"color:#D3FF00;\"><b>0,732</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,784</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,832</b>\n","</td>\n","<td style=\"color:#007F00;\"><b>0,882</b>\n","</td>\n","<td><b><span style=\"color:green\">0,882</span></b>\n","</td>\n","<td>330 558\n","</td>\n","<td><span class=\"flagicon\"><span style=\"display:none;\">Lituania</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/20px-Flag_of_Lithuania.svg.png\" decoding=\"async\" width=\"20\" height=\"12\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/30px-Flag_of_Lithuania.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/40px-Flag_of_Lithuania.svg.png 2x\" data-file-width=\"1000\" data-file-height=\"600\"></span></span>&nbsp;</span><a href=\"/wiki/Lituania\" title=\"Lituania\">Lituania</a>\n","</td></tr><tr>\n","<th><span class=\"flagicon\"><span class=\"mw-image-border\" typeof=\"mw:File\"><a href=\"/wiki/Archivo:Flag_of_the_Metropolitan_Region,_Chile.svg\" class=\"mw-file-description\" title=\"Bandera de la Región Metropolitana de Santiago\"><img alt=\"Bandera de la Región Metropolitana de Santiago\" src=\"//upload.wikimedia.org/wikipedia/commons/thumb/8/8d/Flag_of_the_Metropolitan_Region%2C_Chile.svg/20px-Flag_of_the_Metropolitan_Region%2C_Chile.svg.png\" decoding=\"async\" width=\"20\" height=\"13\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/8/8d/Flag_of_the_Metropolitan_Region%2C_Chile.svg/30px-Flag_of_the_Metropolitan_Region%2C_Chile.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/8/8d/Flag_of_the_Metropolitan_Region%2C_Chile.svg/40px-Flag_of_the_Metropolitan_Region%2C_Chile.svg.png 2x\" data-file-width=\"900\" data-file-height=\"600\"></a></span></span> <b><a href=\"/wiki/Regi%C3%B3n_Metropolitana_de_Santiago\" title=\"Región Metropolitana de Santiago\">Metropolitana</a></b>\n","</th>\n","<td style=\"color:#D3FF00;\"><b>0,733</b>\n","</td>\n","<td style=\"color:#00F900;\"><b>0,785</b>\n","</td>\n","<td style=\"color:#00C400;\"><b>0,833</b>\n","</td>\n","<td style=\"color:#007F00;\"><b>0,883</b>\n","</td>\n","<td><b><span style=\"color:green\">0,886</span></b>\n","</td>\n","<td>7 112 808\n","</td>\n","<td><span class=\"flagicon\"><span style=\"display:none;\">Lituania</span><span class=\"mw-image-border\" typeof=\"mw:File\"><span><img src=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/20px-Flag_of_Lithuania.svg.png\" decoding=\"async\" width=\"20\" height=\"12\" class=\"mw-file-element\" srcset=\"//upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/30px-Flag_of_Lithuania.svg.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/1/11/Flag_of_Lithuania.svg/40px-Flag_of_Lithuania.svg.png 2x\" data-file-width=\"1000\" data-file-height=\"600\"></span></span>&nbsp;</span><a href=\"/wiki/Lituania\" title=\"Lituania\">Lituania</a>\n","</td></tr></tbody><tfoot></tfoot></table>"],"metadata":{"id":"3badQ_inkm0x"}},{"cell_type":"markdown","source":["Es posible observar en las visualizaciones que los proyectos más recientes están concentrados en las regiones de Ñuble y Maule, debido a la mayor concentración de proyectos en fase de ejecución en dichas áreas."],"metadata":{"id":"ISus2W2eks1p"}},{"cell_type":"markdown","source":["###**PARTE 5: Modelo de predicción del cumplimiento del nivel de servicio**"],"metadata":{"id":"MHZ1a9V90heU"}},{"cell_type":"markdown","source":["En esta sección serán evaluados apenas los proyectos que poseen Estado \"Obra Terminada\", el objetivo és evaluar las características que hicieron que un proyecto cumpla el SLA propuesto por el ministério, identificando cuales son los efectos que contribuíran para que ocurrea una falla en el proceso."],"metadata":{"id":"rHvSXrsi0-F3"}},{"cell_type":"code","source":["#selección de los indivíduos de interes:\n","df_model = data.loc[(data['ESTADO PROYECTO']=='OBRA TERMINADA'),:]\n","df_model['Tipo de Expediente'] = df_model.loc[:,'Tipo de Expediente'].str.lower()\n","df_model.sample(5)"],"metadata":{"id":"7yplClI71mMw","outputId":"e79e56e0-00e6-4378-89fb-fe73b43d4c38","colab":{"base_uri":"https://localhost:8080/","height":468}},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["<ipython-input-46-3aa1062fdb60>:3: SettingWithCopyWarning:\n","\n","\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"]},{"output_type":"execute_result","data":{"text/plain":["       ID PHR Postula Con Proyecto Desarrollado  Año Programa  \\\n","19705   LL457                                No          2017   \n","11652   LA525                                No          2016   \n","11320  LA4951                                No          2018   \n","23976  MA1288                                No          2017   \n","42612   ÑU516                                No          2018   \n","\n","      Fecha Publicación DO Región Ejecución   Provincia Tipo de Expediente  \\\n","19705           2017-10-03        Los Lagos  Llanquihue          colectivo   \n","11652           2017-01-14        Araucanía      Cautín          colectivo   \n","11320           2019-02-01        Araucanía     Malleco          colectivo   \n","23976           2017-10-03            Maule      Curicó         individual   \n","42612           2018-11-17            Ñuble     Punilla         individual   \n","\n","      Tipología Madre Tipo de Intervención N° Expediente  ...  \\\n","19705            MAVE         Mejoramiento         12638  ...   \n","11652             CSR       Vivienda Nueva          7689  ...   \n","11320            MAVE         Mejoramiento         18741  ...   \n","23976            MAVE         Mejoramiento         12518  ...   \n","42612             CSR       Vivienda Nueva          6952  ...   \n","\n","                     etapa_5  duracao_5  etapa_6  duracao_6  etapa_7  \\\n","19705                    NaN        NaN      NaN        NaN      NaN   \n","11652                    NaN        NaN      NaN        NaN      NaN   \n","11320                    NaN        NaN      NaN        NaN      NaN   \n","23976                    NaN        NaN      NaN        NaN      NaN   \n","42612  Fecha Término de Obra       66.0      NaN        NaN      NaN   \n","\n","       duracao_7  Fecha_final  Duracion_total target censura  \n","19705        NaN   2021-01-18        3.295890      0       0  \n","11652        NaN   2018-09-03        1.635616      1       0  \n","11320        NaN   2023-04-28        4.238356      0       0  \n","23976        NaN   2019-04-01        1.493151      0       0  \n","42612        NaN   2022-04-22        3.430137      1       0  \n","\n","[5 rows x 60 columns]"],"text/html":["\n","  <div id=\"df-683472f8-e476-4ddf-b689-87028469b1e6\" 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 th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>ID PHR</th>\n","      <th>Postula Con Proyecto Desarrollado</th>\n","      <th>Año Programa</th>\n","      <th>Fecha Publicación DO</th>\n","      <th>Región Ejecución</th>\n","      <th>Provincia</th>\n","      <th>Tipo de Expediente</th>\n","      <th>Tipología Madre</th>\n","      <th>Tipo de Intervención</th>\n","      <th>N° Expediente</th>\n","      <th>...</th>\n","      <th>etapa_5</th>\n","      <th>duracao_5</th>\n","      <th>etapa_6</th>\n","      <th>duracao_6</th>\n","      <th>etapa_7</th>\n","      <th>duracao_7</th>\n","      <th>Fecha_final</th>\n","      <th>Duracion_total</th>\n","      <th>target</th>\n","      <th>censura</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>19705</th>\n","      <td>LL457</td>\n","      <td>No</td>\n","      <td>2017</td>\n","      <td>2017-10-03</td>\n","      <td>Los Lagos</td>\n","      <td>Llanquihue</td>\n","      <td>colectivo</td>\n","      <td>MAVE</td>\n","      <td>Mejoramiento</td>\n","      <td>12638</td>\n","      <td>...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>2021-01-18</td>\n","      <td>3.295890</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>11652</th>\n","      <td>LA525</td>\n","      <td>No</td>\n","      <td>2016</td>\n","      <td>2017-01-14</td>\n","      <td>Araucanía</td>\n","      <td>Cautín</td>\n","      <td>colectivo</td>\n","      <td>CSR</td>\n","      <td>Vivienda Nueva</td>\n","      <td>7689</td>\n","      <td>...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>2018-09-03</td>\n","      <td>1.635616</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>11320</th>\n","      <td>LA4951</td>\n","      <td>No</td>\n","      <td>2018</td>\n","      <td>2019-02-01</td>\n","      <td>Araucanía</td>\n","      <td>Malleco</td>\n","      <td>colectivo</td>\n","      <td>MAVE</td>\n","      <td>Mejoramiento</td>\n","      <td>18741</td>\n","      <td>...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>2023-04-28</td>\n","      <td>4.238356</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>23976</th>\n","      <td>MA1288</td>\n","      <td>No</td>\n","      <td>2017</td>\n","      <td>2017-10-03</td>\n","      <td>Maule</td>\n","      <td>Curicó</td>\n","      <td>individual</td>\n","      <td>MAVE</td>\n","      <td>Mejoramiento</td>\n","      <td>12518</td>\n","      <td>...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>2019-04-01</td>\n","      <td>1.493151</td>\n","      <td>0</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>42612</th>\n","      <td>ÑU516</td>\n","      <td>No</td>\n","      <td>2018</td>\n","      <td>2018-11-17</td>\n","      <td>Ñuble</td>\n","      <td>Punilla</td>\n","      <td>individual</td>\n","      <td>CSR</td>\n","      <td>Vivienda Nueva</td>\n","      <td>6952</td>\n","      <td>...</td>\n","      <td>Fecha Término de Obra</td>\n","      <td>66.0</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>2022-04-22</td>\n","      <td>3.430137</td>\n","      <td>1</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 60 columns</p>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-683472f8-e476-4ddf-b689-87028469b1e6')\"\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 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    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Así, que serán evaludados los cuatro tipos de datos cuanto a las respuestas esperadas."],"metadata":{"id":"GcYu6_8ho1Cn"}},{"cell_type":"code","source":["seg = df_model.groupby(by=['Tipo de Expediente','Tipo de Intervención'])\n","seg['Duracion_total'].describe()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"Ix1LDYoRpmqi","outputId":"b73f0657-e63a-40b7-e684-0cb3cffd4024"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                                          count      mean       std       min  \\\n","Tipo de Expediente Tipo de Intervención                                         \n","colectivo          Mejoramiento          5008.0  2.367642  1.039832  0.539726   \n","                   Vivienda Nueva        3657.0  3.438003  1.100477  1.189041   \n","individual         Mejoramiento          1707.0  2.430362  1.174008  0.624658   \n","                   Vivienda Nueva        1845.0  3.110282  1.092844  0.394521   \n","\n","                                              25%       50%       75%  \\\n","Tipo de Expediente Tipo de Intervención                                 \n","colectivo          Mejoramiento          1.706849  2.161644  2.835616   \n","                   Vivienda Nueva        2.602740  3.452055  4.115068   \n","individual         Mejoramiento          1.567123  2.071233  3.131507   \n","                   Vivienda Nueva        2.263014  3.098630  3.783562   \n","\n","                                              max  \n","Tipo de Expediente Tipo de Intervención            \n","colectivo          Mejoramiento          6.210959  \n","                   Vivienda Nueva        6.375342  \n","individual         Mejoramiento          6.205480  \n","                   Vivienda Nueva        6.558904  "],"text/html":["\n","  <div id=\"df-5570874c-f4bd-47e9-a585-3faba894973c\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr 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<td>5008.0</td>\n","      <td>2.367642</td>\n","      <td>1.039832</td>\n","      <td>0.539726</td>\n","      <td>1.706849</td>\n","      <td>2.161644</td>\n","      <td>2.835616</td>\n","      <td>6.210959</td>\n","    </tr>\n","    <tr>\n","      <th>Vivienda Nueva</th>\n","      <td>3657.0</td>\n","      <td>3.438003</td>\n","      <td>1.100477</td>\n","      <td>1.189041</td>\n","      <td>2.602740</td>\n","      <td>3.452055</td>\n","      <td>4.115068</td>\n","      <td>6.375342</td>\n","    </tr>\n","    <tr>\n","      <th rowspan=\"2\" valign=\"top\">individual</th>\n","      <th>Mejoramiento</th>\n","      <td>1707.0</td>\n","      <td>2.430362</td>\n","      <td>1.174008</td>\n","      <td>0.624658</td>\n","      <td>1.567123</td>\n","      <td>2.071233</td>\n","      <td>3.131507</td>\n","      <td>6.205480</td>\n","    </tr>\n","    <tr>\n","      <th>Vivienda Nueva</th>\n","      <td>1845.0</td>\n","      <td>3.110282</td>\n","      <td>1.092844</td>\n","      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data.columns\n","\n","    #Run WoE and IV on all the independent variables\n","    for ivars in cols[~cols.isin([target])]:\n","        if (data[ivars].dtype.kind in 'bifc') and (len(np.unique(data[ivars]))>10):\n","            binned_x = pd.qcut(data[ivars], bins,  duplicates='drop')\n","            d0 = pd.DataFrame({'x': binned_x, 'y': data[target]})\n","        else:\n","            d0 = pd.DataFrame({'x': data[ivars], 'y': data[target]})\n","        d = d0.groupby(\"x\", as_index=False).agg({\"y\": [\"count\", \"sum\"]})\n","        d.columns = ['Cutoff', 'N', 'Events']\n","        d['% of Events'] = np.maximum(d['Events'], 0.5) / d['Events'].sum()\n","        d['Non-Events'] = d['N'] - d['Events']\n","        d['% of Non-Events'] = np.maximum(d['Non-Events'], 0.5) / d['Non-Events'].sum()\n","        d['WoE'] = np.log(d['% of Events']/d['% of Non-Events'])\n","        d['IV'] = d['WoE'] * (d['% of Events'] - d['% of Non-Events'])\n","        d.insert(loc=0, column='Variable', value=ivars)\n","        print(\"Information value of \" + ivars + \" is \" + str(round(d['IV'].sum(),6)))\n","        temp =pd.DataFrame({\"Variable\" : [ivars], \"IV\" : [d['IV'].sum()]}, columns = [\"Variable\", \"IV\"])\n","        newDF=pd.concat([newDF,temp], axis=0)\n","        woeDF=pd.concat([woeDF,d], axis=0)\n","\n","        if show_woe == True:\n","            print(d)\n","\n","    return newDF, woeDF"],"metadata":{"id":"ZYTSNkUTYt21"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# function to plot WoE\n","# code extracted from https://www.kaggle.com/code/chandrimad31/credit-risk-part-1-binning-woe-iv-pd-model\n","# author: CHANDRIMA D\n","\n","def plot_by_woe(df_WoE, rotation_of_x_axis_labels = 0):\n","    x = np.array(df_WoE.iloc[:, 0].apply(str))\n","    y = df_WoE['WoE']\n","    plt.figure(figsize=(18, 12))\n","    plt.plot(x, y, marker = 'o', color = 'hotpink', linestyle = 'dashed', linewidth = 3, markersize = 18, markeredgecolor = 'cyan', markerfacecolor = 'black')\n","    plt.xlabel(df_WoE.columns[0])\n","    plt.ylabel('Weight of Evidence')\n","    plt.title(str('Weight of Evidence by ' + df_WoE.columns[0]))\n","    plt.xticks(rotation = rotation_of_x_axis_labels)\n","    plt.xticks(fontsize=14)\n","    plt.yticks(fontsize=14)\n","    plt.show()"],"metadata":{"id":"Ct38BaWvY49t"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# function to calculate WoE for continous variables\n","# code extracted from https://www.kaggle.com/code/chandrimad31/credit-risk-part-1-binning-woe-iv-pd-model\n","# author: CHANDRIMA D\n","\n","\n","def woe_continous(df, cat_feature, good_bad_df):\n","    df = pd.concat([df[cat_feature], good_bad_df], axis=1)\n","    df = pd.concat([df.groupby(df.columns.values[0], as_index = False)[df.columns.values[1]].count(),\n","                    df.groupby(df.columns.values[0], as_index = False)[df.columns.values[1]].mean()], axis = 1)\n","    df = df.iloc[:, [0, 1, 3]]\n","    df.columns = [df.columns.values[0], 'n_obs', 'prop_good']\n","    df['prop_n_obs'] = df['n_obs'] / df['n_obs'].sum()\n","    df['n_good'] = df['prop_good'] * df['n_obs']\n","    df['n_bad'] = (1 - df['prop_good']) * df['n_obs']\n","    df['prop_n_good'] = df['n_good'] / df['n_good'].sum()\n","    df['prop_n_bad'] = df['n_bad'] / df['n_bad'].sum()\n","    df['WoE'] = np.log(df['prop_n_good'] / df['prop_n_bad'])\n","    df['diff_prop_good'] = df['prop_good'].diff().abs()\n","    df['diff_WoE'] = df['WoE'].diff().abs()\n","    df['IV'] = (df['prop_n_good'] - df['prop_n_bad']) * df['WoE']\n","    df['IV'] = df['IV'].sum()\n","    return df"],"metadata":{"id":"ZeKH7qdLZCow"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# function to calculate WoE for categorical variables\n","# code extracted from https://www.kaggle.com/code/chandrimad31/credit-risk-part-1-binning-woe-iv-pd-model\n","# author: CHANDRIMA D\n","\n","\n","def woe_categorical(df, cat_feature, good_bad_df):\n","    df = pd.concat([df[cat_feature], good_bad_df], axis=1)\n","    df = pd.concat([df.groupby(df.columns.values[0], as_index = False)[df.columns.values[1]].count(),\n","                    df.groupby(df.columns.values[0], as_index = False)[df.columns.values[1]].mean()], axis = 1)\n","    df = df.iloc[:, [0, 1, 3]]\n","    df.columns = [df.columns.values[0], 'n_obs', 'prop_good']\n","    df['prop_n_obs'] = df['n_obs'] / df['n_obs'].sum()\n","    df['n_good'] = df['prop_good'] * df['n_obs']\n","    df['n_bad'] = (1 - df['prop_good']) * df['n_obs']\n","    df['prop_n_good'] = df['n_good'] / df['n_good'].sum()\n","    df['prop_n_bad'] = df['n_bad'] / df['n_bad'].sum()\n","    df['WoE'] = np.log(df['prop_n_good'] / df['prop_n_bad'])\n","    df = df.sort_values(['WoE'])\n","    df = df.reset_index(drop = True)\n","    df['diff_prop_good'] = df['prop_good'].diff().abs()\n","    df['diff_WoE'] = df['WoE'].diff().abs()\n","    df['IV'] = (df['prop_n_good'] - df['prop_n_bad']) * df['WoE']\n","    df['IV'] = df['IV'].sum()\n","    return df"],"metadata":{"id":"X5iZlPDxaDtY"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["####Modelo 1: Colectivo e Viviendas Nuovas"],"metadata":{"id":"Idhln8Ifxyei"}},{"cell_type":"markdown","source":["#####Paso 1: Selección de indivíduos para estudo con base en la segmentación propuesta"],"metadata":{"id":"xDOZO0UWJhfM"}},{"cell_type":"markdown","source":["Con base en los estudios anteriores será realizado un modelo de regresión logística para los proyectos del Tipo de Expediente Colectivo y Tipo de Intervención Vivienda Nueva."],"metadata":{"id":"tQjjdLZ2I9C4"}},{"cell_type":"code","source":["#selección de registros para la base de modelage:\n","mask = (df_model['Tipo de Expediente']=='colectivo') & (df_model['Tipo de Intervención']=='Vivienda Nueva') & (df_model['censura']==0)\n","mask\n","df_modelo_1 = df_model.loc[mask,:]\n","df_modelo_1.drop(columns=['ID PHR','Año Programa','Fecha Publicación DO','Tipo de Expediente','Tipo de Intervención','N° Expediente'\n","                            ,'Fecha RE Aprobación Proyecto','Fecha Acta Entrega Terreno','Fecha Término de Obra','ESTADO PROYECTO', 'ESTADO PROYECTO DITEC'\n","                            ,'% Corregido','Estado beneficiario DITEC','Fecha RE Renuncia / Eliminación','Observación DPH', 'Observación Región'\n","                            ,'Duracion (años)','Fecha_final','Duracion_total','censura'],inplace=True)"],"metadata":{"id":"DYWXQDyyyD6m"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["La base contiene 3644 registros con 40 variables."],"metadata":{"id":"at78RMi6JMmD"}},{"cell_type":"code","source":["df_modelo_1.shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"f1ko0ncD9c45","outputId":"b3b4739e-5bb8-41a1-b8b8-dc3c2a0ae954"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(3644, 40)"]},"metadata":{},"execution_count":176}]},{"cell_type":"markdown","source":["#####Paso 2: Selección de variables con base en la variable objetivo y poder de predición"],"metadata":{"id":"qMWZKJDhJeXY"}},{"cell_type":"markdown","source":["######**Eliminación de característica con más de 95% de valores nulos**"],"metadata":{"id":"WmPUHIUIJ1B4"}},{"cell_type":"code","source":["nulos = df_modelo_1.isnull().mean()\n","nulos[nulos>0.95].round(4)*100"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9BCjc_Xc1bHb","outputId":"e0dc1eae-58b5-4077-a402-8bee82e8757a"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Proyección Inicio Obra (año/semestre)      100.00\n","Incremento Requerido para Iniciar Obras    100.00\n","etapa_7                                     98.38\n","duracao_7                                   98.38\n","dtype: float64"]},"metadata":{},"execution_count":177}]},{"cell_type":"code","source":["df_modelo_1.drop(columns=['Proyección Inicio Obra (año/semestre)','Incremento Requerido para Iniciar Obras','etapa_7','duracao_7'],inplace=True)"],"metadata":{"id":"3Z2jyxCv2F6f"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["######**Eliminación de característica con base en correlaciones**"],"metadata":{"id":"f2s49Fj4J_OJ"}},{"cell_type":"markdown","source":["Variables independientes con alta correlación no agregan poder de predición al modelo y además pueden crear resultados incorrectos, en esta etapa se utiliza un mapa de calor para evaluar las correlaciones entre las variables y eliminar aquellas qeu tienen mas de 0.7 (en valores absolutos)."],"metadata":{"id":"QAuM9F_CKNRU"}},{"cell_type":"code","source":["mask = np.zeros_like(df_modelo_1.corr().fillna(0), dtype=np.bool)\n","mask[np.triu_indices_from(mask)] = True\n","plt.figure(figsize=(24,24))\n","sns.heatmap(df_modelo_1.corr(), mask=mask, annot=True,  cmap=\"BrBG\", vmin = -1, fmt='.1g', edgecolor='w', linewidth=0.6)\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"HvExXkfD4odt","outputId":"ec3ef298-7e81-4da4-e8df-17f0b74e4776"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<Axes: >"]},"metadata":{},"execution_count":179},{"output_type":"display_data","data":{"text/plain":["<Figure size 2400x2400 with 2 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5OXuX7O/Y5Uvm35PLl+JU0iXvESAcPSqo3P3P6p9dq3Xyx6VyK1ddAY8MVFZWhs7/9km+xpzf0pOSZczKkmOpUmbrHd3dlJRHn4k98oeO7/hBD08YXhAhWs3FhARlZWbK87pjrYenl/45XjSeMM4v/7aNB21zA3cHR9nZ2io+NcVsfXxqqvw9cj//lnMrpfvKuWn7n79ryNZPVKGUu/rVb6IStrZavm9PQYRtcYl5fH88vTx18sTxXOvEGww3ft+8PBV3zYgQvQYO0PRJb6ndk61VokQJ2draqt/wYYq4/z6L70NBM8RlP4Xu5Wl+PPb2dFNs3O09oZ6VlaWpszeoVligqlapYPEYLS0hPj7n3uD6a33vPEdxi42Nlfd15b29vU3XwIbY2Oxt5FImNqfMqX+yk4Tmz5unAQMGqFz58lq1cqW6de2qjZs2yd3d/a73raDYO2cfV66kmk+FcyU1wfRebi6dP6K/vp6mtIR/ZO/spQoPdFBI6yk6sOF1ZWWk5mvM+S0tKUnGrCw5eZj/Pzq7l1LCqdO51jkTc0SHv9ih/0VOzPX9oizWkD29gJe3eX/w9vaUwZD71APxCYnKzMySl9d1dbw8dTyP8/ymDz9VlSqVVKtmmAWizl9X779v/J3hbu6/Vy5brhIlSui59u0sHjMAAMhmzLpi7RBQDDASAoA8HTt2TJcvXzZ7+sXLy0vVqt35vI61a9c2e52Zmanx48crPDxcXl5ecnV11ZYtW/T339k34jExMUpPTzclP+Rm3bp1atiwocqWLStXV1eNHDnSVP/fbTRsaP5kacOGDRUTE3PbcXfs2FG//PKLduzYoeDgYD333HNKS0vLs/zkyZPl7u5utkyePPm2P6+wuJKRoeFDhsooo4YMG2btcAqFB+rU0co1a7Rw6VI92KCBhg8dmuc8l/eqK6lp+mXRSkW81F4ObkUjMaWg3Ott41vjUTUY8I1psbX9j3msNrZKPntYJ3bM1aVzR3R230ad/XWTyt33rGUDLgIyUtO0e/5y3f9Kx3uyzwDWYGtjo4S0VE39/msdNVzQV3/9oVW/7lWbkBq3rlzMbFq/QTEHDmh85BRFrVim7n16a9aUqdp7zahkRcWn23aq4WN9TMuVK5l3vc23Zq7Vsb9OafLoVy0Q4b0ry2iUJHV59VU93KKFqlevrrHjxkmStm3bZs3QbsmrajPd/8r7psXGtsR/2k7iyT2K//M7pcYd18V/ftbRz8aoREkXeQU0tnDEhd/l1FR98e48NX29i5xKFY2R9G7m08+2q0GTx02LJY4tt5KWlq7PtnxRJEZByC+HY2K0fu1ajRw3VjZFeCQjAAAAMBICgLtkY2MjY86PT//KyMi4oZyLi4vZ6ylTpmjmzJmaMWOGwsPD5eLior59++ry5cuSJCenm899+OOPP6pjx44aN26cWrVqJXd3d61du1aRkZF3uUfm/k0kCAoK0oMPPihPT09t3LhR7du3z7X8sGHD1L9/f7N1Dg4OSrtyY5vcDQ8PD5UoUcLsiTZJioszyNs79znFvX28FXfdExpxhrgbRg24kpGhYUOH6syZM5o7f16RGQVBuqZdrhvFIM5gkJdPHu3i7X1DMkFcXJy8r2sXJycn+fn5yc/PT+Hh4Xq2bVt9tGmTOr/yimV3ogCVdHORja2t0i8mma1Pv5gkB/cbfzi8dCFWqbFx2v3uAtO6f7//H3ftq+YTR8il9L0x/CxtYy7u92/08+mrQ8PblsgeEaaki7cyrhkNoaSLl5LPHc1zO5eTY5USaz41QWrsX/Kp9pCFIy54Dm6usrG1VdpF86ds0xKT5Ohe6obyl85fUEqsQT9MjzKt+7fPfNC5l1q+PUau98g8yqU8PGRbooTirzvWJsTHyfO6J+eKm3/bJoG2uUFiepquZGXJ08l8KHxPJyfFpaTkWseQcklXjFmmP4xK0onEeHk7u8jO1lZXsrLyNeb84J7H9yc+Ll6e3rmPPOPp7X3j9y0u3jSCVnpampbMjdLYd97Wg42yE3YDgoJ07OhRbVgVrQfq1r1hm4VZ04Y1FVa9iul1xuXsJ3ri4i/K1/vqE9yG+CRVq3rrEd3emrlG3/74mxbNHKAyvkVj1CsPT8+ce4Prr/UNN1zT/svHx0eG68obrinvnXPtHBcXJ19fX7My/yal++SUCQgIML1fsmRJVaxYUWfPnr3LvcpfCSd26uB7R0yvbUrYS5LsnDyVkXJ1NAQ7Jw+lGm5/Go/My5eUnnhKju7lLReslTi6ucnG1lapCYlm61MSL8rZw+OG8hfPnlfS+Vh9Nnmaad2/1zbz/veS2s96R+5ly9xQr7Bq2qSBwsKuTsWRkfNbRZwhXr4+V79XBkO8qgVXzXUbnh7uKlHCVnFx5iNsGOLi5Z3LeX77lzuUlpauJ59oaYldyHdX779v/J3B2yf3Y8+t7r/3/fKL4uPi9PQTT5rez8zM1KzpM7Queo02frzZwnsBAACA/MJICADyFBgYKHt7e+3cudO0Lj4+XkePXv0Dk6+vr86cOWN6/fvvvysljx+Gr/X999+rTZs26tSpk2rWrKmAgACz7QYFBcnJyUlffPFFrvV/+OEHVapUSSNGjFDt2rUVFBSkEydOmJUJDQ3V999/f8PnVq9e/Zbx5cZoNMpoNN4w3cK1HBwcVKpUKbMlP6ZjsLe3V0hoiHbv2m1al5WVpT27dis8Ivf52MPDI7T7uqfbdu7cqfCICNPrfxMQTv59UnPmRckjlx+XCjN7e3uFhIRo927zdtm9e7fCw/Nol4gI7bmuXXZd1y65MWZl5ZpwU5TY2tnJvZKfYmOufveMWVmKjTkiz8AqN5R3LVdGTccNVZMxg01LmZph8qkWpCZjBsvJq2j8UH87aBtzmZdTlBb/j2lJif1Tl5Nj5VH56pzjJUq6yK18mJJO5T5HuSRd/OdXOXlXMlvn5FVJ6Yln8qhRdNja2cmjsr8uHLz6Bw1jVpYuHDoi76o39hm3cmXVYtJIPTxhuGkpd1+4fEOD9fCE4XL2Ltp95lr29vaqWq2a9u++Ohx+VlaWft29V9XCC/9Qw/nJ3t5egbm0zX7aRleysnTUcEEPlL86FL6NpPvLV9TBC7n/cfPA+bOq4Oaua5+brFjKQ7Epl4pkAoKU3UeCQ6rp5+uubX7Zs1vV87i2qR4epl+uKS9Je3fuMpW/ciVTV65cka2t+ROmtiVKyGgseu3k4uwo/wqlTUtA5XLy8SqlXT8fNpVJvpSqAzF/KaJGQJ7bMRqNemvmGn313T7Nn9ZXFcrlnsBaGNnb2ys0NFS7rrlvy8rK0q5duxSRxzVteESEdl1/b/DTT6byFSpUkI+Pj9k2k5OTdeDAAVOZ0NBQlSxZ0mzY9YyMDJ0+fVrlypWz1O7li6yMVKVfPGNa0uL/1uVLcSpVoaapjK29k1xLV1PyudsfSc/WzlEOpcrpckrRHzGthL2dfAMr65/fDpnWGbOydGr/QZXJ5Y/uHhXK6bnpk/S/yAmmpXLt+1QhLFT/i5wg1zwSYgorFxdn+ftVMC0BAZXl4+2lnbt/NpVJTr6kAwdjFBGR+28M9vb2Cg0JNquTlZWlXbt/VkT4jXU2ffiZmjZpIC9PD4vvT36wt7dXtZAQ7dl99ViSlZWlPbt3Kyw892NPWESE9uwyP0ft2rlTYTm/Yzz2+ONauXaNlkevNi0+vr7q+MILmjF7Vv7tDAAAACyOkRAA5MnV1VVdunTRoEGD5O3trdKlS2vEiBGytb2av/TQQw9p9uzZql+/vjIzMzVkyBDZ29vfcttBQUF677339MMPP8jT01PTpk3TuXPnTAkCjo6OGjJkiAYPHqySJUuqYcOGunDhgg4ePKguXbooKChIf//9t9auXas6derok08+0caNG80+Y9CgQXruued03333qUWLFtq8ebM++OADbd++/Zbx/fnnn1q3bp1atmwpX19f/fPPP3rrrbfk5OSkxx9//A5bMn906NhJ48aMUWj1UNWoEaa10dFKTU3Vk61bS5LGjBqt0qV91fONNyRJ7Tq0V/euXbV65Uo1bNRIW7dsVcyhQxo+coSk7ASEoYOH6PDhw5o2c4YyMzMVmzMXrLu7+239vxYG7Tt10ptjxig0NFTVw7LbJe2adhk7erR8fa+2y/Pt2+u1a9pl29bsdhk2IrtdUlNTtXTxYjVu2lQ+Pj5KSEjQe+vX68KFC3q4RQur7aelBLRsrn2LV8mjsp88qlTSn9u/Vmb6Zfk3zJ6G5ZdFK+Xo6a7QZ1urhL29SlU0f6rL3jl71JLr198LaJubO7V7jfwadFFq3EmlJZ5SpSavKz3pgmKPfm0qE95+rmKPfq0ze9fn1IlWzReWyK/+y7pweJvcytVQ2VpP6/fP7415g4MefUh7Fq6QZ5VK8gyopD+2fqUr6emq1KS+JGn3/GVy8vRQ2HNtVaKkvdyv6xslnbOf+L5+/b2gbfvnNX38RFUNDVFw9er6cN16paWlqcUTT0iSpo0bL29fH73U43VJ2X/EOvlX9qgZV65kyHDhgv48elSOTs4q73frJ5mLkjbtn9fMnLYJql5dm69rm+k5bfNiLm2TcU3bODk5q9w91jbrD/yqYY0f0uHYCzp84bz+r0aEnOzs9NnR7D8uD2/ysC5cuqSFe3+SJG06fFBPh4ar94ON9P6h31SxlIc61bxf7x/KOzmqKHi2Q3u9M268qoWGqlqN6vpg7Tqlpabp0Sez+8hbY8bJp7SvXu3ZQ5L0TLvn1b/769qwerXqNWyor7Zu09GYGPUbPlSS5OLqooj779OCd2erpIODypQtp/2//Kxtn36m1/r0ttp+WoqNjY06/N/DWrTyM/lXKK3y5XwUteQj+fp4qFmjWqZy3ftPV/PGtdTu6eaSpLdmrNFnX+zW9Amvy9nZUbFx2U9/u7o4ydGhpDV25Y507NRJY0aPVvXq1VUjLEzROfcGrdu0kSSNGjlSpUQ3UTsAAQAASURBVEuX1hu9s/+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3N/z2229YsmQJjI2NATRs39bY0MI3PXv2BAAMGjRI6nFNTc13jpZvyfT09JCdnQ1DQ0PxmpqamvizMZ/fhzt27IiioiLo6ekBANatWyfx5P/Tp095+5nY19cXQ4YMgZubG44dO4ZNmzaxjsQZy5Ytg4qKCoRCIR49egRLS0vxsefPn6N169YM07GzatUqjB49GpWVlZg8eTL8/f1x7949mJub4+7du9iyZQu+/fZb1jGZioqKAgDk5uYiLy8PAwcOhLKyMq+n9RBC/n0CEV8/BRNCSAsVExMjdb2srAzXr1/HgQMHcPjwYTg4ODRzMsJlNjY2Uv/oKC8vx8OHD2Fqaoq4uDh88sknDNJxR1VVFX755RfcuXMHQMOT3W5ublBWVmacjB0TExOMHDkSQUFBvH36TRZra2vMnDkTc+fOhZqaGjIyMmBoaIiZM2eiQ4cOCAkJYR2RGSsrK6xduxZjxozBzZs38emnn8LPzw+JiYkwMzMTXyDho/T0dIwZMwZVVVWorKxEmzZt8OzZM6ioqEBHRwf5+fmsI3JGYWEhrl+/DmNj4yZPgvER/Y56N7rgKl1VVRXy8vIAAF26dJHYJ5jvrl+/jqKiIowYMQKqqqoAgOPHj0NTUxN2dnaM03HPmzdvICcnx8tpPTt37sTr169lNgo+fvwY4eHhCA4ObuZk7Pn4+KC4uBiHDh1qcuzVq1cYMWIErl69ysvG5VmzZqF3796YPn261OOhoaG4cOECjh8/3szJuOP169fw9fVFQkIC8vPzkZmZyevtGAYPHizx2cXNzU3i52fVqlWIj4/HuXPnGKRj79KlS/Dz88Ply5cl1jt27IjAwEDMnz+fUTJuKC0txYQJE5CYmAiBQIB79+7ByMgIXl5e0NLSwoYNG1hHJIS0QNSEQAghPLNx40YcPnwYKSkprKMQDlm+fLnUC/Hq6uowNTUV78vIZ+fPn0e/fv0gLy85SKq2thYpKSkYOHAgo2RsqaurIz09nVej8z9U69atcevWLRgYGKBt27Y4d+4crKyskJ2djaFDh6K4uJh1RGZUVVWRlZUFAwMDLF++HFlZWTh8+DDS0tIwZswYlJSUsI7IzODBg9G1a1eEh4dDQ0MDGRkZUFBQwJQpUzB//nw4OzuzjshETU0NRo0ahfDwcJiYmLCOwzn0O0q258+fY+LEiXTBlRBCGHjx4kWTp7Xf9urVK6SlpcmcIsFnBQUFUFJSktiiga+OHj2KxMREfPvttxLTIoik/Px8KCoqonPnzqyjMPX06VPk5+ejvr4eHTp0gIGBAetInODu7o4nT55g165dMDc3R0ZGBoyMjHD69Gn4+fnh1q1brCMSQlog2o6BEEJ45vPPP8eqVatYx2h2PXv2xNmzZ6GlpSXzqf9GaWlpzZiMG5YtW8b7JoP3GTJkCIqLi5tc9CgvL8eQIUN4+fQO0DDm+ty5c9SEIIWWlpZ465dOnTohKysLVlZWKCsrQ1VVFeN0bCkqKoprEB8fD3d3dwBAmzZt8PLlS5bRmLtx4wZ+/PFHCIVCyMnJ4a+//oKRkRHWrVsHDw8P3jYhKCgoIDMzk3UMzqLfUbL5+vpCQUEBRUVFMDc3F69PmjQJfn5+vGpCcHZ2RnR0NNTV1d/7XhIbG9tMqbjr4cOHOHr0qNStcfi8BUxdXR02bdqEgwcPSq1NaWkpo2QfDysrK5w4cQK6urqso/zrtLS03rmlgJqamkQDAp9q8z5vb2EB8Ls2jo6OcHR0lHqMz3X5OyMjI4nv+VobbW1taGtrv/McPtYmLi4Op0+fbtKkYmJigsLCQkapCCEtHTUhEEIIz/z1119QVFRkHaPZjRs3Dq1atQIAODk5sQ3DQZ07d4aHhwe8vb3pCVMZZI1t5vO+iwCwbds2TJgwARcuXICVlVWTEbx83r9+4MCBOHPmDKysrDBhwgTMnz8fCQkJOHPmDIYNG8Y6HlP9+/eHn58f7OzscOXKFRw4cAAAkJOTw/sndxQUFCAUCgEAOjo64hunGhoaePDgAeN0bE2ZMgURERG0X70U9DtKNrrg+h8aGhrinxMNDQ3Gabjt7NmzcHR0hJGREe7cuYNu3brh/v37EIlE6NmzJ+t4TIWEhGDXrl3w9/fH0qVLsWTJEty/fx+//fYbgoKCWMf7KNy/fx81NTWsY3AS1UY2qo10VBfZqDay8bE2lZWVUrfdKi0tFV8vJYSQ/zVqQiCEEJ6JiIhAjx49WMdodm/vv8nHvTjfZ86cOYiJicH333+Pfv36wdvbGxMnTqR9gQHxk4ICgQDTpk2T+OOsrq4OmZmZ6NevH6t4zO3btw9xcXFQUlLCuXPnJG6CCQQCXjchbNu2DW/evAEALFmyBAoKCkhJScH48eOxdOlSxunY2rZtG+bMmYPDhw9jx44d6NSpEwDg5MmTGDVqFON0bNnY2ODq1aswMTHBoEGDEBQUhGfPnmHPnj3o1q0b63hM1dbWIjIyEvHx8ejVq1eTm+t8fDKZfke9H11w/Y+oqCgADU0rISEh0NbWhrKyMuNU3PTtt98iICAAISEhUFNTw6+//godHR24ubnx/vfUL7/8gp07d2Ls2LFYvnw5Jk+ejC5dusDa2hqpqam8/uxHCCGEcNWAAQOwe/durFy5EkDD3w/19fVYt24dhgwZwjgdIaSloiYEQghpYfz8/KSul5eXIy0tDTk5OTh//nwzpyJct2zZMixbtgznzp1DVFQUvv76a8yfPx8TJ07E9OnT0bdvX9YRmWl8UlAkEkFNTU3iYr2ioiI+++wzzJgxg1U85pYsWYKQkBAsWrRI/PQ2adCmTRvx10KhEIsWLWKYhlv09PTwxx9/NFnftGkTgzTcsmbNGvE2HqtXr4a7uztmz54NExMTREZGMk7HVlZWlvgJ5JycHIlj79pmqSWj31HvRxdcmxKJRDA2NsatW7doApYM2dnZ2LdvHwBAXl4er1+/hqqqKlasWIFx48Zh9uzZjBOyU1JSAisrKwCAqqoqysvLATRs+7ds2TKW0QghhBAiw7p16zBs2DBcu3YN1dXV+Oabb3Dr1i2UlpYiOTmZdTxCSAtFTQiEENLCpKenS11XV1fHiBEjEBsb22RvQT7Q0tL64BsUfN7HdPDgwRg8eDC2b9+O/fv3Izo6Gra2tjA3N4e3t7fMJpeWrPGpQQMDAwQGBtJ0iL+prq7GpEmTqAFBhvr6euTm5uLJkyeor6+XODZw4EBGqbihrq4Ov/32G7KzswEAlpaWcHR0hJycHONkbPXu3Vv8tY6ODk6dOsUwDbckJiayjsA5b/+OCggI4P3WC9LQBdemhEIhTExM8Pz5c2pCkKF169aorq4GAHTo0AF5eXmwtLQEADx79oxlNOY6d+6M4uJi6OnpoUuXLoiLi0PPnj1x9epV3k0XIYQQQj4W3bp1Q05ODrZt2wY1NTVUVFTA2dkZc+fORYcOHVjHI4S0UAKRSCRiHYIQQgj5t8XExHzwuR4eHv9iko/P8ePH4e7ujrKyMtTV1bGOw0xBQQFqa2ubXKy/d+8eFBQUYGBgwCYYY76+vtDW1sbixYtZR+Gc1NRUuLq6orCwEH//yC0QCHj9esrNzcWYMWPw559/wtTUFABw9+5d6Orq4vjx4+jSpQvjhITrHjx4AADQ1dVlnIR8DMrLy7Ft2zZkZGSgoqICPXv25P0F12PHjmHdunXYsWMH77d6kcbJyQljx47FjBkzEBAQgN9//x3Tpk1DbGwstLS0EB8fzzoiM4sWLYK6ujoWL16MAwcOYMqUKTAwMEBRURF8fX0RGhrKOiLnqampISMjA0ZGRqyjcA7VRjaqjXRUF9moNrJRbQghpHnQJARCCGlhvvzyS0yfPh329va8HU0sDTUW/DNVVVU4ePAgoqKicPHiRXTp0gWBgYGsYzE1bdo0eHl5NWlCuHz5Mnbt2oVz586xCcZYXV0d1q1bh9OnT8Pa2hoKCgoSx/m4R3ujWbNmoXfv3jh+/Dg6dOhA78lv8fHxQZcuXZCamiretuL58+eYMmUKfHx8cPz4ccYJm1fPnj1x9uxZaGlpwcbG5p0/K2lpac2YjFtqa2sREhKCLVu2oKKiAkDDKPB58+YhODi4yfsPnzx+/BgBAQE4e/Ysnjx50qTxic9NT0DDthVLlixhHYNT3N3dUVVVhe7du0NRUVFiKw+A35PBgIbPL43vMyEhIaioqMCBAwdgYmLC6882ACSaDCZNmgQ9PT1cunQJJiYmcHBwYJiMEEIIIbJkZmZKXRcIBFBSUoKenh5NNCKE/M9REwIhhLQwL168wNixY9GxY0d4enpi2rRp1NkL4OXLl1BXVxd//S6N5/FRSkoKIiMjcejQIdTW1uLLL7/EypUreT82HmjY6sTOzq7J+meffYavv/6aQSJuuHnzJmxsbAA07Nf+Nr7fdL937x4OHz4MY2Nj1lE4JykpSaIBAQDatm2L0NBQqa+zlm7cuHHiCz5OTk5sw3DYvHnzEBsbi3Xr1sHW1hYAcOnSJSxfvhzPnz/Hjh07GCdkZ9q0aSgqKsKyZcuo6QmyL7JKY21t/S8m4a6wsDDWETjt7b+fWrdujfDwcIZpuM3W1lb8nkw+zI8//oj27duzjsFJVBvZqDbSUV1ko9rIxsfa9OjRQ/w3QmPD8tt/MygoKGDSpEn48ccfoaSkxCQjIaTloe0YCCGkBSosLERUVBR2796NwsJCDBo0CNOnT8f48eN529UqJyeH4uJi6OjoQCgUSr04LxKJeDsifd26dYiKikJOTg569+4Nb29vTJ48GWpqaqyjcYaGhgbOnTsnvuHe6Pr16xg8eDBevXrFKBnhqqFDh+Kbb77BqFGjWEfhnDZt2uCPP/5Av379JNaTk5Ph4ODA+ydwiXQaGhrYv38/Ro8eLbF+4sQJTJ48GeXl5YySsaempoYLFy6gR48erKNwQuNnvfdd7uDr5z7y4a5du4bs7GwAgIWFBXr16sU4ETfcu3cPiYmJePLkCerr6yWOBQUFMUrFDUlJSVi/fr3Ez01gYCAGDBjAOBl7VBvZqDbSUV1ko9rIRrWR7vfff8fChQsRGBiIPn36AACuXLmCDRs2IDg4GLW1tVi0aBEmTZqE9evXM05LCGkpqAmBEEJauISEBERGRuLIkSNo1aoVJk+eDC8vL95dQEtKSoKdnR3k5eWRlJT0znMHDRrUTKm4Q1tbG1OmTIG3tzftCyyDg4MDlJWVsW/fPsjJyQFoGG89adIkVFZW4uTJk4wTspWbm4u8vDwMHDgQysrK4qYePjty5AiWLl2KwMBAWFlZNRkVz9enb4GGMeBpaWmIiIgQXwC5fPkyZsyYgV69eiE6OpptQMJJOjo6SEpKgrm5ucR6dnY2Bg4ciKdPnzJKxp6FhQV++eWXJo1yfFVYWPjB5+rr6/+LSbitrq4Ov/32m/givaWlJRwdHcWfc/js4cOHmDx5MpKTk6GpqQkAKCsrQ79+/bB//3507tyZbUCGdu7cidmzZ6Ndu3b45JNPJD7vCQQCXm8b9PPPP8PT0xPOzs7iyU7Jyck4cuQIoqOj4erqyjghO1Qb2ag20lFdZKPayEa1ka1Pnz5YuXIl7O3tJdZPnz6NZcuW4cqVK/jtt9/g7++PvLw8RikJIS0NNSEQQghPvHr1Cnv37sXixYtRXl6O2tpa1pEIh9TU1PB6L+0Pcfv2bQwcOBCampriDvoLFy7g5cuXSEhI4G3zxvPnzzFx4kQkJiZCIBDg3r17MDIygpeXF7S0tLBhwwbWEZkRCoVN1hqfzOX707dlZWXw8PDAsWPHxO89tbW1cHR0RFRUlPiGD19oaWl9cNMOn6dErFixAnfu3EFUVJR4stNff/0Fb29vmJiYIDg4mHFCduLi4rBhwwb8+OOPMDAwYB2HfARyc3MxZswY/PnnnzA1NQUA3L17F7q6ujh+/Di6dOnCOCFbo0aNQllZGWJiYiTq4+npCXV1dZw6dYpxQnb09fUxZ84cLFy4kHUUzjE3N8dXX30FX19fifWNGzdi586d4oYfPqLayEa1kY7qIhvVRjaqjWzKyspIT0+HmZmZxPqdO3dgY2OD169f4/79+7CwsEBVVRWjlISQloaaEAghhAcKCgoQHR2N6Oho/Pnnnxg+fDivL5wBwJs3b5CZmSl1hKijoyOjVOzs3r37g85zd3f/l5Nw26NHj7Bt2zZkZGRAWVkZ1tbW+PrrryX2tecbd3d3PHnyBLt27YK5uTkyMjJgZGSE06dPw8/PD7du3WIdkZn3PYnL56dvG+Xm5oovBJmbm8PY2JhxIjZiYmI++FwPD49/MQn3ODs7S3wfHx+PVq1aoXv37gCAjIwMVFdXY9iwYYiNjWURkRO0tLRQVVWF2tpaqKioNGks5HPzSqPbt2+jqKgI1dXVEut8/NwHAGPGjIFIJMIvv/wi/hzz/PlzTJkyBUKhEMePH2eckC1lZWWkpKRI3YZrwIABvL44r66ujhs3bsDIyIh1FM5p1aoVbt261eTzTG5uLrp164Y3b94wSsYe1UY2qo10VBfZqDayUW1ks7GxQffu3fHTTz9BUVERQMMDSTNmzEBGRgbS09ORnJyMKVOmoKCggHFaQkhLIc86ACGEkH/HmzdvcPjwYURGRuL8+fPQ1dWFt7c3PD09oauryzoeU6dOnYK7uzuePXvW5Bhfn06eP3++zGMCgQCVlZWora3lfRNCx44dsWbNGtYxOCUuLg6nT59uMpbYxMTkH43DbomoyUC2FStWICAgAMbGxhIXiF6/fo3vv/+ed/tJ862x4J/Q0NCQ+H78+PES3/P9M02jsLAw1hE4Kz8/H1988QVu3rwpnkYDQDx9hI+f+4CGrcpSU1MlGinbtm2L0NBQ8fhiPtPV1UVNTU2T9bq6OnTs2JFBIu6YMGEC4uLiMGvWLNZROEdXVxdnz55tcvMrPj6e97+vqDayUW2ko7rIRrWRjWoj2/bt2+Ho6IjOnTuLt4a8efMm6urq8McffwBo+Nw8Z84cljEJIS0MNSEQQkgLc+XKFURGRuLAgQN48+YNvvjiC5w6dQrDhg3j/f7sjebNm4cJEyYgKCgI7du3Zx2HE168eCF1vbi4GCEhIYiMjMSIESOaORX3XLhwAT/++CPy8/Nx6NAhdOrUCXv27IGhoSH69+/POh4TlZWVUFFRabJeWloqHpfOJ0ePHsXo0aOhoKCAo0ePvvNcvj59CwAhISGYNWtWk5+dqqoqhISE8K4J4eXLl1BXVxd//S6N5/FFVFQU6wgfBWpkkW3+/PkwNDTE2bNnYWhoiCtXruD58+fw9/fH+vXrWcdjplWrVnj16lWT9YqKCvHTcXz2/fffY968edi+fTt69+4NALh27Rrmz5/Py5+bLVu2iL82NjbGsmXLkJqaCisrqyaTV3x8fJo7Hmf4+/vDx8cHN27cQL9+/QA07EUeHR2NzZs3M07HFtVGNqqNdFQX2ag2slFtZOvXrx8KCgrwyy+/ICcnB0BDY6GrqyvU1NQAAFOnTmUZkRDSAtF2DIQQ0sIIhUJ0794d3t7ecHNzg5aWFutInKOuro709HTe73X7Lq9evcLatWuxefNmWFpa4rvvvsOQIUNYx2Lq119/xdSpU+Hm5oY9e/bg9u3bMDIywrZt23DixAmcOHGCdUQmxowZg169emHlypVQU1NDZmYm9PX14eLigvr6ehw+fJh1xGYlFApRUlICHR0dCIVCmefxdepKI6FQiMePH0NbW1tiPSEhAZMmTcLTp08ZJWNDTk4OxcXF4p8baU2DIpGI9z83AJCZmSm+aGZqagorKyvGibgjLy8PUVFRyMvLw+bNm6Gjo4OTJ09CT08PlpaWrOMx065dOyQkJMDa2hoaGhq4cuUKTE1NkZCQAH9/f6Snp7OOyIS7uzvS0tIQERGBPn36AAAuX76MGTNmoFevXoiOjmYbkLG3tziRl294fqfx69atW0ucy4ftTgwNDT/oPIFAgPz8/H85DbcdOXIEGzZskNhuKjAwEOPGjWOcjD2qjWxUG+moLrJRbWSj2jRVU1MDMzMz/PHHHzA3N2cdhxDCI9SEQAghLUxaWhp69uzJOganeXl5wc7ODt7e3qyjcE5NTQ22bt2KNWvWoG3btli9ejW+/PJL1rE4wcbGBr6+vnB3d4eamhoyMjJgZGSE9PR0jB49GiUlJawjMpGVlYVhw4ahZ8+eSEhIgKOjI27duoXS0lIkJydTsw+RoKWlBYFAgPLycqirq0vcbK+rq0NFRQVmzZqF7du3M0zZ/JKSkmBnZwd5eXkkJSW989xBgwY1UypuuXLlCry9vXH79m2JcfqWlpaIiIjAp59+yjghW0lJSRg9ejTs7Oxw/vx5ZGdnw8jICKGhobh27RrvGsLepqWlhbS0NBgaGqJLly7YtWsXhgwZgry8PFhZWaGqqop1RCbKysrg4eGBY8eOiZ9kr62thaOjI6KioqCpqck2IGMxMTEffC5NIiGEEEII13Xq1Anx8fHUhEAIaVbUhEAIIS1MUVHRB52np6f3LyfhrqqqKkyYMAHa2to0QvT/iEQi7N69G0FBQaitrUVwcDC8vb0hJyfHOhpnqKio4Pbt2zAwMJBoQsjPz4eFhQXevHnDOiIz5eXl2LZtGzIyMlBRUYGePXti7ty56NChA+tohGNiYmIgEong5eWFsLAwaGhoiI8pKirCwMAAtra2DBMSLrp9+zb69u0Lc3Nz+Pr6ii+c3b59G5s2bcLdu3eRmpoKCwsLxknZsbW1xYQJE+Dn5yfxO+rKlStwdnbGw4cPWUdkZsCAAfD394eTkxNcXV3x4sULLF26FD/99BOuX7+OrKws1hGZys3NlXhS8O97KBNCCCGEkI/fmjVrkJOTg127domnPBFCyL+NmhAIIaSFed8YZ6DhycHa2trmjsYZERERmDVrFpSUlNC2bVuJevF1hKiVlRXy8/Mxb948LFiwoMk+7Y34thf524yMjPDTTz9h+PDhEjd4du/ejdDQUNy+fZt1RMIxb++f/DaBQAAlJSUYGxtj4MCBvGz2SUpKQr9+/Zo0gZEGb968QWZmJp48eYL6+nqJY46OjoxSsTNx4kTU1tbi119/bfIZRyQSwdnZGQoKCjh48CCjhOypqqri5s2bMDQ0lPgddf/+fZiZmfG6Ue706dOorKyEs7MzcnNz8fnnnyMnJwdt27bFgQMHMHToUNYRmVixYgUCAgKafOZ7/fo1vv/+ewQFBTFKxj1v3rxBdXW1xBqfPxOPHz8effr0wcKFCyXW161bh6tXr+LQoUOMkrFXV1eHTZs24eDBgygqKmryc8OHrTtkodrIRrWRjuoiG9VGNqqNbF988QXOnj0LVVVVWFlZNdleKjY2llEyQkhLRi1PhBDSwsja11YkEmH//v3YsmULVFVVmzkVtyxZsgQhISFYtGjRO/ds55Nbt24BaLh4+P333zc5TnuRAzNmzMD8+fMRGRkJgUCAR48e4dKlSwgICMCyZctYx2tWmZmZH3yutbX1v5iE2zZt2oSnT5+iqqoKWlpaAIAXL15ARUUFqqqqePLkCYyMjJCYmAhdXV3GaZvXoEGDUF9fj5ycHKk32gcOHMgoGXunTp2Cu7s7nj171uQYX9+HExMTcfLkSalNlgKBAIsXL8aYMWMYJOMOTU1NFBcXN9m3PT09HZ06dWKUihvs7e3FXxsbG+POnTsoLS0Vbw/DVyEhIZg1a1aTJoSqqiqEhITwvgmhsrISCxcuxMGDB/H8+fMmx/n4Xtzo/PnzWL58eZP10aNHY8OGDc0fiENCQkKwa9cu+Pv7Y+nSpViyZAnu37+P3377jfevKaqNbFQb6aguslFtZKPayKapqYnx48ezjkEI4RmahEAIITwQHx+PRYsWIScnB35+fvD394eamhrrWMy0adMGV69epb3q3/K+Pcgb8XUvcqChEWPNmjX47rvvxPtHt2rVCgEBAVi5ciXjdM2rceLK+z5G8vWGaaN9+/bhp59+wq5du8TvN7m5uZg5cya++uor2NnZwcXFBZ988gnv9mtPTU2Fq6srCgsLm/wc8f3nxsTEBCNHjkRQUBDat2/POg4nKCkp4d69ezKbdR48eAATExNeP+0fEBCAy5cv49ChQ+jatSvS0tLw+PFjuLu7w93dHcHBwawjEo4RCoV4/PgxtLW1JdYTEhIwadIkPH36lFEybpg7dy4SExOxcuVKTJ06Fdu3b8eff/6JH3/8EaGhoXBzc2MdkRllZWXcuHEDpqamEut37tyBjY0NXr9+zSgZe126dMGWLVswduxYqKmp4caNG+K11NRU7N27l3VEZqg2slFtpKO6yEa1kY1qQwgh3EJNCIQQ0oKlpaVh4cKFuHDhAqZPn46goCDo6OiwjsWcr68vtLW1sXjxYtZRyEeouroaubm5qKiogIWFBS8nixQWFn7wufr6+v9iEm7r0qULfv31V/To0UNiPT09HePHj0d+fj5SUlIwfvx4FBcXswnJSI8ePdC1a1eEhISgQ4cOTZ5G1tDQYJSMPXV1daSnp1Oj3FtMTU2xZs0amU/uHD58GEuWLMHdu3ebORl3VFdXY+7cuYiOjkZdXR3k5eVRV1cHV1dXREdH827bF2dnZ0RHR0NdXR3Ozs7vPJdvo2cbJ0CUl5dDXV1d4v23rq4OFRUVmDVrFrZv384wJXt6enrYvXs3Bg8eDHV1daSlpcHY2Bh79uzBvn37cOLECdYRmenTpw8+//zzJk+ULl++HMeOHcP169cZJWOvdevWyM7Ohp6eHjp06IDjx4+jZ8+eyM/Ph42NDcrLy1lHZIZqIxvVRjqqi2xUG9moNoQQwi20HQMhhLRAeXl5WLx4MX799VdMnDgRt2/fhpGREetYnFFXV4d169bh9OnTsLa2brIn+caNGxklY+fly5cfdB6f97+NioqCi4sLlJWVYWFhwToOU3xuLPgniouLUVtb22S9trYWJSUlAICOHTvi1atXzR2NuXv37uHw4cMwNjZmHYVzvvzyS5w7d46aEN7i4uICPz8/mJqaolu3bhLHbt68iYCAALi7uzNKxw2KiorYuXMnli1bhqysLFRUVMDGxgYmJiasozGhoaEhvrnO56YmacLCwiASieDl5YWQkBCJ+igqKsLAwAC2trYME3JDaWmp+O8ndXV18R7S/fv3x+zZs1lGY27ZsmVwdnZGXl4ehg4dCgA4e/Ys9u3bh0OHDjFOx1bnzp1RXFwMPT09dOnSBXFxcejZsyeuXr2KVq1asY7HFNVGNqqNdFQX2ag2slFt3u3w4cM4ePAgioqKUF1dLXEsLS2NUSpCSEtGTQiEENLCzJkzBxERERgyZAiuXbvW5Alc0nDDwsbGBgCQlZUlcYyvewNramq+879dJBLxfkT6okWLMH/+fEyYMAHe3t7o168f60iccffuXWzduhXZ2dkAAHNzc8ybN6/JmF6+GTJkCGbOnIldu3aJ33PS09Mxe/Zs8UX7mzdvNtnDnQ/69u2L3NxcakKQYtu2bZgwYQIuXLgAKyurJo1yPj4+jJKx8+233yI+Ph49evTAiBEjYG5uDpFIhOzsbMTHx6NPnz403ej/6OnpQU9Pj3UM5qKiogA0fH4JCQmBtrY2lJWVGafiBg8PDwCAoaEh+vXr1+Q9hjQwMjJCQUEB9PT0YGZmhoMHD6JPnz44duwYNDU1WcdjysHBAb/99hvWrFmDw4cPQ1lZGdbW1oiPj+f11m0A8MUXX+Ds2bPo27cv5s2bhylTpiAiIgJFRUXw9fVlHY8pqo1sVBvpqC6yUW1ko9rItmXLFixZsgTTpk3D77//Dk9PT+Tl5eHq1auYO3cu63iEkBaKtmMghJAWRigUQklJCWZmZu88jzpcyduSkpI+6Dw+X1isra3FsWPHEB0djZMnT8LIyAienp7w8PDAJ598wjoeM7/++itcXFzQu3dv8ZOTqampuHr1Kvbv3y9zfDoflJSUYOrUqTh79qz4Jk9tbS2GDRuGPXv2oH379khMTERNTQ1GjhzJOG3zOnLkCJYuXYrAwECpN9qtra0ZJWMvIiICs2bNgpKSEtq2bSvRICYQCJCfn88wHTvV1dXYtGkT9u3bh5ycHABA165d4eLiAl9fX94/2SQSiXD48GEkJibiyZMnqK+vlzjOty0HGtXX10NJSQm3bt3i7VSIt718+VI81ep9U7D4PP0KADZt2gQ5OTn4+PggPj4eDg4OEIlEqKmpwcaNGzF//nzWEclHIDU1FSkpKTAxMYGDgwPrOJxCtZGNaiMd1UU2qo1sVJv/MDMzQ3BwMCZPngw1NTVkZGTAyMgIQUFBKC0txbZt21hHJIS0QNSEQAghLUxISMgHnRccHPwvJyGk5Xr8+DF+/vlnxMTE4M6dOxg1ahS8vb3h4OAAoVDIOl6z6tKlC9zc3LBixQqJ9eDgYPz888/Iy8tjlIw77ty5I75pampqyvsJEQCkvk4EAgFNXQHwySefwMfHB4sWLeLd+wn5782fPx8//vgjhgwZgvbt2zeZbtQ4GYCPLC0tERERgc8++4x1FObk5ORQXFwMHR0dCIVCqVOw6H1YusLCQly/fh3Gxsa8bpRrVFZWhsOHDyM/Px8BAQFo06YN0tLS0L59e3Tq1Il1PEIIIYT8jYqKCrKzs6Gvrw8dHR2cOXMG3bt3x7179/DZZ5/h+fPnrCMSQlogakIghBDCS9euXZO5DxpfnxYk/8zly5cRGRmJmJgYdOjQAS9evICWlhaioqIwePBg1vGajYqKCjIzM5uM1b937x66d++OqqoqRskIlxUWFr7zuL6+fjMl4Z42bdrg6tWr6NKlC+so5CPSpk0b/PzzzxgzZgzrKJxz7NgxrFu3Djt27EC3bt1Yx2EqKSkJdnZ2kJeXf+8ULD5PvwKA3bt3Y9KkSU2mrFRXV2P//v1wd3dnlIy9zMxMDB8+HBoaGrh//z7u3r0LIyMjLF26FEVFRdi9ezfriMx89913aN++Pby8vCTWIyMj8fTpUyxcuJBRMvaoNrJRbaSjushGtZGNaiObkZERfv31V9jY2KB3796YMWMGZs6cibi4OLi4uKC0tJR1REJIC0RNCIQQQnin8cKhvb094uLiMHLkSOTk5ODx48f44osvePm0oJyc3Aedx/en4h4/fow9e/YgKioK+fn5cHJygre3N4YPH47KykqsWLEC+/fvf+8N1pZkzJgxmDBhAjw9PSXWo6KisH//fpw+fZpRMjb8/PywcuVKtG7dGn5+fu88d+PGjc2UinxMfH19oa2tjcWLF7OOQj4ihoaGOHny5Hu34+IjLS0tVFVVoba2FoqKilBWVpY4ThdciTRvT4142/Pnz6Gjo8Prz8TDhw9Hz549sW7dOolxzikpKXB1dcX9+/dZR2TGwMAAe/fuRb9+/STWL1++DBcXFxQUFDBKxh7VRjaqjXRUF9moNrJRbWSbPn06dHV1ERwcjO3btyMwMBB2dna4du0anJ2dERERwToiIaQFkmcdgBBCyP+WjY2N1NGqf5eWltYMabhpzZo12LRpE+bOnQs1NTVs3rwZhoaGmDlzJjp06MA6HhMikQj6+vrw8PCAjY0N6zic5ODggNOnT6Nr166YMWMG3N3d0aZNG/Hx1q1bw9/fH99//z3DlM3P0dERCxcuxPXr18WjrlNTU3Ho0CGEhITg6NGjEue2dOnp6aipqQHQ8D4r6/34Q96nW7o9e/YgPDwcBQUFuHTpEvT19REWFgZDQ0OMGzeOdTxm6urqsG7dOpw+fRrW1tZQUFCQOE7NK0Sa5cuXIyQkBJGRkU1usvNdWFgY6wicdOrUKaiqqqJ///4AgO3bt2Pnzp2wsLDA9u3boaWlxTghW43bUvzdw4cPoaGhwSARd1y9ehU//vhjk/VOnTqhpKSEQSLuKCkpkfr3pLa2NoqLixkk4g6qjWxUG+moLrJRbWSj2si2ZMkS8ZZJc+fORdu2bZGSkgJHR0eMGjWKcTpCSEtFTQiEENLCODk5sY7AeXl5eRg7diwAQFFREZWVlRAIBPD19cXQoUMREhLCOGHzu3LlCiIiIsQNGV5eXnBzc+P9Bei36ejoICkpCba2tjLP0dbW5l1n/Zw5cwAAP/zwA3744QepxwDwZn/pxMRE8dfnzp1jF4TjduzYgaCgICxYsACrV68W/2xoamoiLCyM100IN2/eFDeDZWVlSRyj5hUiy8SJE7Fv3z7o6OjAwMCgSfMKn5tPPTw8WEfgpMDAQKxduxZAw/uOn58f/P39kZiYCD8/P15OBgP+09AtEAgwbNgwyMv/57JZXV0dCgoKeH+hvlWrVnj58mWT9ZycHGhrazNIxB26urpITk6GoaGhxHpycjI6duzIKBU3UG1ko9pIR3WRjWojG9VGNmNjY4kpTy4uLnBxcaEpT4SQfxU1IRBCSAsTHBzMOgLnaWlp4dWrVwAantjJysqClZUVysrKeLt/fe/evdG7d29s2rQJhw8fRlRUFBYuXAgHBwd4e3tjxIgRrCMy9yGj6QQCAe/2sq+vr2cdgZNqamqgrKyMGzdu8H4Pcmm2bt2KnTt3wsnJCaGhoeL13r17IyAggGEy9t5uZCHkQ3l4eOD69euYMmUK2rdvTw0rf5OXl4eoqCjk5eVh8+bN0NHRwcmTJ6GnpwdLS0vW8ZgoKCiAhYUFAODXX3+Fg4MD1qxZg7S0NIwZM4ZxOnYaG7pv3LgBe3t7qKqqio8pKirCwMAA48ePZ5SOGxwdHbFixQocPHgQQMPn36KiIixcuJD3tZkxYwYWLFiAmpoaDB06FABw9uxZfPPNN/D392ecji2qjWxUG+moLrJRbWSj2sgma1f2iooKKCkpNXMaQghfUBMCIYQQ3hk4cCDOnDkDKysrTJgwAfPnz0dCQgLOnDmDYcOGsY7HlJKSEqZMmYIpU6agoKAA3t7eGDVqFJ4+fSqx9QBfJSUlYf369cjOzgYAWFhYIDAwEAMGDGCcjHCNgoIC9PT06GkCGQoKCqRu/dKqVStUVlYySEQ+Zr///jvKy8vh7u7OOgozx48fx+nTp8Wj9cl/JCUlYfTo0bCzs8P58+exevVq6OjoICMjAxERETh8+DDriEwoKiqKm2/j4+PFr582bdpIfcqdLxobug0MDDBp0iS6KC/Fhg0b8OWXX0JHRwevX7/GoEGDUFJSAltbW6xevZp1PKYCAwPx/PlzzJkzB9XV1QAa/r5auHAhvv32W8bp2KLayEa1kY7qIhvVRjaqTVN+fn4AGpoGg4KCoKKiIj5WV1eHy5cvo0ePHozSEUJaOoFIVgsUIYSQj1Jjp+/7JCQk/MtJuKu0tBRv3rxBx44dUV9fj3Xr1iElJQUmJiZYunQp77cgePjwIaKjoxEdHY2qqiq4u7tj1apVEuNo+ejnn3+Gp6cnnJ2dYWdnB6BhpN+RI0cQHR0NV1dXxgnZuXr1KhITE/HkyZMmkxH4vH99REQEYmNjsWfPHmri+RsLCwt89913GDduHNTU1JCRkQEjIyNs3boVUVFRvB4dDwDXrl3DwYMHUVRUJL541ig2NpZRKu4yMzPDvXv3eN30Y2ZmhoMHD8La2pp1FM6xtbXFhAkT4OfnJ/F+c+XKFTg7O+Phw4esIzLh6OiI6upq2NnZYeXKlSgoKECnTp0QFxeHr7/+Gjk5OawjMldWVobDhw8jLy8PgYGBaNOmDdLS0tC+fXvxnsp8lpycjIyMDFRUVKBnz54YPnw460icUVFRgezsbCgrK8PExAStWrViHYkzqDayUW2ko7rIRrWRjWrzH0OGDAEA8faiioqK4mONU54CAgJgYmLCKiIhpAWjJgRCCGlhhEIh9PX1MXbs2Cb7Ab9t06ZNzZiKGwYOHIijR49CU1MTAHD06FGMGDECysrKbINxQHV1NY4cOYKIiAhcuHABo0ePhpeXF0aPHg05OTnW8TjB3NwcX331FXx9fSXWN27ciJ07d4qnI/DNmjVrsHTpUpiamjYZAS4QCHjd8GRjY4Pc3FzU1NRAX18frVu3ljjO5xvtu3btwvLly7FhwwZ4e3tj165dyMvLw3fffYddu3bBxcWFdURm9u/fD3d3d9jb2yMuLg4jR45ETk4OHj9+jC+++IK3+7TX1NRg1KhRCA8PpwtkUhw/fhxbt25FeHg4DAwMWMfhFFVVVdy8eROGhoYSTQj379+HmZkZ3rx5wzoiE0VFRZgzZw4ePHgAHx8feHt7AwB8fX1RV1eHLVu2ME7IVmZmJoYPHw4NDQ3cv38fd+/ehZGREZYuXYqioiLs3r2bdcRm1aZNG+Tk5KBdu3bw8vLC5s2boaamxjoWIYQQQj6Qp6cnNm/eDHV1ddZRCCE8Qk0IhBDSwnz//feIiorC8+fP4ebmBi8vL9qP/P8IhUKUlJRAR0cHAKCuro4bN27AyMiIcTL22rZtCzU1NXh4eGDq1KniGv0dn/9YadWqFW7dugVjY2OJ9dzcXHTr1o23NzHat2+PtWvXYtq0aayjcE5ISMg7jzeOfOarX375BcuXL0deXh4AoGPHjggJCRHfCOMra2trzJw5E3PnzhXfMDU0NMTMmTPRoUOH9/5ctWTa2triyUVEkpaWFqqqqlBbWwsVFZUmjailpaWMkrHXuXNnHDx4EP369ZNoQjhy5AgCAgLE70GEvG3YsGHo1asX1q1bJ/Fzk5KSAldXV9y/f591xGalqqqKzMxMGBkZQU5ODiUlJdDW1mYdi5NompFsVBvZqDbSUV1ko9rIRrUhhBDu4PdcZUIIaYECAwMRGBiIS5cuITIyEnZ2djA1NYWXlxdcXV15fRP576gP7z9evHiBFy9eYOXKlVi1alWT4yKRCAKBgNejrnV1dXH27NkmTQjx8fHQ1dVllIo9oVAo3p6CSOJ7k8H7uLm5wc3NDVVVVaioqJDZ/MQ3eXl5GDt2LICG8ZiVlZUQCATw9fXF0KFDed2EMGXKFERERCA0NJR1FM4JCwtjHYGzXFxcsHDhQhw6dAgCgQD19fVITk5GQEAA3N3dWcdjqr6+Hrm5uVK3Uxo4cCCjVNxw7do1/PTTT03WO3XqhJKSEgaJ2LK1tYWTkxN69eoFkUgEHx8fmdPkIiMjmzkdd7xvmhGfUW1ko9pIR3WRjWojG9WGEEK4hZoQCCGkhbK1tYWtrS02b96MQ4cOYfv27QgICMCjR4+oEYE0kZiYyDoC5/n7+8PHxwc3btxAv379ADTshRsdHY3NmzczTseOr68vtm/fTjfApHj9+jXOnDkj3lfb1NQUw4cPpy1g/kZFRQUqKiqsY3CGlpYWXr16BaDhZldWVhasrKxQVlaGqqoqxunYqq2tRWRkJOLj49GrV68mW5xs3LiRUTL2PDw8WEfgrDVr1mDu3LnQ1dVFXV1GNp8OAACU90lEQVQdLCwsUFdXB1dXVyxdupR1PGZSU1Ph6uqKwsLCJo25fG88BRomYL18+bLJek5ODi8nAPz888/YtGkT8vLyIBAIUF5eztspYO+yZs0abNq0STzNaPPmzRLTjPiMaiMb1UY6qotsVBvZqDaEEMIttB0DIYS0cBcvXkRkZCQOHToES0tLJCYm8vYGmFAoRExMDDQ0NAAAkydPRlhYGNq3by9xnqOjI4t45CNw5MgRbNiwAdnZ2QAAc3NzBAYGYty4cYyTsVNfX4+xY8ciJycHFhYWTUaA83Xc4dGjRzF9+nQ8e/ZMYr1du3aIiIiAg4MDo2Tc8Pz5cwQFBSExMVHqE7h8Hh3v6uqK3r17w8/PDytXrsTWrVsxbtw4nDlzBj179uTtawoAhgwZIvOYQCBAQkJCM6bhnry8PERFRSEvLw+bN2+Gjo4OTp48CT09PVhaWrKOx9yDBw9w8+ZNVFRUwMbGhvfbevTo0QNdu3ZFSEgIOnToAIFAIHG88fMyX02fPh3Pnz/HwYMH0aZNG2RmZkJOTg5OTk4YOHAgr5svDQ0Nce3aNbRt25Z1FM5p3bo1bt26BQMDA7Rt2xbnzp2DlZUVsrOzMXToUBQXF7OOyAzVRjaqjXRUF9moNrJRbQghhFtoEgIhhLRAjx49QnR0NKKjo/Hy5UtMmTIFly9fhoWFBetozP39ScGZM2dKfE9PfhFpamtrsWbNGnh5eeHixYus43CKj48PEhMTMWTIELRt27bJTQw+SklJwZdffglHR0f4+/vD3NwcAHD79m1s2LABX375JZKSkvDZZ58xTsrO1KlTkZubC29vb7Rv355+bt6ybds28dOlS5YsgYKCAlJSUjB+/HheP7UN0NSed0lKSsLo0aNhZ2eH8+fPY/Xq1dDR0UFGRgYiIiJw+PBh1hGZWbFiBQICAqCrqyuxfdLr16/x/fffIygoiGE6du7du4fDhw832WaKNGj8fa2jo4PXr19j0KBBKCkpga2tLVavXs06HlMFBQUfdJ6VlRVOnDjBq23LaJqRbFQb2ag20lFdZKPayEa1IYQQbqEmBEIIaWHGjBmDxMREjBw5Et9//z3Gjh0LeXl6uwfQ5ElbQj6UvLw81q1bx/u9o6WJiYnBr7/+Kt7DngCrVq2Cp6cnfvzxR4n1fv36oV+/fpg5cyZWrFiBEydOMErI3oULF3Dx4kV0796ddRROaJx60Lp1a2RlZYm3fBEKhVi0aBHjdNxRXl6Ouro6tGnTRmK9tLQU8vLyvN5uatGiRVi1ahX8/PygpqYmXh86dCi2bdvGMBl7ISEhmDVrVpNtX6qqqhASEsLbJoS+ffsiNzeXmhBk0NDQwJkzZ5CcnIyMjAxUVFSgZ8+eGD58OOtoH4379++jpqaGdYxmNXDgQJw5cwZWVlaYMGEC5s+fj4SEBJw5cwbDhg1jHY8pqo1sVBvpqC6yUW1ko9oQQgi30HYMhBDSwgiFQnTo0AE6OjrvfLI0LS2tGVMR8vEbN24cnJ2dad/tv9HX18fp06dhZmbGOgpntGnTBklJSbCyspJ6PDMzE4MGDcKLFy+aORl3fPrpp9i6dSuvp0G8TUFBAQ8fPkT79u0hJyeH4uJi6OjosI7FOaNHj4aDgwPmzJkjsR4eHo6jR4/yurFHVVUVN2/ehKGhIdTU1JCRkQEjIyPcv38fZmZmvN67XSgU4vHjx9DW1pZYT0hIwKRJk/D06VNGydg6cuQIli5disDAQFhZWTXZTsna2ppRso8LH5/2/1BvvxfxRWlpKd68eYOOHTuivr4e69atQ0pKCkxMTLB06VJoaWmxjsgM1UY2qo10VBfZqDayUW0IIYRb6NFYQghpYYKDg1lHIKRFGj16NBYtWoSbN2+iV69eaN26tcRxR0dHRsnYWr58OYKDgxEVFdXkKVO+ev369TufyNbQ0OD1DUEA+OGHH7Bo0SIEBQWhW7duTW5+8e2JdgMDA2zZsgUjR46ESCTCpUuXZF4gGzhwYDOn447Lly9j48aNTdYHDx6MJUuWMEjEHZqamiguLoahoaHEenp6Ojp16sQoFVtaWloQCAQQCATo2rWrRHNuXV0dKioqMGvWLIYJ2Ro/fjwAwMvLS7wmEAggEoloe7J/gI9P+xPpamtr8ccff8De3h4ATTN6G9VGNqqNdFQX2ag2slFtCCGEe2gSAiGEEEKkevjwIQCgc+fOjJNwg1AolHmMzxfrbWxskJeXB5FIBAMDgyY3k/k4dcXa2hq+vr7w9PSUejwyMhJhYWHIzMxs5mTcce/ePbi6ujb5+eDrza/ffvsNs2bNwpMnT8Q3AaXhY23e1rp1a6SmpjaZMnLz5k307duX1/u8BgQE4PLlyzh06BC6du2KtLQ0PH78GO7u7nB3d+dlk2pMTAxEIhG8vLwQFhYGDQ0N8TFFRUUYGBjA1taWYUK2CgsL33lcX1+/mZJ83Pj4tP+H4mNtVFRUkJ2dTa8fKag2slFtpKO6yEa1kY1qQwgh3EKTEAghhBAiVl9fj1WrVmHDhg2oqKgA0HAB0d/fH0uWLHnnjfiWrr6+nnUETnJycmIdgXM8PT0REBCA9u3bY8yYMRLHjh8/jm+++QaLFy9mlI4b3NzcoKCggL1796J9+/bv3D6ID5ycnODk5ISKigqoq6vj7t27tB2DFH369MFPP/2ErVu3SqyHh4ejV69ejFJxw5o1azB37lzo6uqirq4OFhYWqKurg6urK5YuXco6HhON2ycZGhqiX79+TZrk+I4uzhPyv9enTx/cuHGDXl9SUG1ko9pIR3WRjWojG9WGEEK4hZoQCCGEECK2ZMkSREREIDQ0FHZ2dgCAixcvYvny5Xjz5g1Wr17NOCEb9+/fx5kzZ1BTU4NBgwbB0tKSdSTO4OPTte8zf/58pKSk4PPPP4epqSnMzc0hEomQnZ2Ne/fuwcnJCQsWLGAdk6msrCykp6fD1NSUdRROUVVVRWJiIgwNDSEvT3+q/d2qVaswfPhwZGRkYNiwYQCAs2fP4urVq4iLi2Ocjh2RSISSkhJs2bIFQUFBuHnzJioqKmBjYwMTExPW8ZgbNGiQ+Os3b96gurpa4jjftn/5u9u3b6OoqKhJXfi6zRQh/z/mzJkDPz8/PHjwQOr2bdbW1oySsUe1kY1qIx3VRTaqjWxUG0II4RbajoEQQghvXb9+HdnZ2QAACwsL9OzZk3Ei9jp27Ijw8PAmF55///13zJkzB3/++SejZOwkJibi888/x+vXrwEA8vLyiIyMxJQpUxgn45a3X0+WlpawsbFhnIi9AwcOYN++fcjJyQEAdO3aFS4uLnBxcWGcjL2BAwciKCgIw4cPZx2FfGRu3LiB77//Hjdu3ICysjKsra3x7bff8vpme319PZSUlHDr1i1e10GWqqoqfPPNNzh48CCeP3/e5DhftzjJz8/HF198gZs3b0psA9M4mYavdfmn+LLlQJs2bZCTk4N27drBy8sLmzdvhpqa2jv/nb1792LcuHFNbgC1ZNKmxjW+vvi+pRLVRjaqjXRUF9moNrJRbQghhFuoCYEQQgjvPHnyBC4uLjh37hw0NTUBAGVlZRgyZAj2798PbW1ttgEZUlJSQmZmJrp27SqxfvfuXfTo0UN8I55P+vfvj3bt2mHHjh1QUlLC0qVLceTIETx69Ih1NE6g1xP5bxw6dAjLly9HYGAgrKysmoxJpydUCPlnLC0tERERgc8++4x1FM6ZO3cuEhMTsXLlSkydOhXbt2/Hn3/+iR9//BGhoaFwc3NjHZEJBwcHyMnJYdeuXTA0NMSVK1fw/Plz+Pv7Y/369RgwYADriB8FvjQhqKqqIjMzE0ZGRpCTk0NJSQl9xpOisLDwncf5PB6caiMb1UY6qotsVBvZqDaEEMIt1IRACCE88ObNGygpKbGOwRmTJk1Cfn4+du/eDXNzcwANo2g9PDxgbGyMffv2MU7ITt++fdG3b19s2bJFYn3evHm4evUqUlNTGSVjR1NTEykpKbCwsADQ8ESluro6Hj9+jLZt2zJOxx69nsh/g55QIf+t+vp65Obm4smTJ6ivr5c4NnDgQEap2Dt27BjWrVuHHTt2oFu3bqzjcIqenh52796NwYMHQ11dHWlpaTA2NsaePXuwb98+nDhxgnVEJtq1a4eEhARYW1tDQ0MDV65cgampKRISEuDv74/09HTWET8KfHnaf8SIEXj8+DF69eqFmJgYTJo0CcrKylLPjYyMbOZ0hBBCCCGEEC6ijUYJIaSFqq+vx+rVqxEeHo7Hjx8jJycHRkZGWLZsGQwMDODt7c06IjOnTp1CfHy8+IYp0LAdw/bt2zFy5EiGydhbt24dxo4di/j4eNja2gIALl26hAcPHvD2Iv3Lly/Rrl078fcqKipQVlZGeXk5NSGAXk/kv1NQUMA6AvkIpaamwtXVFYWFhfh7Lz3fm1fc3d1RVVWF7t27Q1FRscnNwdLSUkbJ2CstLRU/pa6uri6uRf/+/TF79myW0Ziqq6sTj9Nv164dHj16BFNTU+jr6+Pu3buM07Hx9ybcd/Hx8QEAuLq6/ltxOOXnn3/Gpk2bkJeXB4FAgPLycrx584Z1LM7ZvXv3O4+7u7s3UxLuodrIRrWRjuoiG9VGNqoNIYRwC01CIISQFmrFihWIiYnBihUrMGPGDGRlZcHIyAgHDhxAWFgYLl26xDoiM2pqarhw4QJ69OghsZ6eno5Bgwbh5cuXbIJxxKNHj7B9+3bcuXMHAGBubo45c+agY8eOjJOxIRQKERMTAw0NDfHa5MmTERYWhvbt24vXHB0dWcRjjl5PhPx7Hj58CADo3Lkz4yTc0KNHD3Tt2hUhISHo0KGDeO/6Rm+/T/NNTEzMO497eHg0UxLusba2xtatWzFo0CAMHz4cPXr0wPr167FlyxasW7dO/DrjmwEDBsDf3x9OTk5wdXXFixcvsHTpUvz000+4fv06srKyWEdsdoaGhhLfP336FFVVVRLbTamoqEBHRwf5+fkMEnKDoaEhrl27Rs24UmhpaUl8X1NTg6qqKigqKkJFRYXXDWFUG9moNtJRXWSj2shGtSGEEG6hJgRCCGmhjI2N8eOPP2LYsGESe5XeuXMHtra2ePHiBeuIzIwbNw5lZWXYt2+f+Mb6n3/+CTc3N2hpaeHIkSOME7JTVFQEXV3dJjd2Go/p6ekxSMWWtLHxf8fnJ3Dp9UT+W3v27EF4eDgKCgpw6dIl6OvrIywsDIaGhhg3bhzreMzU19dj1apV2LBhAyoqKgA0NPv4+/tjyZIlH/Se1FK1bt0aGRkZMDY2Zh2FfEQ2bdoEOTk5+Pj4ID4+Hg4ODhCJRKipqcHGjRsxf/581hGZOH36NCorK+Hs7Izc3Fx8/vnnyMnJQdu2bXHgwAEMHTqUdUSm9u7dix9++AEREREwNTUFANy9exczZszAzJkz4ebmxjgh+Vjcu3cPs2fPRmBgIOzt7VnH4RSqjWxUG+moLrJRbWSj2hBCCDvUhEAIIS2UsrIy7ty5A319fYkmhNu3b6NPnz7iGxt89ODBAzg6OuLWrVvQ1dUVr3Xr1g1Hjx7l9ROncnJyKC4uho6OjsT68+fPoaOjw9sb7UQ2ej2R/8aOHTsQFBSEBQsWYPXq1eJpPdHR0YiJiUFiYiLriMx8++23iIiIQEhICOzs7AAAFy9exPLlyzFjxgysXr2acUJ2hg4dim+++QajRo1iHYVzTpw4ATk5uSYXVuPi4lBXV4fRo0czSsY9hYWFuH79OoyNjWFtbc06DqeUlpZCS0tLajMq33Tp0gWHDx+GjY2NxPr169fx5Zdf8m5boS1btuCrr76CkpLSe7etaNyqgvzHtWvXMGXKFPGkOfIfVBvZqDbSUV1ko9rIRrUhhBA25FkHIIQQ8u+wsLDAhQsXoK+vL7Eu7WIa3+jq6iItLQ3x8fESWw4MHz6ccTL2RCKR1AvPFRUVUFJSYpCIcB29npqysbGR+jrS0NBA165dsWDBApibmzNIxh1bt27Fzp074eTkhNDQUPF67969ERAQwDAZezExMdi1a5fEFi/W1tbo1KkT5syZw+smhHnz5sHf3x8lJSWwsrKCgoKCxHE+31BetGiRxGupUX19PRYtWkRNCG/R19dv8vmYb2pqaqCsrIwbN26gW7du4vU2bdowTMUtxcXFqK2tbbJeV1eHx48fM0jE1qZNm+Dm5gYlJSVs2rRJ5nkCgYCaEKSQl5fHo0ePWMfgJKqNbFQb6aguslFtZKPaEEIIG9SEQAghLVRQUBA8PDzw559/or6+HrGxsbh79y52796NP/74g3U8Zt6+6DpixAiMGDGCdSRO8PPzA9Bw4XDZsmVQUVERH6urq8Ply5fRo0cPRukI1wkEAno9vcXJyUnqellZGdLS0tCjRw8kJCSIn3Lno4KCAqkNca1atUJlZSWDRNxRWloKMzOzJutmZma838N0/PjxAAAvLy/xmkAgEDfQ8Xlaz71792BhYdFk3czMDLm5uQwSsbd79+4POs/d3f1fTsI9CgoK0NPT4/Vr5n2GDRuGmTNnYteuXejZsyeAhikIs2fP5mWj5duTH/g2BeKfOHr0qMT3IpEIxcXF2LZtG68/9wFUm3eh2khHdZGNaiMb1YYQQriFtmMghJAW7MKFC1ixYgUyMjJQUVGBnj17IigoCCNHjmQdjSkjIyMcOXIE3bt3Zx2FM4YMGQIASEpKgq2tLRQVFcXHFBUVYWBggICAAJiYmLCKSDgmISEBX3/9NVJTU6Guri5xrLy8HP369UN4eDgGDBjAKCF3LVmyBKmpqTh79izrKMxYWFjgu+++w7hx4yS2DNq6dSuioqKQlpbGOiIzffv2Rd++fZuMu543bx6uXr2K1NRURsnYKywsfOdxPj/d/sknn2Dv3r0YOnSoxHp8fDxcXV3x5MkTRsnYEQqFUFVVhby8PGRd9hAIBLxt7omIiEBsbCz27NlDExCkePr0KTw8PHDq1Cnx1JXa2lrY29sjOjq6ydZlLV1jw/L7CAQCbNiw4V9Ow11CoVDie4FAAG1tbQwdOhQbNmxAhw4dGCVjj2ojG9VGOqqLbFQb2ag2hBDCLdSEQAghhHfooqtsnp6e2Lx5c5ObyoT8naOjI4YMGQJfX1+px7ds2YLExEQcOXKkmZNx361btzBkyBBe3hRstGvXLixfvhwbNmyAt7c3du3ahby8PHz33XfYtWsXXFxcWEdkJikpCWPHjoWenh5sbW0BAJcuXcKDBw9w4sQJauwhUs2cOROXLl3CkSNH0KVLFwBAbm4uxo8fj08//RS7du1inLD5WVpa4vHjx5gyZQq8vLx4vV3H286fPw9bW1v06dMHubm5qKmpgb6+Plq3bi1xHp+bwd6Wk5Mj3m7KzMwMXbt2ZZyIjcaG5UZpaWmora2FqakpgIY6ycnJoVevXkhISGARkRBCCCGEEMIx1IRACCEtlJGREa5evYq2bdtKrJeVlaFnz57Iz89nlIw9GxsbuugqQ3l5Oerq6po0Z5SWlkJeXp6aE4iYvr4+Tp06BXNzc6nH79y5g5EjR6KoqKiZk3HfnTt30L9/fzx79ox1FKZ++eUXLF++HHl5eQCAjh07IiQkBN7e3oyTsffo0SNs375dfOPL3Nwcc+bMQceOHRknY+PvY1VlcXR0/JeTcFd5eTlGjRqFa9euoXPnzgCAhw8fYsCAAYiNjYWmpibbgIxcvnwZkZGROHDgAIyNjeHt7Q03Nzdef56Rk5NDcXExduzY8c7zgoODmykR+dhs3LgR586dQ0xMDLS0tAAAL168gKenJwYMGAB/f3/GCZvXh06JABpqxydUG9moNtJRXWSj2shGtSGEEO6SZx2AEELIv+P+/ftS93n966+/8OeffzJIxB2y9msngIuLCxwcHDBnzhyJ9YMHD+Lo0aM4ceIEo2SEax4/fiweTyyNvLw8nj592oyJPh6xsbFS927ni9raWuzduxf29vZwc3NDVVUVKioqeDfaWpqamhqMGjUK4eHhWL16Nes4nPEhv7cFAgGv97fX0NBASkoKzpw5g4yMDCgrK8Pa2hoDBw5kHY2pxu1NwsLCcOjQIURFRSEgIABOTk6IjIxEq1atWEdsdo3PoVCTwfs9fPgQR48eRVFREaqrqyWO8fkmxoYNGxAXFyduQAAALS0trFq1CiNHjuRdE0J6errE9++aEsE3VBvZqDbSUV1ko9rIRrUhhBDuoiYEQghpYd5+WvD06dPQ0NAQf19XV4ezZ8/CwMCAQTJuqK2thUAggJeXl/hJQfIfly9flnpRdfDgwViyZAmDRNzn4eGBBw8e8G70bKdOnZCVlQVjY2OpxzMzM3m73+KWLVukrpeXl+P69es4fvw4Tp482cypuENeXh6zZs1CdnY2AEBFRQUqKiqMU3GDgoICMjMzWcfgnPr6etYRPgoCgQAjR47EyJEjWUfhHGVlZbi7u8PAwADBwcHYv38/tm3bxssmBKDhZ4W829mzZ+Ho6AgjIyPcuXMH3bp1w/379yESidCzZ0/W8Zh6+fKl1EbTp0+f4tWrVwwSsZWYmCj+euPGjVBTU5M5JYJvqDayUW2ko7rIRrWRjWpDCCHcRdsxEEJICyMUCmUeU1BQgIGBATZs2IDPP/+8GVNxi5qaGm7evMnrZgxZWrdujdTUVFhZWUms37x5E3379kVVVRWjZNy1ePFiFBcXIyoqinWUZjVv3jycO3cOV69ehZKSksSx169fo0+fPhgyZIjMG/ItmaGhodR1dXV1mJqawtfXF7a2ts2cilsGDx6MBQsW0GQaKXx9fdGqVSuEhoayjkI+MmfPnsXZs2fx5MmTJo0bkZGRjFKx9+effyImJgZRUVGorKzElClT4OXlBTMzM9bRmBAKhRg9evR7GzBiY2ObKRE39enTB6NHj0ZISAjU1NSQkZEBHR0duLm5YdSoUZg9ezbriMy4u7vjwoUL2LBhA/r06QOgoZE5MDAQAwYMQExMDOOE7HTq1AlxcXGwtLSUWM/KysLIkSPx6NEjRsnYo9rIRrWRjuoiG9VGNqoNIYRwC01CIISQFqbxorOhoSGuXbuGtm3bMk7EPUOHDkVSUhI1IUjRp08f/PTTT9i6davEenh4OI2uk2HNmjWsIzCxdOlSxMbGomvXrvj666/Fow7v3LmD7du3o66ujrfTMwoKClhH4Lw5c+bA398fDx8+RK9evdC6dWuJ49bW1oySsVdbW4vIyEjEx8dLrQ2fR4AT2UJCQrBixQr07t0bHTp0oCfd0bCVVFRUFJKSkmBvb48NGzZg7NixkJOTYx2NOTU1NSgrK7OOwWnZ2dnYt28fgIYJPq9fv4aqqipWrFiBcePG8boJITw8HAEBAXB1dUVNTQ2Ahhp5e3vj+++/Z5yOLZoSIRvVRjaqjXRUF9moNrJRbQghhFtoEgIhhLRAb+8pbWJiwjoO54SHhyMkJARubm5Sb/A4OjoySsZecnIyhg8fjk8//RTDhg0D0PBk5dWrVxEXF0fj6/5P48cnvt/kKSwsxOzZs3H69GmJmtjb22P79u0yJwK0dAEBAZg+fTpvn7L9ENKm9ggEAohEIggEAtTV1TFIxQ1DhgyReUwgEPBu6xfyYTp06IB169Zh6tSprKNwhlAohJ6eHtzc3NC+fXuZ5/n4+DRjKvaEQiFKSkqgo6PDOgqnffLJJ0hMTIS5uTksLCwQGhoKR0dHZGRkwM7ODhUVFawjMldZWYm8vDwAQJcuXZr8TcVHNCVCNqqNbFQb6aguslFtZKPaEEIIt1ATAiGEtFDa2tpISUmhJgQp3rVlBd9vfgHAjRs3sG7dOmRkZEBZWRnW1tb49ttv6WcJQEREBDZt2oR79+4BAExMTLBgwQJMnz6dcTK2Xrx4gdzcXIhEIpiYmIj3XuQrExMT5Ofno2/fvpg+fTomTZpEF+b/prCw8J3H9fX1mykJt9TV1SE5ORlWVla8fx2Rf6Zt27a4cuUKunTpwjoKZxgYGLy3WVAgECA/P7+ZEnGDnJwciouLqQnhPZycnDB27FjMmDEDAQEB+P333zFt2jTExsZCS0sL8fHxrCMSDqqqqkJAQAAiIyOlTong8+dBqo1sVBvpqC6yUW1ko9oQQgi3UBMCIYS0ULSnNCH/W0FBQdi4cSPmzZsHW1tbAMClS5ewbds2+Pr6YsWKFYwTEi45f/48IiMj8euvvwIAJkyYgOnTp6Nfv36MkxGuU1JSQnZ2Nm8niZD/zsKFC6Gqqoply5axjkI4jiYhfJj8/HxUVFTA2toalZWV8Pf3Fzd4b9y4kbfNcuTD0JQI2ag2slFtpKO6yEa1kY1qQwgh3EBNCIQQ0kLNmzcPu3fvhomJCe0pTf6RvLw8REVFIT8/H2FhYdDR0cHJkyehp6cHS0tL1vGY0dbWxpYtWzB58mSJ9X379mHevHl49uwZo2SEyyorK3HgwAFERUUhOTkZpqam8Pb2xtSpU985Hryl++6779C+fXt4eXlJrEdGRuLp06dYuHAho2Ts9e7dG2vXrhVviUOaun79OrKzswEAFhYW6NmzJ+NE7M2fPx+7d++GtbU1rK2toaCgIHGcPveRRklJSbCzs4O8vDzrKIQQQgghhBBCWjBqQiCEkBaK9pR+t6SkJKxfv17iJkbjHnF8lpSUhNGjR8POzg7nz59HdnY2jIyMEBoaimvXruHw4cOsIzKjqamJq1evNtmWIicnB3369EFZWRmbYOSjkZubi6ioKISHh6OiogJ//fUX60jMGBgYYO/evU0mQ1y+fBkuLi4oKChglIy9U6dO4dtvv8XKlSulNhGqq6szSsbekydP4OLignPnzkFTUxMAUFZWhiFDhmD//v3Q1tZmG5Ah+txHCCGEEEIIIYQQLqEmBEIIIbzz888/w9PTE87OzrCzswMAJCcn48iRI4iOjoarqyvjhOzY2tpiwoQJ8PPzg5qaGjIyMmBkZIQrV67A2dkZDx8+ZB2RmXnz5kFBQaHJ06QBAQF4/fo1tm/fzigZ+RhUVlbi4MGDiIiIQEpKCkxNTcVNUHwka8uB/Px8WFhY4M2bN4ySsScUCsVfv72fvUgkgkAgQF1dHYtYnDBp0iTk5+dj9+7dMDc3BwDcvn0bHh4eMDY2xr59+xgnJIR8zLS0tCTed9+ltLT0X05DCCGEEEIIIR83mr9HCCE80HjjuHPnzoyTcMPq1auxbt06+Pr6itd8fHywceNGrFy5ktdNCDdv3sTevXubrOvo6NB2AwAiIiIQFxeHzz77DEDDU9tFRUVwd3eHn5+f+Dwae00aXbx4EZGRkTh8+DBEIhEmTJiAtWvXihug+EpXVxfJyclNmhCSk5PRsWNHRqm4ITExkXUEzjp16hTi4+PFDQhAwySj7du3Y+TIkQyTEUJagrCwMPHXz58/x6pVq2Bvbw9bW1sAwKVLl3D69GksW7aMUUJCCCGEEEII+XhQEwIhhLRQ9fX1WLVqFTZs2ICKigoAgJqaGvz9/bFkyRKJJy35Jj8/Hw4ODk3WHR0dsXjxYgaJuENTUxPFxcVNbgymp6ejU6dOjFJxQ1ZWlnjf8by8PABAu3bt0K5dO2RlZYnP+9An6D5mR48e/eBzHR0d/8Uk3FRcXIyYmBhER0cjJycHn332GTZu3AgXFxeoqqqyjscJM2bMwIIFC1BTU4OhQ4cCAM6ePYtvvvkG/v7+jNOxNWjQINYROKu+vh4KCgpN1hUUFFBfX88gEXvOzs4fdF5sbOy/nISQj5+Hh4f46/Hjx2PFihX4+uuvxWs+Pj7Ytm0b4uPjJZqZCSGEEEIIIYQ0RU0IhBDSQi1ZsgQREREIDQ0VP3F78eJFLF++HG/evMHq1asZJ2RHV1cXZ8+ehbGxscR6fHw8dHV1GaXiBhcXFyxcuBCHDh2CQCBAfX09kpOTERAQAHd3d9bxmKKnk//Dycnpg87j6+h4XV1dtG3bFlOnToW3t7fEU9ukQWBgIJ4/f445c+aguroaQMMWDQsXLsS3337LOB17ZWVliIiIEG/ZYWlpCS8vL2hoaDBOxtbQoUMxf/587Nu3Tzwx488//4Svry+GDRvGOB0bfP+Z+KfevHkjfs9ppK6uzigNe3l5eYiKikJeXh42b94MHR0dnDx5Enp6erC0tGQdj6nTp09j7dq1TdZHjRqFRYsWMUhECCGEEEIIIR8XgUgkErEOQQgh5H+vY8eOCA8Pb/IU8u+//445c+bgzz//ZJSMvR07dmDBggXw8vJCv379ADSMAI+OjsbmzZsxc+ZMxgnZqa6uxty5cxEdHY26ujrIy8ujrq4Orq6uiI6OhpycHOuIhHBebGwsHB0dIS9P/b7vU1FRgezsbCgrK8PExAStWrViHYm5a9euwd7eHsrKyujTpw8A4OrVq3j9+jXi4uLEE1n46MGDB3B0dMStW7fETYMPHjxAt27dcPToUdp2ikhVVVWFb775BgcPHsTz58+bHOdjsxwAJCUlYfTo0bCzs8P58+eRnZ0NIyMjhIaG4tq1azh8+DDriEzp6+vDx8enyXSeDRs2YMuWLSgsLGSUjBBCCCGEEEI+DtSEQAghLZSSkhIyMzPRtWtXifW7d++iR48eeP36NaNk3HDkyBFs2LBB/JSpubk5AgMDMW7cOMbJuKGoqAhZWVmoqKiAjY0NTExMWEdibsiQIe/caiEhIaEZ0xBCWqoBAwbA2NgYO3fuFDey1NbWYvr06cjPz8f58+cZJ2RLJBIhPj4ed+7cAdDw+3v48OGMUxEumzt3LhITE7Fy5UpMnToV27dvx59//okff/wRoaGhcHNzYx2RCVtbW0yYMAF+fn5QU1NDRkYGjIyMcOXKFTg7O+Phw4esIzIVHR2N6dOnY/To0ejbty8A4PLlyzh16hR27tyJadOmsQ1ICCGEEEIIIRxHTQiEENJC9e3bF3379sWWLVsk1ufNm4erV68iNTWVUTLCZYmJiRgyZAjrGJz0971/a2pqcOPGDWRlZcHDwwObN29mlIy9yspKJCUloaioqMmYax8fH0ap2BEKhe9sWAEatqqora1tpkTcU1lZidDQUJw9exZPnjxBfX29xPH8/HxGydhTVlZGeno6zMzMJNZv376N3r17o6qqilEy9nbv3o1JkyY1mZhRXV2N/fv3837bICKdnp4edu/ejcGDB0NdXR1paWkwNjbGnj17sG/fPpw4cYJ1RCZUVVVx8+ZNGBoaSjQh3L9/H2ZmZnjz5g3riMxdvnwZW7ZskWha9vHxETclEEIIIYQQQgiRjWbEEkJIC7Vu3TqMHTsW8fHxsLW1BQBcunQJDx484O3F1r+rrq6WevNLT0+PUSL2Ro0ahc6dO8PT0xMeHh7icdcE2LRpk9T15cuXo6KiopnTcEd6ejrGjBmDqqoqVFZWok2bNnj27BlUVFSgo6PDyyaE2NhYmU0Ily5dwpYtW5q87/DN9OnTkZSUhKlTp6JDhw7vbdrgE3V1dRQVFTVpQnjw4AHU1NQYpeIGT09PjBo1Cjo6OhLrr169gqenJzUhEKlKS0thZGQEoOH1VVpaCgDo378/Zs+ezTIaU5qamiguLoahoaHEenp6Ojp16sQoFbf07dsXv/zyC+sYhBBCCCGEEPJRoiYEQghpoQYNGoScnBxs375dPLLY2dkZc+bMQceOHRmnY+vevXvw8vJCSkqKxLpIJIJAIODt3sAA8Oeff2LPnj2IiYlBSEgIhg4dCm9vbzg5OUFRUZF1PE6aMmUK+vTpg/Xr17OOwoSvry8cHBwQHh4ODQ0NpKamQkFBAVOmTMH8+fNZx2PCycmpydrdu3exaNEiHDt2DG5ublixYkXzB+OQkydP4vjx47Czs2MdhXMmTZoEb29vrF+/Hv369QMAJCcnIzAwEJMnT2acjq3G39N/9/DhQ2hoaDBIRD4GRkZGKCgogJ6eHszMzHDw4EH06dMHx44dg6amJut4zLi4uGDhwoU4dOgQBAIB6uvrkZycjICAAN429Lx8+RLq6urir9+l8TxCCCGEEEIIIdLRdgyEEEJ4x87ODvLy8li0aJHUJ3C7d+/OKBm3pKWlISoqCvv27QMAuLq6wtvbm+rzN3v27MHChQvx6NEj1lGY0NTUxOXLl2FqagpNTU1cunQJ5ubmuHz5Mjw8PMRNUHz16NEjBAcHIyYmBvb29vjuu+/QrVs31rGYMzQ0xIkTJ2Bubs46CudUV1cjMDAQ4eHh4i07FBQUMHv2bISGhjbZioAPbGxsIBAIkJGRAUtLS8jL/6eXvq6uDgUFBRg1ahQOHjzIMCXhqk2bNkFOTg4+Pj6Ij4+Hg4MDRCIRampqsHHjRt42zFVXV2Pu3LmIjo5GXV0d5OXlUVdXB1dXV0RHR0NOTo51xGYnJyeH4uJi6OjoyNxaiZqWCSGEEEIIIeTDUBMCIYS0YC9evEBERIR4H1MLCwt4enqiTZs2jJOx1bp1a1y/fr3JqGvS1KNHj/DTTz8hNDQU8vLyePPmDWxtbREeHg5LS0vW8ZqVs7OzxPcikQjFxcW4du0ali1bhuDgYEbJ2NLW1kZKSgpMTEzQtWtXbN26Ffb29rhz5w569eqFyspK1hGZKC8vx5o1a7B161b06NEDa9euxYABA1jH4oyff/4Zv//+O2JiYqCiosI6DidVVVUhLy8PANClSxde1ykkJET8f/39/aGqqio+pqioCAMDA4wfP553E3uOHj36wec6Ojr+i0k+LoWFhbh+/TqMjY1hbW3NOg5zRUVFyMrKQkVFBWxsbGBiYsI6EjNJSUniZuWkpKR3njto0KBmSkUIIYQQQgghHydqQiCEkBbq/PnzcHBwgIaGBnr37g0AuH79OsrKynDs2DEMHDiQcUJ2Pv30U2zatAn9+/dnHYWTampq8PvvvyMyMhJnzpxB79694e3tjcmTJ+Pp06dYunQp0tLScPv2bdZRm5Wnp6fE90KhENra2hg6dChGjhzJKBV7I0eOxLRp0+Dq6ooZM2YgMzMTPj4+2LNnD168eIHLly+zjtjs1q1bh7Vr1+KTTz7BmjVrMG7cONaROMfGxgZ5eXkQiUQwMDCAgoKCxPG0tDRGyQiXxcTEYNKkSVBSUmIdhROEQuEHncf3p7aLiorQvn37JlNE6uvr8fDhQ+jp6TFKRrisqKgIurq6TaYhiEQiPHjwgH5uCCGEEEIIIeQ9qAmBEEJaKCsrK9ja2mLHjh3icap1dXWYM2cOUlJScPPmTcYJm9fb+7peu3YNS5cuxZo1a2BlZdXk5hef93idN28e9u3bB5FIhKlTp2L69OlNRseXlJSgY8eOqK+vZ5SScMm1a9fw6tUrDBkyBE+ePIG7u7t4MkJERAR69OjBOmKzEwqFUFZWxvDhw985zjo2NrYZU3FL45PtsvB1sggAVFZWIjQ0FGfPnsWTJ0+avNfm5+czSsYd1dXVUmtDNwWJNEKhEObm5jh69Ci6dOkiXn/8+DE6duzI2wYNLy+vdx6PjIxspiTc9PbWDG97/vw5dHR0ePtzQwghhBBCCCEfSv79pxBCCPkY5ebm4vDhwxI3wOTk5ODn54fdu3czTMaGpqamxJNMIpEIw4YNkziH9ngFbt++ja1bt8LZ2VnmvuPt2rVDYmJiMydj78GDBxAIBOjcuTMA4MqVK9i7dy8sLCzw1VdfMU7HTuOkFQDQ0dHBqVOnGKbhBnd3d6n7SJP/4HOTwftMnz4dSUlJmDp1Kjp06EA/S2+5d+8evLy8kJKSIrFOv7/J+5ibm6NPnz44ePCgxOc/Pj+T8eLFC4nva2pqkJWVhbKyMgwdOpRRKu5ofF/5u4qKCprGQgghhBBCCCEfgJoQCCGkherZsyeys7NhamoqsZ6dnY3u3bszSsUOH2+a/zfOnj373nPk5eV5uQ+uq6srvvrqK0ydOhUlJSUYPnw4unXrhl9++QUlJSUICgpiHZGJoUOHIjY2FpqamhLrL1++hJOTExISEtgEYyg6Opp1BPIRO3nyJI4fPw47OzvWUThn2rRpkJeXxx9//EENGlJUVlYiKSkJRUVFqK6uljjm4+PDKBV7AoEAP/zwA3755ReMHTsW69atE9eDzz9DR44cabJWX1+P2bNnS0yM4Bs/Pz8ADT8by5Ytg4qKivhYXV0dLl++zMspT4QQQgghhBDyT9F2DIQQ0kIdOHAA33zzDebNm4fPPvsMAJCamort27cjNDQU5ubm4nOtra1ZxeScrKysJtsP8E1eXh7CwsKQnZ0NALCwsMD8+fN5fUEaALS0tJCamgpTU1Ns2bIFBw4cQHJyMuLi4jBr1izejkgXCoUoKSlpMq74yZMn6NSpE2pqahglI1zTpk0b5OTkoF27dtDS0nrnzb/S0tJmTMYthoaGOHHihMTvadKgdevWuH79OszMzFhH4Zz09HSMGTMGVVVVqKysRJs2bfDs2TOoqKhAR0eHt7+jAMnfUydPnsTkyZMxYcIEBAUFwcDAgCZo/M3du3cxePBgFBcXs47CxJAhQwAASUlJsLW1haKioviYoqIiDAwMEBAQABMTE1YRCSGEEEIIIeSjQJMQCCGkhZo8eTIA4JtvvpF6TCAQ0Pji//Pq1Svs27cPu3btwvXr13ldj9OnT8PR0RE9evQQP4WbnJwMS0tLHDt2DCNGjGCckJ2amhrxFhXx8fFwdHQEAJiZmfHyQn1mZqb469u3b6OkpET8fV1dHU6dOoVOnTqxiMacs7PzB50XGxv7Lyfhlk2bNkFNTQ0AEBYWxjYMh61cuRJBQUGIiYmReAKXNDTFPXv2jHUMTvL19YWDgwPCw8OhoaGB1NRUKCgoYMqUKZg/fz7reJwxevRopKSkwNHREVeuXGEdh5Py8vJQW1vLOgYzjdPTPD09sXnzZqirqzNORAghhBBCCCEfJ5qEQAghLVRhYeEHn6uvr/8vJuGu8+fPIyIiAr/++is6duwIZ2dnjB8/Hp9++inraMzY2NjA3t4eoaGhEuuLFi1CXFwc0tLSGCVjr2/fvhgyZAjGjh2LkSNHIjU1Fd27d0dqaiq+/PJLPHz4kHXEZiUUCsVPskv7OKmsrIytW7fCy8uruaMx5+np+UHnRUVF/ctJyMfCxsZGYjJEbm4uRCIRDAwMoKCgIHEun9+HExISsHTpUqxZswZWVlZNasPnm4Wampq4fPkyTE1NoampiUuXLsHc3ByXL1+Gh4cH7ty5wzoiM0OGDMGRI0cktg16/vw5nJ2dceHCBdTX17MLx1DjtgONRCIRiouLcfz4cXh4eGDbtm2MkhFCCCGEEEIIaQmoCYEQQnimvr4eJ06cwOeff846ChMlJSWIjo5GREQEXr58iYkTJyI8PBwZGRmwsLBgHY85JSUl3Lx5s8mI2ZycHFhbW+PNmzeMkrF37tw5fPHFF3j58iU8PDwQGRkJAFi8eDHu3LnDu6faCwsLIRKJYGRkhCtXrkBbW1t8TFFRETo6OpCTk2OYkJCPR0hIyAefGxwc/C8m4TahUAgATbbyoMlOgLa2NlJSUmBiYoKuXbti69atsLe3x507d9CrVy9UVlayjkg4pnHbgUZCoRDa2toYOnQovLy8IC/P78GZlZWVCA0NxdmzZ/HkyZMmzSp83uKEEEIIIYQQQj4Ev/+qJIQQHsnNzUVkZCSio6Px9OlTXu7T7uDggPPnz2Ps2LEICwvDqFGjICcnh/DwcNbROENbWxs3btxo0oRw48YN6OjoMErFDYMHD8azZ8/w8uVLaGlpide/+uorXo5Mb5ygwtcnSAn5X+JzY8E/0TgmnTRlY2ODq1evwsTEBIMGDUJQUBCePXuGPXv2oFu3bqzjNbuXL19+8Ll8naBBr6d3mz59OpKSkjB16lR06NChSfMTIYQQQgghhJB3oyYEQghpwV6/fo1Dhw5h165dSE5OxoABAxAUFIQvvviCdTQmTp48CR8fH8yePbvJTXbSYMaMGfjqq6+Qn5+Pfv36AQCSk5Oxdu3aJmN7+UgkEuH69evIy8uDq6sr1NTUoKioyMsmhLfl5eUhLCwM2dnZABr2bZ8/fz66dOnCOBkbH7oFReM0DULIhxk0aBDrCJy1Zs0avHr1CgCwevVquLu7iz/vREREME7X/DQ1Nd9705gmaJB3OXnyJI4fPw47OzvWUQghhBBCCCHko0RNCIQQ0gJdvXoVu3btwv79+9GlSxe4ubkhJSUFP/zwA6+3HLh48SIiIiLQq1cvmJubY+rUqXBxcWEdi1OWLVsGNTU1bNiwAd9++y0AoGPHjli+fDl8fHwYp2OrsLAQo0aNQlFREf766y+MGDECampqWLt2Lf766y/eTtQ4ffo0HB0d0aNHD/GF+uTkZFhaWuLYsWMYMWIE44TNLzo6Gvr6+rCxsQHtfEb+qbq6OmzatAkHDx5EUVERqqurJY6XlpYySsYNZWVliIiIEDc9WVpawsvLCxoaGoyTsdW7d2/x1zo6Ojh16hTDNOzRU/7vZ2NjI7VRQyAQQElJCcbGxpg2bVqTbRv4QktLC23atGEdgxBCCCGEEEI+WgIRXRklhJAWxdraGi9fvoSrqyvc3NxgaWkJAFBQUEBGRgavmxAaVVZW4sCBA4iMjMSVK1dQV1eHjRs3wsvLC2pqaqzjMVNbW4u9e/fC3t4e7du3Fz9RyeeavM3JyQlqamqIiIhA27ZtkZGRASMjI5w7dw4zZszAvXv3WEdkwsbGBvb29ggNDZVYX7RoEeLi4pCWlsYoGTtz587Fvn37oK+vD09PT0yZMoVuZMiQm5uLvLw8DBw4EMrKyuInk/ksKCgIu3btgr+/P5YuXYolS5bg/v37+O233xAUFMTrhrBr167B3t4eysrK6NOnD4CGxsvXr18jLi4OPXv2ZJyQnaFDhyI2NhaampoS6y9fvoSTkxMSEhLYBOO4rKwsXm5XAQDffvstduzYASsrK4nXU2ZmJqZNm4bbt2/j7NmziI2Nxbhx4xinbX4///wzfv/9d8TExPB+4hUhhBBCCCGE/DeoCYEQQlqYVq1aYdKkSZg6dSqGDx8uvplDTQjS3b17FxEREdizZw/KysowYsQIHD16lHUsZlRUVJCdnQ19fX3WUTinbdu2SElJgampKdTU1MRNCPfv34eFhQWqqqpYR2RCSUkJN2/ebLLFSU5ODqytrfHmzRtGydj666+/EBsbi8jISKSkpGDs2LHw9vbGyJEjeX+THQCeP3+OSZMmISEhAQKBAPfu3YORkRG8vLygpaWFDRs2sI7ITJcuXbBlyxaMHTsWampquHHjhngtNTUVe/fuZR2RmQEDBsDY2Bg7d+6EvHzDUL/a2lpMnz4d+fn5OH/+POOE7AiFQpSUlEBHR0di/cmTJ+jUqRNqamoYJeOeV69eYd++fdi1axeuX7/O2+0YZsyYAT09PSxbtkxifdWqVSgsLMTOnTsRHByM48eP49q1a4xSsmNjY4O8vDyIRCIYGBhAQUFB4jgfmywJIYQQQggh5J+g7RgIIaSFyc/PR3R0NGbPno3Xr19j8uTJcHNzo5teMpiammLdunX47rvvcOzYMd7v0d6nTx+kp6dTE4IU9fX1Um9UPHz4kNfTIrS1tXHjxo0mTQg3btxocjOMT1q1aoXJkydj8uTJKCwsRHR0NObMmYPa2lrcunULqqqqrCMy5evrC3l5eRQVFcHc3Fy8PmnSJPj5+fG6CaGkpARWVlYAAFVVVZSXlwMAPv/88yY3C/nm2rVrEg0IACAvL49vvvlGYjsCPsnMzBR/ffv2bZSUlIi/r6urw6lTp9CpUycW0Tjn/PnziIiIwK+//oqOHTvC2dkZ27dvZx2LmYMHD+L69etN1l1cXNCrVy/s3LkTkydPxsaNGxmkY8/JyYl1BEIIIYQQQgj5qFETAiGEtDCdOnXCkiVLsGTJEiQkJCAyMhJ2dnaora1FdHQ0pk+fjq5du7KOyTlycnJwcnLi/QXHOXPmwN/fHw8fPkSvXr3QunVriePW1taMkrE3cuRIhIWF4aeffgLQsGdyRUUFgoODMWbMGMbpmt+KFSsQEBCAGTNm4KuvvkJ+fj769esHAEhOTsbatWvh5+fHOCU3CIVCCAQCiEQi3j5x+3dxcXE4ffo0OnfuLLFuYmKCwsJCRqm4oXPnziguLoaenh66dOki3mbg6tWraNWqFet4TKmrq6OoqAhmZmYS6w8ePOBtM1iPHj0gEAggEAgwdOjQJseVlZWxdetWBsm4oaSkBNHR0YiIiMDLly8xceJE/PXXX/jtt994Px1MSUkJKSkpMDY2llhPSUmBkpISgIYGzMav+SY4OJh1BEIIIYQQQgj5qNF2DIQQwgPl5eX45ZdfEBkZibS0NHTr1k3iyTlCGgmFwiZrjTdPBQIBr2+gPnjwAKNGjYJIJMK9e/fQu3dv3Lt3D+3atcP58+d599S/nJwciouLoa2tjbCwMGzYsAGPHj0CAHTs2BGBgYHw8fHh7RSWt7djuHjxIj7//HN4enpi1KhRUl9nfKOmpoa0tDSYmJhIbG9y7do12Nvb4/nz56wjMrNo0SKoq6tj8eLFOHDgAKZMmQIDAwMUFRXB19cXoaGhrCMy4+PjgyNHjmD9+vUSTU+BgYEYP348wsLC2AZkoLCwECKRCEZGRrhy5Qq0tbXFxxQVFaGjowM5OTmGCdlxcHDA+fPnMXbsWLi5uWHUqFGQk5OjLcr+z6pVq7BmzRrMmDEDn376KQDg6tWr2LVrFxYvXowlS5Zg06ZNOHHiBM6cOcM4LSGEEEIIIYSQjw01IRBCCM/cuHEDkZGR2LJlC+sohIPe9wQy37dpqK2txYEDB5CRkYGKigr07NkTbm5uUFZWZh2t2Unbf/zVq1cAwNsnkhvNmTMH+/fvh66uLry8vODm5oZ27dqxjsUpY8aMQa9evbBy5UqoqakhMzMT+vr6cHFxQX19PQ4fPsw6ImekpqYiJSUFJiYmcHBwYB2HqerqagQGBiI8PBy1tbUAAAUFBcyePRuhoaG8nxRBJMnLy8PHxwezZ8+W2DKImhD+45dffsG2bdtw9+5dAA3blM2bNw+urq4AgNevX0MgEPByGkJdXR02bdqEgwcPoqioCNXV1RLHS0tLGSUjhBBCCCGEkI8DNSEQQgghBADw8uVLXL58GdXV1ejTp4/E05R8V1NTAzMzM/zxxx8S+9fzmVAoxOPHj+nnRAqhUAg9PT3Y2Ni8cxJEbGxsM6bilqysLAwbNgw9e/ZEQkICHB0dcevWLZSWliI5ORldunRhHZFwWFVVFfLy8gAAXbp0gYqKCuNE3JCXl4ewsDBkZ2cDACwsLDB//nzevp5SU1MRERGBAwcOwNzcHFOnToWLiws6dOjA+yaE2tparFmzBl5eXk22xSENgoKCsGvXLvj7+2Pp0qVYsmQJ7t+/j99++w1BQUHw8fFhHZEQQgghhBBCOI2aEAghpAUZNWoUli9fjs8+++yd57169Qo//PADVFVVMXfu3GZKR7jsxo0bGDNmDB4/fgyRSAQ1NTUcPHgQ9vb2rKNxRqdOnRAfH09NCP9HKBRCQ0Pjvdst8PFJwWnTpn3QNhRRUVHNkIa7ysvLsW3bNonJInPnzkWHDh1YRyPko3P69Gk4OjqiR48esLOzA9CwVUVGRgaOHTuGESNGME7ITmVlJQ4cOIDIyEhcuXIFdXV12LhxI7y8vHg9uUdVVRVZWVkwMDBgHYWTunTpgi1btmDs2LFQU1PDjRs3xGupqanYu3cv64iEEEIIIYQQwmnUhEAIIS1IREQEgoKCoKGhAQcHB/Tu3RsdO3aEkpISXrx4gdu3b+PixYs4ceIExo4di++//x56enqsYxMOsLe3R0VFBdavXw8lJSWsXLkSN2/exL1791hH44w1a9YgJycHu3btgry8POs4zAmFQoSFhUFDQ+Od53l4eDRTIkJIS+Xl5fVB50VGRv7LSbjLxsYG9vb2CA0NlVhftGgR4uLikJaWxigZt9y9excRERHYs2cPysrKMGLECBw9epR1LCbGjRsHZ2dn+j0tQ+vWrZGdnQ09PT106NABx48fR8+ePZGfnw8bGxuUl5ezjkgIIYQQQgghnEZNCIQQ0sL89ddfOHToEA4cOICLFy+KL5AJBAJYWFjA3t4e3t7e9DQ3kdCuXTvExcWhZ8+eAICysjK0adMGZWVlUFdXZ5yOG7744gucPXsWqqqqsLKyQuvWrSWO8220vlAoRElJCXR0dFhHIR8hAwMDeHl5wdPTE7q6uqzjEI4TCoXQ19eHjY0N3vXn65EjR5oxFbcoKSnh5s2bMDExkVjPycmBtbU13rx5wygZN9XV1eHYsWOIjIzkbRNCeHg4QkJC4Obmhl69ejX5XOPo6MgoGTeYmppi9+7d6Nu3L/r374/PP/8cixYtwoEDBzBv3jw8efKEdURCCCGEEEII4TRqQiCEkBauvLwcr1+/Rtu2baGgoMA6DuEoaTeU1dTUkJmZCUNDQ4bJuMPT0/Odx/k2Wl9OTg7FxcXUhED+K2FhYYiOjkZWVhaGDBkCb29vfPHFF2jVqhXraISD5s6di3379kFfXx+enp6YMmUK2rRpwzoWp+jq6mLjxo2YMGGCxPrBgwcREBCAoqIiRskIVwmFQpnHBAIB6urqmjEN9yxatAjq6upYvHgxDhw4gClTpsDAwABFRUXw9fVtMnWEEEIIIYQQQogkakIghBBCCIRCIRISEiRu6vTr1w8HDx5E586dxWvW1tYs4hEOokkI5H8hLS0N0dHR2LdvH+rq6uDq6govLy/xVBZCGv3111+IjY1FZGQkUlJSMHbsWHh7e2PkyJEQCASs4zGzYsUKBAQEYP369di0aRMWLVqEfv36AQCSk5Oxdu1a+Pn5YdmyZYyTEvJxS01NRUpKCkxMTODg4MA6DiGEEEIIIYRwHjUhEEIIIQRCoRACgUDqmOvGdb4+FVdfX4/vv/8eR48eRXV1NYYNG4bg4GAoKyuzjkZIi1FTU4MffvgBCxcuRE1NDaysrODj4wNPT09e32B+m4eHBx48eICEhATWUZgrLCxEdHQ0du/ejdraWty6dQuqqqqsYzHROJVGW1sbYWFh2LBhAx49egQA6NixIwIDA+Hj40OvI/JOb968gZKSEusYnPLdd9+hffv28PLykliPjIzE06dPsXDhQkbJCCGEEEIIIeTjIM86ACGEEELYKygoYB2Bs1avXo3ly5dj+PDhUFZWxubNm/HkyRNERkayjkbIR6+mpgZHjhxBVFQUzpw5g88++wze3t54+PAhFi9ejPj4eOzdu5d1TE7o1KnTO8en88nbjXN8bI57W2PzoEAggK+vL3x9ffHq1SsADdsqESJLXV0d1qxZg/DwcDx+/Bg5OTkwMjLCsmXLYGBgAG9vb9YRmfrxxx+l/v6xtLSEi4sLNSEQQgghhBBCyHvQJARCCCGEkHcwMTFBQEAAZs6cCQCIj4/H2LFj8fr1a7ohSN5rz549CA8PR0FBAS5dugR9fX2EhYXB0NAQ48aNYx2PmbS0NERFRWHfvn0QCoVwd3fH9OnTYWZmJj4nKysLn376KV6/fs0wKeGKt7djuHjxIj7//HN4enpi1KhRvH4vFgqFePz4MbS1tVlHIR+ZFStWICYmBitWrMCMGTOQlZUFIyMjHDhwAGFhYbh06RLriEwpKSkhOzsbhoaGEuv5+fmwsLDAmzdvGCUjhBBCCCGEkI8DTUIghBBCCHmHoqIijBkzRvz98OHDIRAI8OjRI3Tu3JlhMsJ1O3bsQFBQEBYsWIDVq1eLn9jW1NREWFgYr5sQPv30U4wYMQI7duyAk5MTFBQUmpxjaPj/2rvzsKrL/P/jr3MAFUhBkuOImSsaSAqpLVpjmmbaiGalXpri4NIyheOW1pSl05g6aYzURFOYS41paYVToamFigtugAtqiYkVhKYEQW6H8/vDr/wiXMj03Idzno/r6rrg/nz+eOp1dVQ+7899N9XAgQMN1MHVPPbYY3r33XfVqFEjxcbGatGiRapXr57pLJfRsmXLSx63cOzYMSfVuIbk5OQq3xsdHX0VS1zXggUL9J///Ed33XWXHnnkkfL1tm3bau/evQbLXEOjRo2UlpZWaQghLS1NISEhhqoAAAAAoPpgCAEA3Ny2bduUnZ0tSQoPD9dNN91kuAioXs6cOVPpnGQfHx+dPn3aUBGqi4SEBL3xxhvq27evpk+fXr7evn17jR8/3mCZeTk5OWrcuPFF7/H399dbb73lpCKzxo4dW+V7Z8+efRVLXFNiYqKuv/56NWvWTKmpqUpNTT3vfcuWLXNymWuYMmWKAgICTGe4lL59+1bpPovF4rFHenz77bdq0aJFpfWysjL+jiNp5MiR+utf/6rTp0+ra9eukqTVq1frySef1Lhx4wzXAQAAAIDrYwgBANxUQUGBBg4cqC+++EKBgYGSpMLCQnXp0kXvvvsu2/YCVeRwODRs2DDVrFmzfO3EiRN65JFH5O/vX77mqQ+/cGEHDx5UVFRUpfWaNWuqpKTEQJHruNQAgqfZsWNHle671Nvu7mro0KEe+2uvioEDB8pms5nOcCllZWWmE1xeeHi41q1bV+nz+P333z/vn12eZsKECfrhhx/02GOP6dSpU5LOHtEwceJEPfXUU4brAAAAAMD1MYQAAG7qiSeeUHFxsXbv3q2wsDBJ0p49exQTE6O4uDgtWrTIcCFQPcTExFRae+ihhwyUoLpp2rSpMjIyKj3gSUlJKf9c9lRWq/WiD5U97c3kzz//3HSCS5s3b57pBJfFcAYu1+TJkxUTE6Nvv/1WZWVlWrZsmfbt26cFCxbof//7n+k84ywWi2bMmKFnn31W2dnZ8vX1VWhoaIWhVAAAAADAhTGEAABuKiUlRatWrarwoCs8PFyvvvqq7r77boNlqA6OHDmiffv2SZJatWrl0TtneMp28Ljyxo4dq7/85S86ceKEHA6H0tPTtWjRIr344ot68803TecZ9cEHH1T4/vTp09qxY4fmz5+vKVOmGKpyDT/++KPsdruCgoIqrB87dkze3t6qU6eOoTK4IofDYTqhWigpKVFqaqpyc3PL32o/Jy4uzlCVWX369NHy5cs1depU+fv7a/Lkybrpppu0fPlyde/e3XSey7jmmmvUoUMH0xkAAAAAUO1YHPzUAgDcUu3atbVu3TpFRkZWWN+xY4c6d+6soqIiM2FwaSUlJXriiSe0cOHC8jeRvby8NHToUCUkJMjPz89wIVC9vPPOO3r++ed14MABSVJISIimTJmi4cOHGy5zTf/973+1ePFiffTRR6ZTjOnZs6d69+6txx57rMJ6YmKikpOT9cknnxgqA6qnHTt2qFevXiotLVVJSYmCgoJ09OhR+fn5yWazKScnx3QiAAAAAABuhyEEAHBTffr0UWFhoRYtWqSQkBBJ0rfffqvBgwerbt26ld5CBSTp4Ycf1qpVq/TKK6+oU6dOkqT169crLi5O3bt312uvvWa4EKieSktL9dNPP3Fu+yXk5OSoTZs2+umnn0ynGBMUFKS0tLRKR3bs3btXnTp10g8//GCoDKie7rzzTrVs2VKJiYkKCAhQZmamfHx89NBDD2n06NHq16+f6USjtm7dquzsbElnd01r166d4SIAAAAAgDuwmg4AAFwdr7zyioqKitSkSRM1b95czZs3V9OmTVVUVKSEhATTeXBRS5cuVVJSknr27Kk6deqoTp066tWrl9544w29//77pvOAaqVr164qLCyUpPI3biWpqKhIXbt2NVjmmn7++WfNmTNHDRs2NJ1i1MmTJ3XmzJlK66dPn9bPP/9soAio3jIyMjRu3DhZrVZ5eXnp5MmTatSokWbOnKmnn37adJ4x33zzje644w7dfPPNGj16tEaPHq0OHTro9ttv1zfffGM6DwAAAABQzXmbDgAAXB2NGjXS9u3btWrVKu3du1eSFBYWpm7duhkugysrLS1V/fr1K63bbDaVlpYaKAKqry+++KLS2eOSdOLECa1bt85AkeuoW7euLBZL+fcOh0PFxcXy8/PT22+/bbDMvJtvvln/+c9/Kg0MJiYm8oYycBl8fHxktZ59/8Jmsyk3N1dhYWEKCAjQ4cOHDdeZM2LECJ0+fVrZ2dlq1aqVJGnfvn3685//rBEjRiglJcVwIQAAAACgOuM4BgAAUO6uu+7StddeqwULFqhWrVqSzr6dHBMTo2PHjmnVqlWGCwHXl5WVJUmKjIzUmjVrFBQUVH7NbrcrJSVFr7/+ur7++mtDhebNmzevwhCC1WpVcHCwbrnlFtWtW9dgmXlpaWnq1q2bOnTooLvuukuStHr1am3ZskUrV67UHXfcYbgQqF7uvvtuDRs2TIMGDdLIkSOVlZWluLg4LVy4UMePH9fmzZtNJxrh6+urDRs2KCoqqsL6tm3bdMcddzB8CgAAAAD4XRhCAAA3MmfOnCrfGxcXdxVLUF3t2rVLPXr00MmTJ9W2bVtJUmZmpmrVqqUVK1aodevWhgudKzk5ucr3RkdHX8USVCdWq7X8Afv5/qrt6+urhIQExcbGOjsN1URGRob++c9/KiMjQ76+vmrTpo2eeuophYaGmk4Dqp2tW7equLhYXbp0UUFBgYYOHaoNGzYoNDRUSUlJioyMNJ1oRMuWLfX222/r5ptvrrCenp6uQYMG6auvvjJUBgAAAABwBwwhAIAbadq0aYXvjxw5otLSUgUGBkqSCgsLy88lz8nJMVCI6qC0tFTvvPNOhWM8Bg8eLF9fX8Nlzndu++ZLsVgsstvtV7kG1cWhQ4fkcDjUrFkzpaenKzg4uPxajRo1ZLPZ5OXlZbDQjHM7RFRFmzZtrmIJAOCjjz7StGnT9Oqrr6p9+/aSzg5sPPHEE5o4caL69u1rNhAAAAAAUK0xhAAAbuq///2v/v3vfyspKanCOa8jR47Uww8/rMGDBxsuBAD3dfr0aY0aNUqTJ0+uNCDmqc7tEHGpf34w1COVlZXpq6++UkFBgcrKyipc++Mf/2ioCqieunbtqmXLlpUP5Z5TVFSkvn37as2aNWbCDKhbt26Fo3BKSkp05swZeXt7S1L51/7+/jp27JipTAAAAACAG2AIAQDcVPPmzfX++++f95zXBx54QAcPHjRUBlfDkQPA1REYGKgdO3YwhPB/Dh06VOV7GzdufBVLXNumTZs0aNCg8h01fokBDeC3s1qtys/Pl81mq7BeUFCghg0b6vTp04bKnG/+/PlVvjcmJuYqlgAAAAAA3J236QAAwNWRl5enM2fOVFq32+36/vvvDRTBVf16u93zval87q05T3/4VVJSotTUVOXm5urUqVMVrsXFxRmqgqvq06ePPvzwQ40ZM8Z0ikvw5MGC3+KRRx5R+/bt9fHHH6tBgwYV3loGUHW/PAJmz549ys/PL//ebrcrJSVFDRs2NJFmDIMFAAAAAABnYScEAHBTvXv31rfffqs333xTN910k6SzuyCMGjVKDRs2/E1vv8NzrFq1ShMnTtS0adN02223SZI2btyoZ555RtOmTVP37t0NF5qzY8cO9erVS6WlpSopKVFQUJCOHj0qPz8/2Ww25eTkmE6Ei3nhhRc0a9Ys3XXXXWrXrp38/f0rXPfkwZUXX3xR9evXV2xsbIX1uXPn6siRI5o4caKhMvP8/f2VmZmpFi1amE4BqrVzR8BIOu8xML6+vkpISKj0OeTOioqKqnxvnTp1rmIJAAAAAMDdMYQAAG7qyJEjiomJUUpKinx8fCSdPee1R48emjdvXqUtaQFJioiIUGJiom6//fYK6+vWrdOoUaOUnZ1tqMy8O++8Uy1btlRiYqICAgKUmZkpHx8fPfTQQxo9erT69etnOhEu5mLHMFgsFo8eXGnSpIn++9//qmPHjhXWN2/erIEDB3r0kUFdu3bVk08+qXvuucd0ClCtnTvSpFmzZkpPT1dwcHD5tRo1ashms8nLy8tgofP9cjDjQhwOB0e/AAAAAAB+N45jAAA3FRwcrE8++UT79+/X3r17JUk33HCDWrZsabgMruzAgQMKDAystB4QEKCvv/7a6T2uJCMjQ6+//rqsVqu8vLx08uRJNWvWTDNnzlRMTAxDCKjEkx+kX0p+fr4aNGhQaT04OFh5eXkGilzHE088oXHjxik/P1833nhj+SDhOW3atDFUBlQv546AKSsrM1ziOj7//HPTCQAAAAAAD8EQAgC4uZYtWzJ4gCrr0KGDxo4dq4ULF6p+/fqSpO+//14TJkzQzTffbLjOLB8fH1mtVkmSzWZTbm6uwsLCFBAQoMOHDxuug6s7t/nYpd5A9RSNGjVSWlpapd0i0tLSFBISYqjKNdx///2SVGGLeIvFwtvJwO9w4MABxcfHl+/oFB4ertGjR6t58+aGy5yrc+fOVbpv165dV7kEAAAAAODuGEIAADcyduxY/f3vf5e/v7/Gjh170Xtnz57tpCpUJ3PnztV9992n66+/Xo0aNZIkHT58WKGhofrwww/NxhkWFRWlLVu2KDQ0VJ07d9bkyZN19OhRLVy4UBEREabz4KIWLFigf/7zn/ryyy8lnR0MmzBhgoYMGWK4zKyRI0fqr3/9q06fPq2uXbtKklavXq0nn3xS48aNM1xnFjtoAFfWihUrFB0drcjISHXq1EnS2YGn1q1ba/ny5erevbvhQtdQXFysRYsW6c0339S2bdsYeAIAAAAA/C4Wx7nXsgAA1V6XLl30wQcfKDAwUF26dLngfRaLRWvWrHFiGaoTh8Ohzz77rPwYj7CwMHXr1s3j3+DeunWriouL1aVLFxUUFGjo0KHasGGDQkNDlZSUpMjISNOJcDGzZ8/Ws88+q8cff7z8wdf69ev16quv6oUXXtCYMWMMF5rjcDg0adIkzZkzR6dOnZIk1apVSxMnTtTkyZMN1wFwJ1FRUerRo4emT59eYX3SpElauXKltm/fbqjMNaxdu1ZJSUlaunSpQkJC1K9fP91///3q0KGD6TQAAAAAQDXGEAIAAABwFTRt2lRTpkzR0KFDK6zPnz9fzz//PG+8S/rpp5+UnZ0tX19fhYaGqmbNmqaTjEhOTlbPnj3l4+Oj5OTki94bHR3tpCrAPdSqVUs7d+5UaGhohfX9+/erTZs2OnHihKEyc/Lz8zVv3jwlJSWpqKhI/fv3V2JiojIzMxUeHm46DwAAAADgBjiOAQAAVFBSUqLU1FTl5uaWv6F8TlxcnKEq87p27aply5YpMDCwwnpRUZH69u3L7iKoJC8vTx07dqy03rFjR+Xl5Rkocj3XXHMNb9tK6tu3r/Lz82Wz2dS3b98L3mexWNgiHfiNgoODlZGRUWkIISMjQzabzVCVOb1799batWt17733Kj4+Xvfcc4+8vLyUmJhoOg0AAAAA4EYYQgAAN3XixAklJCTo888/V0FBgcrKyipc9/StZ3F+O3bsUK9evVRaWqqSkhIFBQXp6NGj8vPzk81m8+ghhC+++KLSUIZ09v+1devWGSiCq2vRooWWLFmip59+usL64sWLKz0M8zQlJSWaPn26Vq9efd4/o3JycgyVmfHLX/+vfy8AXJ6pU6dq/PjxGjlypEaNGqWcnJzywbC0tDTNmDFDY8eONVzpfJ9++qni4uL06KOPevyfRQAAAACAq4chBABwU8OHD9fKlSv1wAMP6Oabb5bFYjGdhGpgzJgx6t27txITExUQEKBNmzbJx8dHDz30kEaPHm06z4isrKzyr/fs2aP8/Pzy7+12u1JSUtSwYUMTaXBxU6ZM0YABA7R27Vp16tRJ0tkHX6tXr9aSJUsM15k1YsQIpaamasiQIWrQoAF/RgG44qZMmaJHHnlEzz77rGrXrq1Zs2bpqaeekiSFhITo+eef98jhyvXr1yspKUnt2rVTWFiYhgwZooEDB5rOAgAAAAC4GYvD4XCYjgAAXHkBAQH65JNPyh98AVURGBiozZs3q1WrVgoMDNTGjRsVFhamzZs3KyYmRnv37jWd6HRWq7X8Aen5/trk6+urhIQExcbGOjsN1cC2bdv08ssvKzs7W5IUFhamcePGKSoqynCZWYGBgfr444/5M+r/vPvuu1V+CHj48GHl5ubyewdcgtVqLT/m5Jzi4mJJUu3atU1luYySkhItXrxYc+fOVXp6uux2u2bPnq3Y2Fh+fwAAAAAAv5vVdAAA4Opo2LAhP0DEb+bj4yOr9exfD2w2m3JzcyWdHWo5fPiwyTRjDh48qAMHDsjhcCg9PV0HDx4s/+/bb79VUVERAwi4oHbt2untt9/Wtm3btG3bNr399tseP4AgSXXr1lVQUJDpDJfx2muvKSwsTDNnziwfWPmlH3/8UZ988okGDRqkm266ST/88IOBSqD6+fUuK7Vr1+bvx//H399fsbGxWr9+vXbu3Klx48Zp+vTpstlsio6ONp0HAAAAAKjm2AkBANzUp59+qjlz5igxMVGNGzc2nYNq4u6779awYcM0aNAgjRw5UllZWYqLi9PChQt1/Phxbd682XQiUK3Y7XZ98MEH5Q+Ww8PD1adPH3l7e/apaG+//bY++ugjzZ8/X35+fqZzXEJycrISEhK0Zs0a+fv7q379+qpVq5aOHz+u/Px81atXT8OGDdOYMWNUv35907mAy7NarQoICLjkcS/Hjh1zUpHrs9vtWr58uebOnavk5GTTOQAAAACAaowhBABwU0eOHFH//v21du1a+fn5ycfHp8J1fuCK89m6dauKi4vVpUsXFRQUaOjQodqwYYNCQ0M1d+5ctW3b1nSiUQcOHFB8fHyFB8qjR49W8+bNDZfBFe3evVvR0dHKz89Xq1atJEn79+9XcHCwli9froiICMOF5kRFRZXvMNKkSZNKf0Zt377dUJl5R48e1fr163Xo0CH9/PPPqlevnqKiohQVFVW+Uw2AS7NarYqPj1dAQMBF74uJiXFSEQAAAAAAnoMhBABwU926dVNubq6GDx+u+vXrV3oLjB+4Ar/NihUrFB0drcjIyPKz2NPS0pSZmanly5ere/fuhgvham677TYFBwdr/vz5qlu3riTp+PHjGjZsmI4cOaINGzYYLjRnypQpF73+3HPPOakEgLuyWq3Kz8+XzWYznQIAAAAAgMdhCAEA3JSfn582btzo8W+uA1dKVFSUevTooenTp1dYnzRpklauXOnRb27j/Hx9fbV161a1bt26wvquXbvUoUMH/fzzz4bKAMD9eXl5KS8vjyEEAAAAAAAMYD9PAHBTN9xwAw+48Jt9//33GjJkiEJCQuTt7S0vL68K/3my7OxsDR8+vNJ6bGys9uzZY6AIrq5ly5b6/vvvK60XFBSoRYsWBooAwHPwvgUAAAAAAOZ4mw4AAFwd06dP17hx4/SPf/xDN954Y6XztuvUqWOoDK5s2LBhys3N1bPPPqsGDRpUOsbDkwUHBysjI0OhoaEV1jMyMnjLEuf14osvKi4uTs8//7xuvfVWSdKmTZs0depUzZgxQ0VFReX3esJnclBQkPbv36969eqpbt26F/18OXbsmBPLALijsrIy0wkAAAAAAHgsjmMAADdltZ7d7ObXD3kcDocsFovsdruJLLi42rVra926dYqMjDSd4jKmTp2q8ePH66WXXtLLL7+sSZMmqWPHjpKktLQ0zZgxQ2PHjtWzzz5ruBSu5tznsPT/P4vP/dX7l997ymfy/PnzNXDgQNWsWVPz58+/6L0xMTFOqgIAz5GcnFzle6Ojo69iCQAAAADA3TGEAABuKjU19aLXO3fu7KQSVCfh4eF65513FBUVZTrFZZw7Uzo4OFjx8fGaNWuWvvvuO0lSSEiIJkyYoLi4OHaNQCWX+hz+JT6TcT6/HloBgN/jl8NxF+Mpw3EAAAAAgKuHIQQAAFBu5cqVmjVrll5//XU1adLEdI5LsFqtys/Pr3DkQnFxsaSzO0cAl2PXrl2KiIgwneFUJSUl8vf3v2r3u5MFCxbon//8p7788ktJUsuWLTVhwgQNGTLEcBkAAAAAAABwad6mAwAAV05WVpYiIiJktVqVlZV10XvbtGnjpCpUJwMGDFBpaamaN28uPz8/+fj4VLjuqee0//otZIYPcDmKi4u1aNEivfnmm9q2bZvHvWXaokULjR49WjExMWrQoMF573E4HFq1apVmz56tP/7xj3rqqaecXGne7Nmz9eyzz+rxxx9Xp06dJEnr16/XI488oqNHj2rMmDGGCwEAAAAAAICLYycEAHAjv3xj22q1ymKx6Hwf82yxigvhnPbKrFarAgICLrkduqcOaODS1q5dq6SkJC1dulQhISHq16+f7r//fnXo0MF0mlPt27dPTz/9tD7++GO1bdtW7du3V0hIiGrVqqXjx49rz5492rhxo7y9vfXUU0/p4YcflpeXl+lsp2vatKmmTJmioUOHVlifP3++nn/+eR08eNBQGQB3U1JSotTUVOXm5urUqVMVrsXFxRmqAgAAAAC4A4YQAMCNHDp0SNdff70sFosOHTp00XsbN27spCqgerNarYqPj1dAQMBF7/PEAQ1cWH5+vubNm6ekpCQVFRWpf//+SkxMVGZmpsLDw03nGZWbm6v33ntP69at06FDh/Tzzz+rXr16ioqKUo8ePdSzZ0+PHD44p1atWtq1a5datGhRYf3LL7/UjTfeqBMnThgqA+BOduzYoV69eqm0tFQlJSUKCgrS0aNH5efnJ5vNppycHNOJAAA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de variables correlacionadas\n","vars_eliminar = ['Total Asignado Proyecto MINVU','Total Aporte MINVU Final (incluye incrementos)'\n","  ,'Total Disponible Proyecto (incl. ahorro familia)','Monto Incr. Obra','Total Aporte MINVU Original','dif_fechas','cantidad_etapas']\n","df_modelo_1.drop(columns=vars_eliminar,inplace=True)"],"metadata":{"id":"cjJH-y8R6K4W"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["mask = np.zeros_like(df_modelo_1.corr().fillna(0), dtype=np.bool)\n","mask[np.triu_indices_from(mask)] = True\n","plt.figure(figsize=(24,24))\n","sns.heatmap(df_modelo_1.corr(), mask=mask, annot=True,  cmap=\"BrBG\", vmin = -1, fmt='.1g', edgecolor='w', linewidth=0.6)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"hi6eXpKw71hQ","outputId":"3fc242ce-53d8-48de-c863-0874fe66aa53"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<Axes: >"]},"metadata":{},"execution_count":181},{"output_type":"display_data","data":{"text/plain":["<Figure size 2400x2400 with 2 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de variable por Information Value (IV)**"],"metadata":{"id":"bRJMV15aENO8"}},{"cell_type":"code","source":["iv, woe = iv_woe(df_modelo_1,target='target',bins=20)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"sXn1MbeVERd5","outputId":"fdcc9fb8-e78a-43ce-a972-679a1556bf3d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Information value of Postula Con Proyecto Desarrollado is 0.421415\n","Information value of Región Ejecución is 1.021865\n","Information value of Provincia is 1.646317\n","Information value of Tipología Madre is 0.112691\n","Information value of Ahorro Eximido (Aporte MINVU) is 0.023844\n","Information value of Ahorro Familia is 0.151289\n","Information value of Total Presup. Proyecto is 0.381233\n","Information value of Total Complem. is 0.337032\n","Information value of Nombre Constructora is 6.965473\n","Information value of Cumple Término PEH is 0.857802\n","Information value of SUBESTADO PROYECTO DITEC is 0.0\n","Information value of Concepto Incremento Obra is 8.138908\n","Information value of Total Incremento is 0.095401\n","Information value of Total Alza Materiales is 1.061049\n","Information value of Total Albergue Transitorio is 0.032697\n","Information value of etapa is 1.334747\n","Information value of etapa_1 is 0.12767\n","Information value of duracao_1 is 4.15959\n","Information value of etapa_2 is 0.201234\n","Information value of duracao_2 is 1.284542\n","Information value of etapa_3 is 1.029436\n","Information value of duracao_3 is 2.199101\n","Information value of etapa_4 is 0.314291\n","Information value of duracao_4 is 1.447219\n","Information value of etapa_5 is 1.121664\n","Information value of duracao_5 is 2.735159\n","Information value of etapa_6 is 0.652768\n","Information value of duracao_6 is 4.229504\n"]}]},{"cell_type":"markdown","source":["La regla dice que todo lo que tiene IV < 0.02 no tiene poder de predición y las caracteristicas con IV > 0.5 tienen valor suspechoso de predición. Así que serán eliminadas la variables afera del rango propuesto"],"metadata":{"id":"F84YRtCDFRb7"}},{"cell_type":"code","source":["elimina_iv = ['Región Ejecución','Provincia','Nombre Constructora','Cumple Término PEH','SUBESTADO PROYECTO DITEC','Concepto Incremento Obra'\n","  ,'Total Alza Materiales','etapa','duracao_1','duracao_2','duracao_3','duracao_4','etapa_5','duracao_5','etapa_6','duracao_6']\n","df_modelo_1.drop(columns=elimina_iv,inplace=True)"],"metadata":{"id":"bTsYdRKlFsvG"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["#####Paso 3: Creación de variables 0 y 1 de los regresores"],"metadata":{"id":"dB4niCvJK40U"}},{"cell_type":"markdown","source":["En esa etapa todas las variables serán convertidas en variables do tipo binário (_dummies_). Eso permite una posterior análisis de la razón de probabilidades entre grupos.\n","\n","Además, se realizará la avaliación de la estadística _weight_ _of_ _evidence_ (WoE) para grupamento y redución de características similares con base en el poder de predición."],"metadata":{"id":"FJymQFygK_nm"}},{"cell_type":"code","source":["#código de creación de dummies\n","data_dummies1 = [pd.get_dummies(df_modelo_1['Postula Con Proyecto Desarrollado'], prefix='PostulaProyecto', prefix_sep=':')\n","                 ,pd.get_dummies(df_modelo_1['Tipología Madre'], prefix='Tipologia', prefix_sep=':')\n","                 ,pd.get_dummies(df_modelo_1['etapa_1'], prefix='etapa_1',prefix_sep=':')\n","                 ,pd.get_dummies(df_modelo_1['etapa_2'], prefix='etapa_2',prefix_sep=':')\n","                 ,pd.get_dummies(df_modelo_1['etapa_3'], prefix='etapa_3',prefix_sep=':')\n","                 ,pd.get_dummies(df_modelo_1['etapa_4'], prefix='etapa_4',prefix_sep=':')]\n","\n","dummies1 = pd.concat(data_dummies1,axis=1)\n","\n","df_modelo_1 = pd.concat([df_modelo_1,dummies1],axis=1)"],"metadata":{"id":"rSI7_VQMGq74"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["Evaluación de las variables creadas por el proceso anterior"],"metadata":{"id":"mmTUNPVTMVMo"}},{"cell_type":"code","source":["df_modelo_1.info()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"XqYS3w0My_6k","outputId":"68b240b4-e6c7-417d-f56e-154620000098"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.frame.DataFrame'>\n","Int64Index: 3644 entries, 0 to 44165\n","Data columns (total 44 columns):\n"," #   Column                                      Non-Null Count  Dtype  \n","---  ------                                      --------------  -----  \n"," 0   Postula Con Proyecto Desarrollado           3644 non-null   object \n"," 1   Tipología Madre                             3644 non-null   object \n"," 2   Ahorro Eximido (Aporte MINVU)               1388 non-null   float32\n"," 3   Ahorro Familia                              1261 non-null   float32\n"," 4   Total Presup. Proyecto                      3644 non-null   float32\n"," 5   Total Complem.                              3644 non-null   float32\n"," 6   Total Incremento                            3644 non-null   float32\n"," 7   Total Albergue Transitorio                  3644 non-null   int16  \n"," 8   etapa_1                                     3644 non-null   object \n"," 9   etapa_2                                     3644 non-null   object \n"," 10  etapa_3                                     3644 non-null   object \n"," 11  etapa_4                                     1765 non-null   object \n"," 12  target                                      3644 non-null   int8   \n"," 13  PostulaProyecto:No                          3644 non-null   uint8  \n"," 14  PostulaProyecto:Sí                          3644 non-null   uint8  \n"," 15  Tipologia:CCH                               3644 non-null   uint8  \n"," 16  Tipologia:CSR                               3644 non-null   uint8  \n"," 17  etapa_1:Fecha Acta Entrega Terreno          3644 non-null   uint8  \n"," 18  etapa_1:Fecha RE Aprobación Proyecto        3644 non-null   uint8  \n"," 19  etapa_1:Fecha_complem_1                     3644 non-null   uint8  \n"," 20  etapa_1:Fecha_incr_1                        3644 non-null   uint8  \n"," 21  etapa_2:Fecha Acta Entrega Terreno          3644 non-null   uint8  \n"," 22  etapa_2:Fecha RE 1er Incr. Alza Materiales  3644 non-null   uint8  \n"," 23  etapa_2:Fecha RE Aprobación Proyecto        3644 non-null   uint8  \n"," 24  etapa_2:Fecha Término de Obra               3644 non-null   uint8  \n"," 25  etapa_2:Fecha_complem_1                     3644 non-null   uint8  \n"," 26  etapa_2:Fecha_complem_2                     3644 non-null   uint8  \n"," 27  etapa_2:Fecha_incr_1                        3644 non-null   uint8  \n"," 28  etapa_3:Fecha Acta Entrega Terreno          3644 non-null   uint8  \n"," 29  etapa_3:Fecha RE 1er Albergue Transitorio   3644 non-null   uint8  \n"," 30  etapa_3:Fecha RE 1er Incr. Alza Materiales  3644 non-null   uint8  \n"," 31  etapa_3:Fecha RE Aprobación Proyecto        3644 non-null   uint8  \n"," 32  etapa_3:Fecha Término de Obra               3644 non-null   uint8  \n"," 33  etapa_3:Fecha_complem_1                     3644 non-null   uint8  \n"," 34  etapa_3:Fecha_incr_1                        3644 non-null   uint8  \n"," 35  etapa_4:Fecha Acta Entrega Terreno          3644 non-null   uint8  \n"," 36  etapa_4:Fecha RE 1er Albergue Transitorio   3644 non-null   uint8  \n"," 37  etapa_4:Fecha RE 1er Incr. Alza Materiales  3644 non-null   uint8  \n"," 38  etapa_4:Fecha RE 2do Albergue Transitorio   3644 non-null   uint8  \n"," 39  etapa_4:Fecha RE 2do Incr. Alza Materiales  3644 non-null   uint8  \n"," 40  etapa_4:Fecha RE Aprobación Proyecto        3644 non-null   uint8  \n"," 41  etapa_4:Fecha Término de Obra               3644 non-null   uint8  \n"," 42  etapa_4:Fecha_complem_2                     3644 non-null   uint8  \n"," 43  etapa_4:Fecha_incr_1                        3644 non-null   uint8  \n","dtypes: float32(5), int16(1), int8(1), object(6), uint8(31)\n","memory usage: 391.4+ KB\n"]}]},{"cell_type":"markdown","source":["######**Evaluación de las variables categóricas**"],"metadata":{"id":"G7Ha0NIHyCsh"}},{"cell_type":"code","source":["#separación entre objetivo y variables independientes\n","X = df_modelo_1.drop(columns='target')\n","y = df_modelo_1['target']"],"metadata":{"id":"HlzcwVc9IJ-d"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["df_tipo = woe_categorical(X, 'Tipología Madre', y)\n","plot_by_woe(df_tipo)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":901},"id":"1Bm81QzZIdeO","outputId":"d31757d4-ec79-4bf0-ebba-d2f26cd40302"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["df_etapa1 = woe_categorical(X, 'etapa_1', y)\n","plot_by_woe(df_etapa1)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":886},"id":"YhO7SBc4I-31","outputId":"ee9a399e-58bb-4339-9cdb-0b9402a410f5"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 Axes>"],"image/png":"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= woe_categorical(X, 'etapa_2', y)\n","plot_by_woe(df_etapa2)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":848},"id":"vUD_YWV9fRWS","outputId":"063cd009-b8dc-4f74-c0d8-36b8a4ef7ca6"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 Axes>"],"image/png":"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= woe_categorical(X, 'etapa_3', y)\n","plot_by_woe(df_etapa3)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":871},"id":"sap_FkmWffs3","outputId":"f7e8784a-4c23-40a3-c7fd-be977230d79b"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 Axes>"],"image/png":"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= woe_categorical(X, 'etapa_4', y)\n","plot_by_woe(df_etapa4)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":846},"id":"AZ5rGe1bfvUP","outputId":"650084b6-8c96-4bee-8dbf-9904e0952302"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 Axes>"],"image/png":"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de las variábles Numéricas**"],"metadata":{"id":"jNS2KLp8MF5l"}},{"cell_type":"code","source":["X['AporteMINVU_factor'] = pd.cut(X['Ahorro Eximido (Aporte MINVU)'], 10)\n","plot_by_woe(woe_continous(X,'AporteMINVU_factor',y))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":893},"id":"yVcNyCBZhTg5","outputId":"1d5a49c3-49f6-4812-f832-38bee015b16e"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 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Q6fCp6tC9qfu8Bdjq3ycNAM4gAnh4RZokZ1yclJgoeWMj1qQkOWNjldb2VwaAM8tuk0b1kJbsqB776pB09VnmW2MBAACAjsowpL+sl3442bT5gXZzX7WhidLZXfl+GkC7UE8jaqB10iXZXS5pap21nm1j6lTZXS6N9M7VAeDMurC7exutcpe04YB19QAAAADtgc0mxTXyrvYQhzQsSbrlPOnpCdJt50vDuxG+A2g3CODhFfGSpkhy3HmnV67vuPNOTf3xPgDg8yJDpCEJ7mNrs80VPwAAAIC/qnBJ23Ol1fvqn1P7+2RJCguURiZLvx4mPXWxdPNQc9V7MI0eALQ//MsEr7nTbtc7/ftLM2ZICxa03YVvvFHOfv10R9tdEQCsN6qH9HWNll2HC6XdJxve5wIAAADwNeUVZui+KUfaekQqKjdbxwzvZq5mr21gnBQcYD43JMF89OkiBbCmFIBvIICH12RImu5yaeG8ear49FMpJ6f1F01IUMC8ebre5VKGnS+2APxIvxipa5h0tKh6bM0+AngAAAD4vhKn9N0xcxPVb4+axzWVu8znz0use25QgDRntBQb6t62EQB8BAkmvOpZu13RYWEKWLJECg9v3cXCwxWwZImiQ0M1l/AdgL+p3Iy1pk05UmGZNfUAAAAArXG6XPr8gPTCV9LvlksvfS19dahu+F5p02HP45K5UIXwHYCPIsWEV8VIWupwKGToUAV89pmU4KF3W1MkJCjgs88UMnSoljkcimnTKgGgnRjRXXLU+NLsdEnr91tXDwAAANAcBaXmXkbPbpD+a7n0v1ukb46YK9wb0iNS6hl9ZmoEgDOMFjTwujRJqxwOXTJ0qE7u2KGK2bOlV19t+gVuvFEB8+YpOjRUyxwOnee1SgHAYuFB0tAE6ctD1WNrs6WLerHiBwAAAO2bYUhPZ0onihufa5PUK9rcOHVwvBQT6vXyAMAqrIDHGZEmabvDoevCw6X58+XYsUOaPVtKSvJ8QlKSNHu2OW/+fF0fHq4dhO8AOoLRKe7Hx05LO49bUwsAAADQVDabdE7X+p+326QBsdL0s6UnLpLuHSmN70n4DsDv2QzDMKwuAlJBQYEiIyOVn5+viIgIq8vxqlWSnnW5tFiSy26XIzdXrm3b5Coqkj0sTPZBg+SMjVWAy6Wpkm6325Vhcc0AcMYYhvTH1dLhwuqxoQnSLWnW1QQAAICOzTCkg6fMTVTzS6QZ53qet/O49LfPq48ddumsOGlIghnOhwWdmXoBwMuak+XSggZnXIakDLtdRyStk7QxNlZZGRkqlRQsqa/MFfMj7XbFW1gnAFjCZjNXwS/cVj225Yj5g05kiHV1AQAAoGNxGdK+PGlTjrQlx3xnpmS2j5ncX+ocXPec3tFSTCcpJcpcRDKoqxRC9ASgY+NfQVgmXtLUHx8AgBqGd5MWf1+9WZXLkL49KqX3sLYuAAAA+DeXIe06Ya5035wj5ZXUnWPI3FjV0/emAXbpkXHsXwQANRDAAwDQ3oQGSucnSV8fNsP4UT2k5EirqwIAAIA/crqkHblm4L7liFRY1vg5m3PqXxxC+A4AbgjgAQBojyb3l64dxFt2AQAA0PYMwwzbN+dIW49Ixc6mndelk9nPfWiCd+sDAD/CT/UAALRH9HsHAACAN723XTpS1Pi8+LAfQ/dEKTnC3LMIANBkdqsLaCtffvmlLrvsMkVFRSksLEwjRozQwoULm3WN0tJSPfroo+rbt69CQkKUlJSkW2+9VUePHq33nAULFmj48OEKCwtTdHS0rrjiCn399detfTkAAAAAAACtU+HyPG6zmaF6fbpHSFf0kx4cI/0hQ7pygNQjkvAdAFrAL1bAr1ixQpMmTVJISIimTZumzp07a9GiRbr++uu1f/9+3XvvvY1ew+Vy6corr9SyZcs0YsQIXX311crKytJLL72kTz/9VJ9//rni4uLcznn88cf13//930pJSdEvf/lLnTp1Sm+88YZGjhypTz/9VOnp6d56yQAAAAAAAHXllUhbftxEtbRC+q96somhidKy3dXHPaOqV7rHhp6RUgGgI7AZhmFYXURrOJ1ODRgwQAcOHNDnn3+uIUOGSJLy8/M1fPhw7d27Vzt37lRKSkqD13n55Zf1s5/9TNOnT9eCBQtk+/G3ui+88IJ+9atf6dZbb9WLL75YNT8rK0tnnXWWevXqpS+++EKRkebmeJs3b9aIESPUq1cvffvtt7Lbm/Ymg4KCAkVGRio/P18REREt+EgAADoEw5AMsbkVAABAO3FEUqakjZJ2SSqVFCypj6Q0SemS4r1dRO5padNhM3Tfk+f+3GPjpBgPgbphSC9vlnpHS4MTpChaIAJAUzUny/X5FjSfffaZdu/erRtuuKEqfJekyMhI/f73v1dZWZleeeWVRq/zr3/9S5L05JNPVoXvknTbbbepV69eWrBggYqLi6vGX375ZTmdTj3wwANV4bskDRkyRNOnT9f333+vtWvXtsErBABA0uly6bM90qOrpG+OWF0NAABAh7dK0tUul5JcLl0t6eljx/T2ypV674MP9PbKlXr62DFdLSnJ5dI1LpdWteXNDUM6fEr6KEt6Yo30hxXS4u11w3fJDOU9sdmknw2VMlIJ3wHAi3w+gF+5cqUkaeLEiXWemzRpkiRp1aqGv8yVlJRow4YN6t+/f52V8jabTRMmTFBRUZG++uqrNr0vAABNsmyXNOf/pLe/MzfKWrPP6ooAAAA6rOOSbnC5NFbSkqwsue64Q0pKkrNrV7nGjZN+8hO5xo2Ts2tXKSlJrjvu0Hu7dmnsj+cdb+mNDUPKzjc3T310lfTYaumDndKBgobP21r/vnYAAO/z+R7wWVlZkqS+ffvWeS4hIUHh4eFVc+qze/duuVwuj9eoee2srCyNHj266s/h4eFKSKi7aUnN+fUpLS1VaWlp1XFBQSNfMAEAHVdkiFReYwOt73OlY0VSXJh1NQEAAHRAGyVd4nTqZFGRNHu2nAsWNHzC4cPS88/L+fzz0owZWjhvnpaHhWmpw6G0pt7UZUiLv5c25UgnihufL0mdHNI58WZP97PiGp8PAPAan18Bn5+fL0lubWBqioiIqJrTmmvUnFf55+bMr+3JJ59UZGRk1SM5ObnBGgEAHdh5ieYPUTVl7remFgAAgA5qo6QxTqdObtqkigEDpMbC99oWLFDFgAE6uWmTMpxObWzqeXabtOtE4+F7eJCUnizNHiY9NUGaNcQM4IMCmlcnAKBN+XwA76vmzJmj/Pz8qsf+/QQpAIB6BAVII7q7j63bL5VXWFMPAABAB3Nc5sr30k2bVDF+vJRTT1/1xuTkqGL8eJVs2qRLnM7qdjTlFVJOYf3nDan77ntJZu/2sanS3SOkJy+SZpwrDeoqOYh7AKC98PkWNJWr0OtbbV5QUKDo6OhWX6PmvMo/N2d+bcHBwQoODm6wLgAAqozqIa3YW31cWCZtOSKdn2RZSQAAAB3F7S6XThYVqWLyZKmwgaC8KQoLVTF5sk7u2KE7ywK04L0d0rdHpYhg6eGx5uaotQ1JkN7bYf45LtQ8HpIgpUSZK+QBAO2Wz/9KtKF+6zk5OSosLKy3t3ulXr16yW6319uz3VOf+b59+6qwsFA5Hn7r3VBfegAAWiSxs9S3i/sYm7ECAAB43SpJb9jtqpg9u+Ur32vLyVHF7Nl6LTZMqwpKpdIK6dhp6dApz/Pjw6Vrz5J+P9oM6acOlHpGE74DgA/w+QA+IyNDkvTJJ5/UeW7ZsmVuc+rTqVMnDR8+XDt27NC+fe5hhmEYWr58ucLCwnT++ee36X0BAGiWUT3cj7NONPxWZQAAALTaXJdLjh07mt/zvTGvvirH9h16dkxK9djmBgL+cT2l7hGeV8gDANotnw/gL7roIvXq1UuvvfaaNm/eXDWen5+vJ554QkFBQbrpppuqxg8fPqzt27fXaR9z6623SjJ7sxuGUTX+4osv6ocfftCMGTPUqVOnqvGbb75ZDodDjz/+uNu1Nm/erNdff10DBw7UqFGj2vrlAgA6siEJ5uZaNa3NtqYWAACADuCIpHclOefO9cr1nc89q8VD4nWkc5Bkk3SyxCv3AQBYx2bUTJt91IoVKzRp0iSFhIRo2rRp6ty5sxYtWqR9+/bpmWee0b333ls1d9asWXrllVf08ssva9asWVXjLpdLl112mZYtW6YRI0YoIyNDu3bt0jvvvKPU1FRt2LBBcXFxbvd9/PHH9d///d9KSUnR1VdfrVOnTumNN95QWVmZPv30U6Wnpzf5NRQUFFT1lY+IiGj1xwQA4KcWfy8t/6H6uJNDevJic6NWAAAAtKl3JF0tSUlJ0uHDbX+DpCTp4EG98/0xTe0WYfaBBwC0e83Jcn1+BbwkjRs3TmvXrlV6errefPNN/eMf/1B8fLzeeOMNt/C9IXa7Xe+9954efvhhHTt2TH/961+VmZmpn//851q/fn2d8F2SHnjgAb366quKi4vTP/7xDy1cuFCjR4/WunXrmhW+AwDQZLXb0BQ7pa+98MMgAAAAtFGS49gx74TvknTokBy5udo4MI7wHQD8lF+sgPcHrIAHADTZ3A3S9tzq455R0n384hcAAKCtXS/p7ZUr5Ro3zmv3sK9cqWsyMvSm1+4AAGhrHW4FPAAAHcroWqvg9+RJBwosKQUAAMCflUpyFXp303tXUZFKvXoHAICVCOABAPA158ZLkbXeorxmnzW1AAAA+LFgSfbwcK/ewx4WJprPAID/IoAHAMDXBNilkcnVx72ipX4x1tUDAADgp/pIsg8a5NV72AcNUl+v3gEAYCWH1QUAAIAWSO8hFZZJo1Ok7uwdAgAA4A1pkpxxcVJionc2Yk1KkjM2Vmltf2UAQDvBCngAAHxRl07S9HMI3wEAALwoXZLd5ZKmTvXODaZOld3l0kjvXB0A0A4QwAMAAAAAAHgQL2mKJMedd3rl+o4779TUH+8DAPBPBPAAAAAAAAD1uNNul7N/f2nGjLa98I03ytmvn+6wE80AgD/jX3kAAAAAAIB6ZEia7nIpYN48KSGhbS6akKCAefN0g8uljLa5IgCgnSKABwDAXxiGtCNX+u6Y1ZUAAAD4lWftdkWHhSlgyRIpPLx1FwsPV8CSJYoODdVcVr8DgN9zWF0AAABopaIy6fMD0tps6UiRlNRZGhgr2WxWVwYAAOAXYiQtdTiUMXSoSj77TBWTJ0s5Oc2/UEKCApYsUcjQoVrmcCimzSsFALQ3/KoVAABft79AWvS9Gb5L0qFT0g8nra0JAADAz6RJWuVwKPrcwQr4frt0443Nu8CNNypgxw5FDx2q1Q6HzvNKlQCA9oYAHgAAX9cvRooLdR9bk21NLQAAAH4sTdL2hd/rup2npPnz5fh+uzR7tpSU5PmEpCRp9mw5duyQ5s/X9eHh2kH4DgAdis0wDMPqIiAVFBQoMjJS+fn5ioiIsLocAICvWb5bWry9+thhl564SAoPsq4mAAAAf3OyWHpwheQytKpvFz07JkWLhyTIFWCXIzdXrm3b5Coqkj0sTPZBg+SMjVWAy6Wpkm6329lwFQD8RHOyXHrAAwDgDy5Mlt7fKTld5rHTJW04IF3Uy9q6AAAA/MnqfZLLXMeYkXVCGfvydWRgnNaF2rUxNlZZGRkqlRQsqa/MFfMj7XbFW1gyAMBaBPAAAPiD8CBpaIL05aHqsTXZ0viebMYKAADQFsoqzE3va7qgm+JDAzVV0lRLigIAtHf0gAcAwF+MTnE/Plok7TxuTS0AAAD+ZuMhqajcfWxsqiWlAAB8BwE8AAD+one0lBjuPsZmrAAAAK1nGNLKve5jA2KlxM6WlAMA8B0E8AAA+AubTRrVw31sc45UUGpNPQAAAP5i90lpf4H72LhUS0oBAPgWAngAAPzJBd2lwBpf3l2GtG6/dfUAAAD4A5vMdxtWiguVBnW1rBwAgO8ggAcAwJ+EBkrnJ7mPZWabQTwAAABapncX6d6R0v2jpBHdzY3u7Wx0DwBoHAE8AAD+pvZmrMeLpe+PWVMLAACAP+kRKd00WMpItboSAICPIIAHAMDfpERKyRHuY2zGCgAAAADAGUcADwCAv/G0GevePKnUaUk5AAAAAAB0VA6rCwAAAF4wrJv0zvdS9wizJc3QBCkwwOqqAAAAAADoUAjgAQDwRyEO6ZFxUkSw1ZUAAAD4pgMF0qlSaUCs+Q5DAABagAAeAAB/RfgOAADQch9lSZtzpIRwaWyqNLybucgBAIBmoAc8AAAAAABATcdPS1tyzD/nFEpvfCut329tTQAAn0QADwAAAAAAUNPqfZJR4zg4QBrR3bJyAAC+iwAeAICOprzC6goAAADar7IKKbPWavcLk6VOgdbUAwDwaTQvAwCgI3AZ0s7j0pp90p486dFxkoPfwwMAANTxxUHpdLn7WEaKNbUAAHweATwAAP6uuFx6KlM6WlQ9tiVHSkuyriYAAID2yDCklXvdxwbFSfHhlpQDAPB9LH0DAMDfdQqUIoLdx9ZkW1MLAABAe7bzuHTolPvY2FRLSgEA+AcCeAAAOoLRPdyPdx6XjhRaUwsAAEB7VXv1e9cwaWCcJaUAAPwDATwAAB3BkAQpPMh9bC2r4AEAAKrknpa+OeI+NjZVstssKQcA4B8I4AEA6AgCA6QR3d3HPj8glVVYUw8AAEB7s3qfZNQ4DnHU/f4JAIBmIoAHAKCjGFWrDU1RubTpsDW1AAAAtCelTimz1rsDL+xuhvAAALQCATwAAB1F1zBpQKz7GJuxAgAASF8clIqd1cc2SRmpVlUDAPAjBPAAAHQktTdj/eGkdLDAmloAAADaA8Oou/nqoK7m4gUAAFqJAB4AgI7k3HgpIth9jM1YAQBAR3aiWCoscx8bm2pJKQAA/0MADwBARxJgl0Ymu49tOCiVOD3PBwAA8HcxodIfx0szB0s9IqX4MGlgbOPnAQDQBOwmAgBAR5OeLC3bJRk/Hpc4pY2HpPQeDZ4GAADgtwIDpAu6S8O7mRvV22xWVwQA8BOsgAcAoKOJCTX7mtbEZqwAAABm8B4eZHUVAAA/QgAPAEBHVHsz1ux8aV+eJaUAAAAAAOCvCOABAOiIBnWVokPMP4cHSRf3qrs5KwAAAAAAaBV6wAMA0BHZbdLk/uZ/hySYfU8BAAA6CsOQ8kqk6E5WVwIA8HME8AAAdFQXdLe6AgAAAGtsz5We+8JciDA2VerThY1XAQBeQQAPAAAAAAA6lhV7JUPSphzzcV6i9IvzrK4KAOCH6AEPAAAAAAA6jqNF0raj7mP9YqypBQDg9wjgAQAAAABAx7F6n7n6vVInh3RBN8vKAQD4NwJ4AABQLa9E+jhLKiyzuhIAAIC2V+KU1u13HxuZLAXToRcA4B18hQEAAOZGZKv3Sd8ckVyGFBQgXdTL6qoAAADa1oYDZghfySYpI9WqagAAHQAr4AEAgLkSbHOOGb5L0ppsyTAaPgcAAMCXuAxp5V73sXPipdhQS8oBAHQMBPAAAEAa1cP9+GiRtPO4NbUAAAB4w/Zc6UiR+9i4VEtKAQB0HATwAABA6ttFig9zH1ubbU0tAAAA3rBij/txYrjUL8aaWgAAHQYBPAAAkGw2aXSK+9jmHKmg1Jp6AAAA2tLRImnbMfexcT3N74EAAPAiAngAAGAa0V0KrPGtQYUhrd9vXT0AAABtpXbv99BAaViSJaUAADoWAngAAGAKDZTSav0guja7emNWAAAAX1RcLn1+wH1sZLIU7LCmHgBAh0IADwAAqo2utRnr8WJzwzIAAABf9fkBqcRZfWyTlJFS73QAANoSATwAAKiWGiV1j3AfW7PPklIAAABazTCkNbU2lj83XooJtaYeAECHQwAPAACq2WzSqFqr4LcelU4WW1MPAABAa9hs0u3DpYm9pbBAc2xcT2trAgB0KATwAADA3fBuUnBA9bHLkNaxGSsAAPBRXTpJUwZIj18k/Wyo1LeL1RUBADoQAngAAOAuxCEN6+Y+lrlfqnBZUw8AAEBbCAqQzk8yV8UDAHCGEMADAIC6am/GmlcibTtmTS0AAAAAAPgoAngAAFBXcqS5IWslm6TsfKuqAQAAAADAJzmsLgAAALRTo3tIuaelkcnmxqyxoVZXBAAAAACATyGABwAAng3rZj4cvGEOAAD4EJch/XW91C9GGpMiRYZYXREAoAMjgAcAAJ4RvAMAAF/03TFp90nzsWy3dF6idMM55kbzAACcYfxkDQAAAAAA/MfKvdV/dhnS4VNScIBl5QAAOjYCeAAAAAAA4B9yCs0V8DWNTZVsNkvKAQCAAB4AADRPhUsqcVpdBQAAQF2r9rofhwWae9oAAGARGqABAICmySuRMrOlzP1SWqJ09VlWVwQAAFCtuFz6/ID7WHoPKYj2MwAA6xDAAwCAxq3fLy3YavZRlcwfbif3lwL5gRYAALQT6w9IpRXVx3abNCbFunoAABAtaAAAQFP07lIdvktSUbn09WHr6gEAAKjJZbhvvipJg+OlLp0sKQcAgEoE8AAAoHFdw6T+Me5ja7OtqQUAAKC2bUel3NPuY+N6WlMLAAA1EMADAICmGV3rLdy7T0qHTllTCwAAQE0r9rofd4+QekdbUgoAADURwAMAgKYZHC9FBLuPrdlnTS0AAACVDp+Stue6j41LlWw2S8oBAKAmAngAANA0AXZpZLL72IaDUqnTmnoAAACkur3fw4Ok85MsKQUAgNoI4AEAQNOlJ0s1F5OVOKWNbMYKAAAscrrcXBBQU3qyFBhgTT0AANRCAA8AAJouJlQ6K859jDY0AADAKuv3S2UV1cd2mzQmpf75AACcYQTwAACgeWpvxrovX8rOt6YWAADQsaVESed0rX6H3pAEKbqTlRUBAODGYXUBAADAx5zdVYoOkU6WVI+t2SfNONe6mgAAQMfUp4v5OFYkrdonpSVaXREAAG5YAQ8AAJrHbpPSe7iPfXVIKi63ph4AAIC4MOmas6Se0VZXAgCAGwJ4AADQfCOTzSC+UmmF9OUh6+oBAAAAAKAdIoAHAADNFxVi9lutafU+yTCsqQcAAAAAgHaIAB4AALRM5WasNkmD4qTJ/S0tBwAAAACA9oZNWAEAQMsMiJWu7C+dnyTFhFpdDQAA6Ci++rHt3dAEKYB1hQCA9o0AHgAAtIzdJk3qY3UVAACgI3EZ0rvbpRPFZku80T3Md+WFB1ldGQAAHvGrYgAAAAAA4Bu+OWKG75KUVyK9v1M6WmRtTQAANIAAHgAAAAAA+IaVe92Pe0RKPaOsqAQAgCYhgAcAAAAAAO3fwQJp53H3sXGpks1mSTkAADQFATwAAGg7FS5pc470yW6rKwEAAP6m9ur3zkHSeYmWlAIAQFOxCSsAAGi9ojJpxV4pM1vKL5UCbNKF3aXOwVZXBgAA/EFhmfTFQfex0SlSYIA19QAA0ESsgAcAAG3jk91m+C5JFYa0/oC19QAAAP+xbr9U7qo+ttuk0T2sqwcAgCYigAcAAK0XFiSl1XoL+Jp9ksuwph4AAOA/KlzS6n3uY2mJUmSINfUAANAMBPAAAKBtjE5xPz5eLG3PtaYWAADgP745Ip0odh8bm2pJKQAANBcBPAAAaBs9o6Rund3H1uzzOBUAAKDJam++mhol9Yy2ohIAAJqNAB4AALQNm00aVasX69ajUl6JNfUAAADfd6BAyjrhPsbqdwCADyGABwAAbWd4Nyk4oPrYZZibpgEAALRE7dXvEcHSeYkepwIA0B4RwAMAgLbTKVA6P8l9bG22uXkaAABAcxSWSV8edB8b3UNyEGUAAHwHX7UAAEDbqr0Za16JtO2YNbUAAADflXtaigqpPg7w0O4OAIB2jgAeAAC0rR6R5qMmNmMFAADNlRolPTRW+tX50oBYKS1Jigxp7CwAANoVh9UFAAAAPzS6h7Rga/Xxd8ek46elmFDragIAAL7HbpPOiTcftLQDAPggVsADAIC2d36SFFLj9/yGpEw2YwUAAK0QQIQBAPA9fPUCAABtL9ghXdDNfWzdflauAQAAAAA6FAJ4AADgHbU3SXPYpWOnrakFAAAAAAAL0AMeAAB4R7cIqU8XsxXN6B7SoK5mH1cAAID6FJVJ+aVSUmerKwEAoE0QwAMAAO+56wL6tQIAgKZbky0t2SH1j5HG9ZTO5hf4AADfxk/EAADAewjfAQBAU1W4pNX7zD/vOC698JX0zvfW1gQAQCvxUzEAAAAAALDe5hwpr8R9bHg3z3MBAPARBPAAAAAAAMB6K/e6H/eKlnpEWlIKAABthQAeAACceSeLra4AAAC0J9n50u6T7mNjUy0pBQCAtuTzAXxBQYHuuecepaSkKDg4WKmpqbrvvvtUWFjY5GtkZWXpiSee0JgxY5SUlKSgoCAlJyfrpptu0vbt2z2eM2vWLNlstnofAACglgqX9PVhae4G6YHPpEOnrK4IAAC0F7VXv0cGS0MTLCkFAIC25LC6gNYoKipSRkaGNm/erIkTJ2r69OnatGmTnnnmGa1atUqrV69WSEhIo9d58MEH9eabb+rss8/WlVdeqYiICG3dulXz58/X22+/raVLl2rMmDEez73rrrsUFRXVxq8MAAA/YxjSU5nSgYLqsbXZ0nWDrKsJAAC0D6dKpa8OuY+NSWEzdwCAX/DpAP7pp5/W5s2b9bvf/U5/+tOfqsbvv/9+PfXUU/rrX/+qOXPmNHqdSy65RL/73e80dOhQt/E33nhD06dP169+9Stt27bN47l33323UlNTW/U6AADwezabNCjOPYDfcECaMkAKCrCuLgAAYL212ZLTVX3ssEujelhXDwAAbchnf51sGIZeeuklhYeH68EHH3R77sEHH1R4eLheeumlJl1r1qxZdcJ3SZo2bZr69eun7777Trm5uW1SNwAAHVZ6D6lml7Zip7TxUL3TAQBAB1Dhklbvcx87P0nqHGxNPQAAtDGfXQGflZWlQ4cOadKkSQoLC3N7LiwsTOnp6Vq2bJn279+v5OTkFt8nMDBQkuRweP5QffDBBzp16pSCg4M1cOBAXXTRRQoKCmr0uqWlpSotLa06LigoaGA2AAB+IDZUOitO2nasemxNtnRhy79OAwAAH7cpR8ovdR9j81UAgB/x6QBekvr27evx+b59+2rZsmXKyspqcQD/xRdfaNu2bRo2bFi9fd7vuOMOt+PExES9/PLLmjRpUoPXfvLJJ/XII4+0qC4AAHzWqB7uAfzePGl/vpQcaVlJAADAQiv2uB/3jpZ68H0BAMB/+GwLmvz8fElSZKTnL8wRERFu81py/ZkzZ8put+vpp5+u8/yYMWO0cOFCZWdnq7i4WFlZWXr00UeVl5enyZMn66uvvmrw+nPmzFF+fn7VY//+/S2qEwAAn3J2Vymq1gbpa7KtqQUAAFhrb560J899bFxPKyoBAMBrLF8Bf++997q1YmnMXXfdVe+q97ZSXFysqVOnavv27Xr88cc1duzYOnN+9rOfuR336dNHDz74oLp166af//znevTRR7VkyZJ67xEcHKzgYHraAQA6mAC7lJ4sfZhVPfblQemqgVKI5d+WAACAM2nlXvfjqBBpcLwlpQAA4C2W/6T74osvqqioqMnzr7nmGvXt27dq5Xt9K9wre6rXt0K+PiUlJbryyiu1YsUKzZkzR7///e+bdf7MmTM1e/ZsZWZmNus8AAA6jPQe0se7JJdhHpdWSF8clMakWFsXAAA4c8oqpK1H3MfGpJi/rAcAwI9Y/pWtsLBQhmE0+VG5Gr1yFXxlL/jaGusR70lxcbEmT56s5cuX67/+67/0xBNPNPv1BAQEKCoqqlm/VAAAoEOJCpHO6eo+tjZbMgxr6gEAAGdeUID0yDhpygApOkRy2M29YgAA8DOWr4Bvqb59+yopKUmZmZkqKipSWFhY1XNFRUXKzMxUz549m7wBa3Fxsa688kotX75cv/3tb/XUU0+1qK7s7Gzl5OSof//+LTofAIAOYVQPaUuNVW8HCsw+sD2jLSsJAACcYeFB0sTe0kU9ze8FwoOsrggAgDZn+Qr4lrLZbPrFL36hwsJCPfbYY27PPfbYYyosLNQtt9ziNn769Glt375d2dnum71Vtp1Zvny57rnnHv35z39u8N45OTk6ePBgnfG8vDzNmjVLknTDDTe04FUBANBBDIyTYjq5j7EZKwAAHVOAXUqJsroKAAC8wmYYvvt+76KiIqWnp2vLli2aOHGizjvvPH399df65JNPNGzYMK1atUqdOlX/cL9y5UqNGzdOGRkZWrlyZdX4rFmz9MorryghIUG33Xabx3vNmjVLqampVdeZMGGCRo4cqb59+youLk779+/X0qVLdfz4cY0fP14ffvihQkJCmvxaCgoKFBkZqfz8fEVERLTo4wEAgE9Ztkt6b0f1caBdevJiKTTQupoAAAAAAGhEc7Jcn21BI0lhYWFatWqVHn74YS1atEgrVqxQYmKi7r33Xj300ENu4XtD9u7dK8lc2f7II494nDN27NiqAL53796aNWuWvvzyS7377rvKz89XeHi4zj33XN1www36xS9+oYCAgLZ4iQAA+K8Lk6UPdkoVP64FKHdJnx+Qxve0ti4AAAAAANqIT6+A9yesgAcAdEgvfS19fdhsR5PeQ7qwuxTZ9HeQAQAAH+N0mRuuAgDgwzrMCngAAODjJvU2Q/eBcZLdZnU1AADAm/JLpD+uloZ1kzJSpPhwqysCAMDrCOABAIB1kiOtrgAAAJwpa7OlonJp5V7zMSRBuuU8ycYv4QEA/ov3fQEAAAAAAO9yuqQ12e5joYGE7wAAv0cADwAAAAAAvOvrw1JBqfvY2FRLSgEA4EwigAcAAAAAAN61cq/7cd8uUveGN60DAMAfEMADAID25UihtOg7aedxqysBAABtYc9JaW+e+xir3wEAHQSbsAIAgPbh+2PSJ7ulHT8G7yeKpX4x1tYEAABar/bq9y6dpHPjLSkFAIAzjRXwAACgfThaVB2+S9KWI1JeiXX1AACA1ssrkTYedh8bkyIFEEcAADoGvuIBAID2YXg3KSig+thlSOv3W1cPAABovbXZ5tf0SoF2KT3ZunoAADjDCOABAED70ClQGpbkPlb7h3YAAOA7yiukNfvcx4Z3k8KCrKkHAAALEMADAID2Y1QP9+OTJdK2o9bUAgAAWufrw9KpMvcxNl8FAHQwBPAAAKD9SImSekS6j63JtqQUAADQCoYhrdjrPtYvRuoWYUk5AABYhQAeAAC0L6NrrYLfdlQ6ftqaWgAAQMvsyZOy893HWP0OAOiACOABAED7kpYkhTiqjw1J69iMFQAAn7Jyr/txl07SufGWlAIAgJUI4AEAQPsS4jA3aKspc79U4bKmHgAA0HwX9TS/ngfYzOOMFMlus7YmAAAsQAAPAADan9qbsRaUSt8csaYWAADQfClR0qwh0h/HS1f0k9J7NHYGAAB+iQAeAAC0P90jpF7R7mNsxgoAgO+JDJEu6yuFBlpdCQAAliCABwAA7VPtVfDbc6WjRdbUAgAAAABACxDAAwCA9um8xLqr5dayCh4AAAAA4DsI4AEAQPsUFCCN6F59HGCTyiqsqwcAAAAAgGZyWF0AAABAvUb3MDdfHdVDurC71DnY6ooAAEB93t0uxXSShneTgokbAACQCOABAEB7Fh8uPTJWstmsrgQAADTkZLH0fz9ILsMM4tN7SBN7S+FBVlcGAIClaEEDAADaN8J3AADav9X7zPBdkoqd0pp9kp2v4QAAEMADAAAAAICWK6uou1H6Bd3rbqYOAEAHRAAPAAAAAABabuMhqajcfSwjxZpaAABoZwjgAQCA7ymrkI4VWV0FAAAwDGnFXvexgbFSYmdLygEAoL1hE1YAAOA7cgrNt7h/fkDqGib9V7rVFQEA0LHtPikdKHAfG5tqSSkAALRHBPAAAMA37Dwu/e3z6uO9edL+fCk50rKSAADo8FbscT+OC5UGdbWmFgAA2iFa0AAAAN/QO1qKDHYfq73hGwAAOHNOFEtbjriPZaRKdpsl5QAA0B4RwAMAAN8QYJfSe7iPfXFQKnFaUw8AAB3d6n2Sy6g+Dg6QLuxuXT0AALRDBPAAAMB3pCdLNRfVlVZIXx60rBwAADqssgops9Y70UZ0lzoFWlMPAADtFAE8AADwHdGdpHPi3cfWZkuG4Xk+AADwji8PSkXl7mNsvgoAQB0E8AAAwLeMrtWGZn+BtC/fmloAAOiIDENaudd97Kw4KT7cknIAAGjPCOABAIBvGRgnxXRyH1uzz5paAADoiLJOSAdPuY+NS7WkFAAA2jsCeAAA4FvstrqbsX51SDpd7nk+AABoW4YhJUdUH3cNM39BDgAA6iCABwAAvufC7mYQX6ncJW04YF09AAB0JP1jpftHSfdeKJ2XaK5+r/l1GQAAVHFYXQAAAECzRYZIQxKkrw9Xj63NNjd/sxEAAADgdTab1LuL+QAAAPViBTwAAPBNtTdjPVwo7T5pTS0AAAAAAHhAAA8AAHxTvxiz52xNbMYKAAAAAGhHCOABAIBvstnqroLflCMVlllTDwAAAAAAtRDAAwAA33VBd8lhNx/DkqQ7L5DCAq2uCgAA/3OgQNp1QjIMqysBAMCnsAkrAADwXeFB0i3nSalRUudgq6sBAMB/fbBT+uaIlBwhjesppSVKgQFWVwUAQLtHAA8AAHzbOfFWVwAAgH/LPS1tPWL+eX+B9L9bpLIKaUyKtXUBAOADaEEDAAAAAADqt2qvVLPzTIhDGt7NqmoAAPApBPAAAAAAAMCzEqe0br/72MhkM4QHAACNIoAHAAAAAACefXFQKnZWH9tE6xkAAJqBAB4AAPiXsgpp/X7pxa8kl9H4fAAA4JlhSCv3uo8N6ip1DbOkHAAAfBHvGQMAAP7B6ZIWfy99fqB6pd53x6Szu1pbFwAAvmrHcSmn0H1sXKolpQAA4KtYAQ8AAPyDwy7tOuH+Nvk1+6yrBwAAX7dij/txQrg0INaaWgAA8FEE8AAAwH+MrtWT9tuj0olia2oBAMCXHSsyv47WNDZVstksKQcAAF9FAA8AAPzH+UlSSI0Oe4akzGzLygEAwGet2md+Ha3UySEN72ZZOQAA+CoCeAAA4D9CHNKwJPexdfulCpc19QAA4ItKnObXz5pGJrv/khsAADQJATwAAPAvtdvQ5JdKW496ngsAAOracMAM4SvZJGWkWlUNAAA+jQAeAAD4l+4RUs8o9zE2YwUAoGlchrRyr/vYOfFSbKgl5QAA4OsI4AEAgP+pvQr++1xzMzkAANCw3NNSQan72NhUS0oBAMAfEMADAAD/c16iFBroPraWzVgBAGhU1zDpiYukG86REsPNR/8Yq6sCAMBnsYMKAADwP0EB0oju0md7qsfWH5Cu6CcFBlhXFwAAviDYIY3qIaUnm6vhbTarKwIAwGexAh4AAPinUT3cjwvLpC1HrKkFAABfZLNJkSFWVwEAgE8jgAcAAP4pIVzq28V9jM1YAQAAAABnEAE8AADwX7U3Y806IR0+ZU0tAAAAAIAOhwAeAAD4r8HxUnhQ9XFiuNmKBgAAVHMZZq93AADQ5tiEFQAA+K/AAGlMipR72uwJ3zuajeQAAKhte670jy+ltCRpbKqUGmV1RQAA+A0CeAAA4N+u6Gd1BQAAtG8r9kgVhvTFQfMxort002CrqwIAwC/QggYAAAAAgI7qaJG07Zj7WK9oa2oBAMAPEcADAAAAANBRrdzrfhwaKA1LsqQUAAD8EQE8AAAAAAAdUXG59PkB97GRyVIw3WoBAGgrBPAAAKBjys6XSpxWVwEAgHU+P+D+tdAmKSPFsnIAAPBH/FobAAB0HKVO6atD0ppsM4C/4RxpVA+rqwIA4MxzGdKqfe5j58ZLMaHW1AMAgJ8igAcAAB3H/G+krw9XH6/ZJ6UnSzabdTUBAGCF74+ZG7DWNK6nNbUAAODHaEEDAAA6jhHd3Y/3F0j78q2pBQAAK63Y636c1Fnq28WSUgAA8GcE8AAAoOM4K07q0sl9bM0+z3MBAPBXRwql7465j41L5R1hAAB4AQE8AADoOOw2s+VMTV8dkk6XW1MPAABWWLnX/TgsUBrWzZJSAADwdwTwAACgYxmZbAbxlcpd0oYD1tUDAMCZVFwufV7r6156DykowJp6AADwcwTwAACgY4kMkQbHu4+tzZYMw5p6AAA4kz4/IJVWVB/bJI1JsawcAAD8HQE8AADoeEbXChoOF0q7T1pTCwAAZ4phSKtq7X0yJKHu/igAAKDNEMADAICOp1+MFBfqPsZmrAAAf2ezSb86XxqbKgX/2HJmbKqVFQEA4PcI4AEAQMdjt0mjeriPbcqRCsusqQcAgDMlPly6bpD0xEXSTYOlPl2srggAAL9GAA8AADqmC5MlR41vhZyuupvSAQDgrzoFSiO6m6viAQCA1xDAAwCAjik8SBqa4D62NltysRkrAAAAAKBtEMADAICOq/ZmrEeLpJ3HrakFAAAAAOB3COABAEDH1TtaSgx3H1u/35paAAAAAAB+hwAeAAB0XLYam7EmdZamnW0+AADwFy5D+ut66ZPdbDYOAIAFHFYXAAAAYKkLukspUVLPKDaiAwD4n2+PSlknzMeHO6Xh3aRrB0lBAVZXBgBAh0AADwAAOrbQQKlXtNVVAADgHSv3Vv+53CVl50uBvBkeAIAzha+6AAAAAAD4o8OnpO257mNjU3nHFwAAZxABPAAAAAAA/qjm6ndJCg+Szk+ypBQAADoqAngAAAAAAPzN6XJpw0H3sVE9pEB6vwMAcCbRAx4AAKAmw5D25Utrs6WuYdLE3lZXBABA863bL5VVVB/bbdKYFOvqAQCggyKABwAAqLTrhPTWNml/gXkcGSxd1FMK4E2DAAAf4jKkVXvdx4YmSFEhlpQDAEBHxk+TAAAAlUIc1eG7JOWXSluPWlcPAAAtsfWIdLzYfWxsqiWlAADQ0RHAAwAAVOoeIaVGuY+tzbakFAAAWqz25qs9IqVe0ZaUAgBAR0cADwAAUNPoHu7H3x+Tck9bUwsAAM116JS047j72NhUyWazpBwAADo6AngAAICa0pKkTjW2yTHEKngAgO+ovfq9c5CUlmhJKQAAgAAeAADAXVCANKK7+9j6/ZLTZU09AAA0VVGZtOGA+9ioHlJggDX1AAAAAngAAIA6RtVqQ3OqTNqSY00tAAA01br9UnmNXxjbbdLoFOvqAQAABPAAAAB1JHaW+nRxH1tDGxoAQDuXHCn1j6k+Pi9Rigqxrh4AACBH41MAAAA6oNE9pF0nqo93HpdyCqWEcOtqAgCgIQNizcehU2Yv+Au7N3oKAADwLlbAAwAAeDIkQQoPch9jM1YAgC9I6izdcI7UM9rqSgAA6PAI4AEAADwJDKi7cnDDAamswpp6AAAAAAA+hwAeAACgPum1NmMtKpc2HbamFgAAAACAzyGABwAAqE/XMLOXbk1sxgoAAAAAaCICeAAAgIaMrrEKPjjA7Ktb4bKuHgAAavr6sLT1iOQyrK4EAAB44LC6AAAAgHbt3HjprDhpcLw0rJsUwrdPAIB2osIlLfpOOlkixYVKGanm/iWdAq2uDAAA/IifIAEAABoSYJduH251FQAA1PXNETN8l6Rjp6W3v5N6RUupUZaWBQAAqtGCBgAAAAAAX7Rir/txahThOwAA7QwBPAAAAAAAvmZ/vrTrhPvYuFRLSgEAAPUjgAcAAAAAwNes3Ot+HBEsDU20pBQAAFA/AngAAICWOF0ubc+1ugoAQEdUWCZ9ech9bEyK5OBHfAAA2hs2YQUAAGgqw5D25klrsqWNhySbTXryIqlToNWVAQA6krXZktNVfRxgk0b1sK4eAABQLwJ4AACApiosk/6yXnIZ1WNfHJQyUi0rCQDQwVS4pNX73MfSkswWNAAAoN3x+fenFRQU6J577lFKSoqCg4OVmpqq++67T4WFhc26js1mq/cxa9Ysr94bAAD4iM7B0uB497E12ebKeAAAzoQtR6S8EvexsamWlAIAABrn0yvgi4qKlJGRoc2bN2vixImaPn26Nm3apGeeeUarVq3S6tWrFRIS0uTrpaSkeAzbhwwZ4vV7AwAAHzGqh7Qpp/r40Cnph5NS7y7W1QQA6DhW7HE/7hklpUZZUQkAAGgCnw7gn376aW3evFm/+93v9Kc//alq/P7779dTTz2lv/71r5ozZ06Tr5eamqqHH37YknsDAAAf0T9WiguVjp2uHluTTQAPAPC+7Hxp90n3sXE9rakFAAA0ic0wfPM904ZhqHv37iooKFBOTo7CwsKqnisqKlJCQoK6du2q3bt3N+l6NptNGRkZWrly5Rm/t2S2s4mMjFR+fr4iIiKafB4AALDA8t3S4u3Vxw679MRFUniQdTUBAPzf/26RPj9QfRwZLP1xvBTg891lAQDwKc3Jcn32q3RWVpYOHTqk9PR0twBcksLCwpSenq4ffvhB+/fvb/I18/Ly9M9//lNPPPGEXnjhBW3duvWM3RsAAPiQEd3N0L2S0yVtOFD/fAAAWutUqfTVIfexMSmE7wAAtHM++5U6KytLktS3b1+Pz1eOV85rii1btui2227TAw88oF/96lc699xzdemll+ro0aNtfu/S0lIVFBS4PQAAgI/oHCwNSXAfYzNWAIA3HS1yf6eVw27uSwIAANo1nw3g8/PzJUmRkZEen69c+l85rzH33nuv1q1bp9zcXBUUFGjdunW69NJLtXTpUl1xxRWqqKho03s/+eSTioyMrHokJyc3qU4AANBOjK4VehwtknYet6YWAID/691Femyc9POhUu9o6fwk8xfCAACgXbN8E9Z7771XpaWlTZ5/11131bvyvDWeeeYZt+MLL7xQH3zwgcaPH69Vq1bpvffe01VXXdVm95szZ47uueeequOCggJCeAAAfEmfLlJCuJRTWD22JtvcpBUAAG8IsEtpSeajvKLx+QAAwHKWB/AvvviiioqKmjz/mmuuUd++fatWn9e3yryypUt9q9Sbwm6365ZbbtGqVauUmZlZFcC3xb2Dg4MVHMxqBQAAfJbNZr71/+3vqsc250gFpVIEX+MBAF4WGGB1BQAAoAksb0FTWFgowzCa/Bg7dqykxvusN9anvaliY81VbDV/SXCm7g0AANq5Ed2lwBrfTrkMaR2bsAMAAAAATJYH8C3Vt29fJSUlKTMzs84K+qKiImVmZqpnz56tbuuyYcMGSVJqauoZvzcAAGjnQgPNNgA1ZWabQTwAAAAAoMPz2QDeZrPpF7/4hQoLC/XYY4+5PffYY4+psLBQt9xyi9v46dOntX37dmVnZ7uNb926VeXl5XXusW7dOj311FMKDAzUtdde26p7AwAAP1V7M9bjxdIPJ62pBQDgX4rKzE2+AQCAz7IZhuGzS7SKioqUnp6uLVu2aOLEiTrvvPP09ddf65NPPtGwYcO0atUqderUqWr+ypUrNW7cOGVkZGjlypVV47NmzdKHH36oUaNGKTk5WYGBgdq2bZs++eQT2Ww2zZs3T7/85S9bde/GFBQUKDIyUvn5+YqIiGj1xwYAAJwhhiE9uVbKPS0NS5JGp0jd+VoOAGgDH2dJH+yUBnWVxqVKA2LNPUgAAIClmpPlWr4Ja2uEhYVp1apVevjhh7Vo0SKtWLFCiYmJuvfee/XQQw81OQC/8sorlZeXpy1btmj58uUqKytTQkKCpk2bprvvvlvDhw/32r0BAICPs9mkm4dI0Z2kEJ/+1goA0J5UuKTV+yRD0rdHzcfE3tKUAVZXBgAAmsGnV8D7E1bAAwAAAACqfHVI+vcm97H7R0k9Iq2pBwAAVGlOluuzPeABAAAAAPBbK/a4H/eOJnwHAMAHtTiALysr044dO+R0OtuyHgAAAAAAOra9edKePPexcT2tqAQAALRSswP406dP6+c//7lCQ0M1aNAgZWdnS5LuuOMO/elPf2rzAgEAAHwWnf4AAC2xcq/7cVSINDjeklIAAEDrNDuAnzNnjrZs2aKVK1cqJCSkavziiy/Wm2++2abFAQAA+KSiMumzPdIfV0u5p62uBgDgS/JLpI2H3MfGpEgBdJAFAMAXOZp7wrvvvqs333xTI0aMkM1mqxofNGiQdu/e3abFAQAA+JyF26TMbKncZR5nZktXDrC2JgCA78jcL1XUeAeVwy6N6mFdPQAAoFWa/Sv0Y8eOqWvXrnXGi4qK3AJ5AACADqsyfJekdfslp6v+uQAAVHK6pNX73MeGJUnhQdbUAwAAWq3ZAfz555+vDz/8sOq4MnR/6aWXdOGFF7ZdZQAAAL5odK1ViqfKpC051tQCAPAtmw5LBaXuY2NTLSkFAAC0jWa3oHniiSd06aWX6rvvvpPT6dTf//53fffdd1q3bp1WrVrljRoBAAB8R2JnqU8XadeJ6rG12VJaknU1AQB8w4q97sd9ukjJkZaUAgAA2kazV8CPGjVKmzdvltPp1DnnnKNPPvlEXbt21fr165WWluaNGgEAAHxL7VXwO45LRwqtqQUA4Bv2nJT25rmPjUu1ohIAANCGmr0CXpJ69+6tf/3rX21dCwAAgH8YkmD26y0sqx5bmy1dfZZ1NQEA2reVe92Po0Okc+MtKQUAALSdZq+A/+ijj7Rs2bI648uWLdPHH3/cJkUBAAD4tMAAaUR397HPD0jlFdbUAwBo30qc0jdH3McyUqWAZv/IDgAA2plmfzW///77VVFR94dHwzB0//33t0lRAAAAPm9UrTY0ReXS14etqQUA0L6FOKSHx0qX9ZU6B0mBdmlkstVVAQCANtDsFjRZWVk666y6b58eMGCAdu3a1SZFAQAA+LyuYdKAWGl7bvXY2mzpgu71nwMA6LgiQ6Qr+kmTekv7C8xWZgAAwOc1ewV8ZGSkfvjhhzrju3btUlhYWJsUBQAA4Bdqb8a6+6R06JQ1tQAAfENggNQr2uoqAABAG2l2AH/llVfq7rvv1u7du6vGdu3apXvvvVeTJ09u0+IAAAB82rnxUkSw+9iafdbUAgAAAAA445odwD/99NMKCwvTgAED1LNnT/Xs2VMDBw5UTEyMnnnm/7N35/FR1ff+x9+TPSQkLAkkkJUdEUQRREJIkFtRb69Lq7VSrVj3ut2rvW21Wqy1xdr+2mo3uXpbl7q2tlytWrTKElZFQBHZIQskBAiQnWxzfn+MWU72SWbyneX1fDzm8eB85syZdyx8e+Yz33y/v/BGRgAAAP8U2skavpsOS3WNZvIAAAAAAAaU22vAx8fHa/369Xrvvff0ySefKDo6WtOmTdO8efO8kQ8AAMC/ZaVKK/ZJ1hfHpxulzcVSVlq3LwMABIEmp+vLWgAAELDcbsBLksPh0IUXXqgLL7zQ03kAAAACy/BB0pQR0mdHXcdjh0pDosxmAgCYd+q09NhaaXaKNC9dGhZtOhEAAPCCPjXg33//fb3//vs6evSonE6n7bk//vGPHgkGAAAQMHIzpOHRUna6NGqw6TQAAF+QVyBV1Env7pfe2y/NHC1df5bkcJhOBgAAPMjtBvyPfvQjPfLIIzr33HOVnJwsBzcHAAAA3Tsj0fUAAECSGpqkvMLWY0tSRCjNdwAAApDbDfinnnpKzz77rK677jpv5AEAAAAAILB9XCJV1dtruRlGogAAAO9ye7eX+vp6zZkzxxtZAAAAAAAIbJYlrcq31yYOZ4kyAAAClNsN+JtuukkvvfSSN7IAAAAAABDYDpyUCsvtNWa/AwAQsNxegub06dP6n//5H/3rX//StGnTFB4ebnv+l7/8pcfCAQAABCzLkvaUSXGRUjKzHgEgaLSf/T48Wpo60kgUAADgfW434D/99FNNnz5dkvTZZ5/ZnmNDVgAAgB5U1UsbD0lrC6Wj1dJ5o6Xrp5tOBQAYCCdrpa1H7LWcDCmEz9IAAAQqtxvwK1eu9EYOAACA4LC+SFq+q/X44xLpyjOkmAhzmQAAAyOvUHJarccRodKcVHN5AACA17m9Bnyzffv2acWKFaqtrZUkWZbVwysAAACg81Ok0DYzHRud0qbD5vIAAAZGQ5Prt5/aOm+0NCi88/MBAEBAcLsBX1ZWpgULFmjChAm65JJLVFJSIkm68cYbdd9993k8IAAAQEAZHCmdnWyv5RW41oQHAASuzcWuZcjaYvNVAAACntsN+P/6r/9SeHi4CgsLNWjQoJb61VdfrX/+858eDQcAABCQ5qbZj0urpb0nzGQBAHifZXXcfHVSAptwAwAQBNxeA/7dd9/VihUrlJKSYquPHz9eBQUFHgsGAAAQsMYPk0bGuBrvzfIKpAnDzWUCAHjP/pNSUYW9xux3AACCgtsz4Kurq20z35udOHFCkZGRHgkFAAAQ0BwOKTvdXtt2RKqsM5MHAOBd7We/JwySzhxhJAoAABhYbjfgs7Oz9fzzz7ccOxwOOZ1OPf7445o/f75HwwEAAASs2SlSeJtbsSZL2nDIXB4AgPfkZkhnJ0nNe3DnpEshju5eAQAAAoTbS9A8/vjjWrBggTZv3qz6+np997vf1Y4dO3TixAmtW7fOGxkBAAACz6BwacYoaWObpntegfRvY2jKAECgGTfM9ThR6xrrz081nQgAAAwQt2fAn3nmmdqzZ4/mzp2ryy67TNXV1frKV76irVu3auzYsd7ICAAAEJiy223GWlYr7TpuJgsAwPuGRUuXTXJ9CQsAAIKC2zPgJSk+Pl4/+MEPPJ0FAAAguGQMkVLipENtNubLK5DOSDQWCQAAAADgOb1qwH/66ae9vuC0adP6HAYAACCoOBzS3DTplc9aa9uPSqdOS0OizOUCAAAAAHhErxrw06dPl8PhkGVZcjha1yS1LEuSbLWmpiYPRwQAAAhgM0dJf98p1X1xD+W0pPVF0iXjzeYCAAAAAPRbr9aAP3jwoA4cOKCDBw/q9ddfV2Zmpn7/+99r27Zt2rZtm37/+99r7Nixev31172dFwAAILBEh0szR9tr246YyQIA8Jw3dkubDkkNTFIDACCY9WoGfHp6esufr7rqKj355JO65JJLWmrTpk1TamqqHnroIV1++eUeDwkAABDQ5qZJawulccNcG7NOTzKdCADQHydqpRX7JEvS33e5xvkLMtl8FQCAIOT2Jqzbt29XZmZmh3pmZqY+//xzj4QCAAAIKmnx0sO50ogY00kAAJ6wpsDVfJekijrp/QPSgo6fowEAQODr1RI0bU2ePFlLly5VfX19S62+vl5Lly7V5MmTPRoOAAAgaNB8B4DAUN8krSu012anuJYcAwAAQcftGfBPPfWU/uM//kMpKSmaNm2aJOnTTz+Vw+HQm2++6fGAAAAAAAD4jY8OS9UN9lpuhpEoAADAPLcb8LNmzdKBAwf04osvateuXZKkq6++WosWLVJMDDO3AAAAAABByrKklfn22hmJ0shYI3EAAIB5bjfgJSkmJka33HKLp7MAAACgPaclhThMpwAA9MbeE1Jxpb02P8NIFAAA4Bt61YB/4403dPHFFys8PFxvvPFGt+deeumlHgkGAAAQtJyWtPu4lFfoWkv4zlmmEwEAemPlQfvxiBhpcqKZLAAAwCf0qgF/+eWX68iRIxoxYoQuv/zyLs9zOBxqamryVDYAAIDgU1IpPbVZOlbTWiutYvkCAPB1ZTXSp6X2Wk46v8UEAECQC+nNSU6nUyNGjGj5c1cPmu8AAAD9lDBIqmm3ed/aQjNZAAC9t7pAstocR4VJs1OMxQEAAL6hVw34toqKiryRAwAAAJIUHtqxYbPxkNTARAcA8Fl1jdK6dl+Wzk6RosPN5AEAAD7D7QZ8RkaGcnJy9PTTT+vkyZPeyAQAABDc5qbZj6sbpK1HzGQBAPTso2KpttFey80wEgUAAPgWtxvwmzdv1qxZs/TII48oOTlZl19+uf7617+qrq7OG/kAAACCz8hYaeJwey2vwEwWAED3LKvj5qtTEl0bsAIAgKDndgP+7LPP1s9//nMVFhbqnXfeUWJiom655RaNHDlS3/rWt7yREQAAIPhkp9uP95+UiivNZAEAdG1PmVRSZa/NzzSTBQAA+By3G/DNHA6H5s+fr6efflr/+te/lJmZqeeee86T2QAAAILXtJFSXKS9xix4APA9jU5pZJvZ7iNjpEkJ5vIAAACf0ucG/KFDh/T4449r+vTpmjVrlmJjY/W73/3Ok9kAAACCV1iIdH67zVg/POza6A8A4DumjJAeypHunCWdOcI1+z3EYToVAADwEWHuvmDZsmV66aWXtG7dOk2aNEnf+MY39H//939KT0/v+cUAAADovblp0rv7JeuL49pG6eMSaU6q0VgAgHZCHNIZia6HZfV8PgAACBpuN+AfffRRXXPNNXryySd11llneSMTAAAAJGn4IFczZ8ex1lpeAQ14APBlDma/AwCAVm434AsLC+XghgIAAGBgZKfbG/AF5VJhuZQWby4TAAAAAKBXer0G/OOPP67a2tqW5vu6detUV1fX8nxlZaW+/e1vez4hAABAMJuSKA2JstfWFprJAgAAAABwS68b8Pfff78qKytbji+++GIdPny45bimpkbLli3zbDoAAIBgFxoiZbVbcuajw1Jtg5k8AADpcIXrt5EAAAB60OslaKx2G8m0PwYAAICXZKVJ7+yTnJYUG+FaA97JvRgAGPPmHunTUmnsUCk3Q5qe5PrCFAAAoB2314AHAADAABsSJV00TkqKlc4aKYWHmk4EAMHreI20vdT15/0nXY9FU6W5aWZzAQAAn0QDHgAAwB98eYLpBAAASVqdL7X9JaSoMOncUabSAAAAH+dWA/6ZZ55RbGysJKmxsVHPPvusEhISJMm2PjwAAAAAAAHndKO0vshem5PqasIDAAB0wmH1cjH3jIwMORyOHs87ePBgv0MFo4qKCsXHx6u8vFxxcXGm4wAAAAAA2ltTIL3yWeuxQ9LDuVJijKlEAADAAHd6ub3+mj4/P7+/uQAAAAAA8E+WJa1sN+HszBE03wEAQLfYph0AAMBfnTotfXDQ1RQCAHjXruNSabW9Nj/TTBYAAOA3WKgOAADAn1iWtPO4lFcgbT8qOS0pJU6aMNx0MgAIbCvz7cdJsdJExl4AANA9ZsADAAD4m9d2SJ+UuprvkrS20GweAAh0R6ulHUfttdwMqRf7pAEAgOBGAx4AAMCfOBxSdpq9trVEqqwzkwcAgsGaAqntal/RYdJ5o43FAQAA/qNXDfh7771X1dWute7WrFmjxsZGr4YCAABAN2anSGFtbuOaLGnDIXN5ACCQnW6U1hfZa3NSpUhWdAUAAD3rVQP+N7/5jaqqqiRJ8+fP14kTJ7waCgAAAN2IiZBmJNtrawtbl6QBAHjOpkOuJnwzh6ScDFNpAACAn+nVV/YZGRl68skndeGFF8qyLG3YsEFDhw7t9Nx58+Z5NCAAAAA6MTdN2nS49fh4jbT7uDQ50VwmAAg0TktalW+vTR0pJQwyEgcAAPifXjXgf/7zn+u2227T0qVL5XA4dMUVV3R6nsPhUFNTk0cDAgAAoBNjhkqjBkvFla21vEIa8ADgSUerpVOn7bX5GUaiAAAA/9SrJWguv/xyHTlyRBUVFbIsS7t379bJkyc7PFiaBgAAYIB0thnrp6UdG0UAgL5LipV+ukC68gzXrPfkWGnCcNOpAACAH3Fr15jY2FitXLlSmZmZCgtjwxkAAACjZo2Wlu+S6r74DUSnJW0oki4ebzYXAASS6HDpgkwpN8P1JafDYToRAADwI2530XNyctTU1KTXX39dO3fulCSdccYZuuyyyxQaGurxgAAAAOhCdLh07ihpXVFrbW2htHCcFEKDCAA8KsQhDYs2nQIAAPgZtxvw+/bt07//+7/r0KFDmjhxoiRp6dKlSk1N1VtvvaWxY8d6PCQAAAC6kJ1ub8CfPC3tOOraJBAAAAAAYFSv1oBv6+6779aYMWNUVFSkLVu2aMuWLSosLFRmZqbuvvtub2QEAABAV9LiXY+28grNZAEAAAAA2Lg9A3716tXauHGjhg0b1lIbPny4HnvsMWVlZXk0HAAAAHohO016cXvr8Y6jUlmNNHyQuUwA4K+clnS6URoUbjoJAAAIAG7PgI+MjFRlZWWHelVVlSIiIjwSCgAAAG44d5QU1W5exZ4yM1kAwN/tPCbd/y/ppe1SccfPvgAAAO5wuwH/5S9/Wbfccos2bdoky7JkWZY2btyo2267TZdeeqk3MgIAAKA7kWHSeaOlwRHSwrHSj+ZL56eaTgUA/mllvtTgdG1q/ega6ZXPTCcCAAB+zO0laJ588kldf/31Ov/88xUe7vqVvMbGRl166aV64oknPB4QAAAAvfAfE6WvniGFuT2/AgDQrLRK+vyYvZYaZyYLAAAICG434IcMGaL/+7//0759+7Rz505J0uTJkzVu3DiPhwMAAEAvsVYxAPTfqnz7cUy4NHO0kSgAACAwuN2AbzZu3Dia7gAAAACAwFDbIG08ZK9lpUkRoWbyAACAgMDvKAMAAAAAsOGQVNfUehzikOalm8sDAAACAg14AACAQNbkdD0AAF1zWtLqfHvtrJHSsGgjcQAAQOCgAQ8AABCITtZK/9gjPfiBtKXEdBoA8G07jkrHauy1+ZlmsgAAgIDidgO+sLBQlmV1qFuWpcLCQo+EAgAAQD80N97f3iuV10l53KMBQLfab76aEieNHWokCgAACCxuN+AzMzN17NixDvUTJ04oM5MZAgAAAMYlx0pt50vsOyGVVBqLAwA+raRS2nncXsvNkBwOI3EAAEBgcbsBb1mWHJ3ciFRVVSkqKsojoQAAANAPZyVJgyPsNWbBA0DnVhfYj2PCpXNHmckCAAACTlhvT7z33nslSQ6HQw899JAGDRrU8lxTU5M2bdqk6dOnezwgAAAA3BQWIs1JlVbsb61tOiRdPkmKCDWXCwB8TU2Da3xsa24aYyUAAPCYXjfgt27dKsk1A3779u2KiGidVRUREaGzzjpL3/nOdzyfEAAAAO7LSpPe3d+6FE1to/RxsXR+qtFYAOBTNhRJdU2txyEOKTvdXB4AABBwet2AX7lypSTphhtu0BNPPKG4uDivhQIAAEA/JQySJidKn7fZuyevkAY8ADRzWh2Xn5meJA2LNpMHAAAEJLfXgP/Tn/5E8x0AAMAfZKfZj/NPSUXlRqIAgM8JcUi3zJCyUqXwLz4a52YYjQQAAAJPr2fAN6uurtZjjz2m999/X0ePHpXT6bQ9f+DAAY+FAwAAQD+cOUIaEiWdOt1ayyuUFk01lwkAfElKnPSNadJlk6RtR6SxQ00nAgAAAcbtBvxNN92k1atX67rrrlNycrIcDoc3cgEAAKC/Qr/YjPXtva21jw5LX5ksRbl9GwgAgSs2wrX5KgAAgIe5/cnrnXfe0VtvvaWsrCxv5AEAAIAnZaVK7+xt3Yy1rsnVhGeTQQAAAADwOrfXgB86dKiGDRvmjSwAAADwtKHR0tSR9lpeoWRZnZ8PAAAAAPAYtxvwP/7xj/XDH/5QNTU13sgDAAAAT2u/GeuhCteGrAAAAAAAr+rVEjRnn322ba33ffv2aeTIkcrIyFB4eLjt3C1btng2IQAAAPpncqI0PFoqq22t5RVKmWw2CCDIOC3ptx9KU0dIs1Ok6PCeXwMAANAPvWrAX3755V6OAQAAAK8JcUhZadIbuyWHpCkjpBnJplMBwMD7tFTaddz1eHOPqwl/xSQpPNR0MgAAEKB61YBfsmSJt3MAAADAm+akSvVNrk1Zhw8ynQYAzFiV3/rn043SgZNSmNsrswIAAPRarxrwAAAA8HNxkdKlE02nAABzDldIe8rstfkZUpvlVgEAADzN7Qb80KFDbevBN3M4HIqKitK4ceO0ePFi3XDDDR4JCAAAAABAv7Wd/S5JgyOkc1iOCwAAeJfbDfgf/vCH+slPfqKLL75Ys2bNkiR9+OGH+uc//6k77rhDBw8e1O23367GxkbdfPPNHg8MAAAAAIBbquqlDw/ba9nprP0OAAC8zu0G/Nq1a/Xoo4/qtttus9WXLVumd999V6+//rqmTZumJ598kgY8AAAAAMC89UVSg7P1OMQhZaeZywMAAIKG27vNrFixQv/2b//Wob5gwQKtWLFCknTJJZfowIED/U8HAAAA72lySltLXA8ACFRNTmlNgb02I1mKjzKTBwAABBW3G/DDhg3Tm2++2aH+5ptvatiwYZKk6upqDR48uP/pAAAA4HmnTktv7pYe/EB6eou0fJfktEynAgDv+LRUOlFrr+VmGIkCAACCj9tL0Dz00EO6/fbbtXLlypY14D/66CO9/fbbeuqppyRJ7733nnJycjybFAAAAJ5RViO9s6/1+FiNtKdMmpRgLhMAeEv7zVczhkiZQ00kAQAAQcjtBvzNN9+sM844Q7/97W/1t7/9TZI0ceJErV69WnPmzJEk3XfffZ5NCQAAAM8ZM1QaNVgqrmyt5RXQgAcQeA5VSHtP2GvMfgcAAAPI7Qa8JGVlZSkrK8vTWQAAADAQHF9sPvjqjtbaJ6WupWmGsCYygADSfvZ7XKR0TrKRKAAAIDj1ag34iooK25+7ewAAAMAPzBotRYS2HjstaUORuTwA4GlV9dJHh+217DQpzO2t0AAAAPqsV3ceQ4cO1dGjRyVJQ4YM0dChQzs8musDraKiQvfee6/S09MVGRmpjIwM/fd//7eqqqp6fY2HH35YDoej28eNN95oe83ixYu7PR8AAMCnRYdL546y19YVsRkrgMCxrlBqcLYehzqkuWnm8gAAgKDUqyVoPvjgAw0bNkyStHLlSq8Gckd1dbVycnK0bds2XXjhhbrmmmu0detW/eIXv9Dq1au1Zs0aRUX1/GvUubm5XT73zDPP6PDhw1q4cGGnz99zzz0aMmRIH38CAAAAg7LTpPVtZr2fqJV2HJWmjjSXCQA8ZdRgKXOIdPCU63jGKCmeZbYAAMDAcliW5bfTnJYsWaJHHnlE3/ve9/TYY4+11L///e/rZz/7mX7605/q/vvv7/P1S0tLlZKSovj4eBUXFysiIqLlucWLF+u5557TwYMHlZGR0Z8fQ5JrJn98fLzKy8sVFxfX7+sBAAD0ymNrpcLy1uMzR0jfnmkuDwB4Wv4p11rwuRlSxhCzWQAAQEBwp5fbp8Xv8vLydO2112rOnDk6fNi1pt4LL7ygtWvX9uVyfWJZlp555hnFxsbqoYcesj330EMPKTY2Vs8880y/3uO5555TY2OjrrvuOlvzHQAAIGBkt1uOYcdR10x4AAgUGUOkxdNpvgMAACPcbsC//vrrWrhwoaKjo7VlyxbV1dVJksrLy/XTn/7U4wG7snfvXhUXFysrK0sxMTG252JiYpSVlaUDBw6oqKjvm4n97//+ryTppptu6vKcf/zjH1q6dKl++ctf6p133lF9fX2f3w8AAGDAzRglRbVZldCSa91kAAAAAEC/ud2Af/TRR/XUU0/p6aefVnh4eEs9KytLW7Zs8Wi47uzdu1eSNH78+E6fb643n+euvLw87dmzR7Nnz9aUKVO6PO+uu+7SAw88oPvuu0+XXHKJMjIytGLFih6vX1dXp4qKCtsDAABgwEWFSbNG22vri6QmZ+fnAwAAAAB6ze0G/O7duzVv3rwO9fj4eJ06dcoTmXqlvLy85X0707z2TvN57upp9vu8efP02muvqbCwULW1tdq7d68eeeQRnTp1Spdeeqk2b97c7fWXLl2q+Pj4lkdqamqfcgIAAPTb3HbL0JTXSZ+WmskCAAAAAAEkrOdT7JKSkrRv374OG4+uXbtWY8aMcTvAfffd17KMTW/cc889Xc5695SKigr95S9/UWxsrK6++upOz/nWt75lOx43bpweeughjR49WjfeeKMeeeQRvfHGG12+x/333697773X9p404QEAgBEpcdKYodKBk621vELp7GRzmQCgL7aWSNHh0sThksNhOg0AAID7Dfibb75Z99xzj/74xz/K4XCouLhYGzZs0He+850Om6H2xrJly1RdXd3r86+88kqNHz++ZeZ7VzPcm5d06WqGfHdeeeUV1dTU6MYbb1RsbKxbr73++ut1xx13aN26dd2eFxkZqcjISLezAQAAeMXcNHsD/li1dLrRvj48APiyJqf0l8+lU6el5FgpN8O1xFYk4xgAADDH7TuR73//+3I6nVqwYIFqamo0b948RUZG6jvf+Y7uuusutwNUVVW5/Rqp5zXee1ojvjvPPPOMpO43X+1KaGiohgwZopMnT/Z8MgAAgK84J1n6207XTPjsNGlyohTC7FEAfuSTUlfzXZJKqqSXP5NS46WMIUZjAQCA4OawLMvqzYkHDx5UZmZmy3F9fb327dunqqoqnXHGGW7PFO8vy7KUkpKiiooKHTlyRDExMS3PVVdXKykpSYmJiTpw4IBb192+fbumTZumKVOm6LPPPnM7V2FhodLT0zVx4kTt2rWr16+rqKhQfHy8ysvLW9avBwAAGFDMeAfgz/7feml/m4lQmUOk/84yFgcAAAQud3q5vd6EdezYscrMzNS3vvUt/fnPf9axY8d0xhlnaNasWQPefJckh8Ohm266SVVVVfrxj39se+7HP/6xqqqqdPPNN9vqNTU12rVrlwoLC7u8bvPmqzfeeGOX5xw5ckSHDx/uUD916pQWL14sSVq0aFFvfxQAAADfQPMdgL8qLLc33yVpfmbn5wIAAAygXs+AX7VqVctj06ZNqq+v15gxY3TBBRdo/vz5mj9/vkaOHOntvDbV1dXKysrSJ598ogsvvFDnnHOOtmzZonfffVczZ87U6tWrFR0dbfsZ5s+fr5ycHK1atarD9err6zVq1ChVVlaquLhYw4cP7/R9V61apS996UuaM2eOxo8fr8TERBUVFemf//ynysrKdMEFF+itt95SVFRUr38WZsADAAAAQB89/4m08VDrcXyk9OgFUmiv55wBAAD0mju93F5Pc8rNzVVubq4k6fTp01q/fn1LQ/65555TQ0ODJk2apB07dvQrvDtiYmK0evVqPfzww3r99de1cuVKJScn67777tOSJUtszffeWL58ucrKyvS1r32ty+a75PptgMWLF+ujjz7S8uXLVV5ertjYWE2bNk2LFi3STTfdpNDQ0P7+eAAAAACAnlTWSZuL7bV56TTfAQCAT+j1DPjO1NfXa926dXrnnXe0bNkyVVVVqampyZP5ggYz4AEAgM+qaZAGhZtOAQCde2ev9Oae1uOwEOknF0iDI81lAgAAAc0rM+AlV8N948aNWrlyZctSNKmpqZo3b55++9vfKicnp1/BAQAA4COanNInpVJegXSoQvrJAimC3/AD4GOanNKaAnvt3FE03wEAgM/odQP+ggsu0KZNm5SZmamcnBzdeuuteumll5ScnOzNfAAAABhopxulH62Syutaa1tKpNkpxiIBQKe2HrGPVZKUm2EkCgAAQGd6vSheXl6ehg8frgsuuEALFizQl770JZrvAAAAgSgqTBrd7tco8wo6PxcATFqVbz8eO1RKizcSBQAAoDO9bsCfOnVK//M//6NBgwbpZz/7mUaNGqWpU6fqzjvv1F//+lcdO3bMmzkBAAAwkOam2Y8PnpKKyo1EAYBOFZySDpy015j9DgAAfEyvG/AxMTG66KKL9Nhjj2nTpk06fvy4Hn/8cQ0aNEiPP/64UlJSdOaZZ3ozKwAAAAbK1BFSfLs1lNcWmskCAJ1pP/t9SJQ0PclIFAAAgK70ugHfXkxMjIYNG6Zhw4Zp6NChCgsL086dOz2ZDQAAAKaEhkhZ7WbBf3jYtT48AJhWUSd9XGKvzUt3jV0AAAA+pNebsDqdTm3evFmrVq3SypUrtW7dOlVXV2v06NGaP3++fve732n+/PnezAoAAICBNCdVemevZH1xXNckbS7uuDwNAAy0I1Wu/Sqq6l3HYSFSVqrZTAAAAJ3odQN+yJAhqq6uVlJSkubPn69f/epXys3N1dixY72ZDwAAAKYMi5amjpQ+LW2t5RW4mlwOh7lcADBhuPSTC1xfCq7Kd20cPTiyx5cBAAAMtF434H/+859r/vz5mjBhgjfzAAAAwJdkp9kb8EUVUkG5lDHEWCQAkCSFh0rnp0qzU6QGp+k0AAAAnep1A/7WW2/1Zg4AAAD4osmJrpnwJ2pba3kFNOAB+A6HQ4oINZ0CAACgU+xQAwAAgK6FODqu+b65WKppMJMHAAAAAPwIDXgAAAB07/wUVyO+WYNT2nTIXB4AAAAA8BM04AEAANC9+ChpepK9trZQsiwzeQAEp+p66WRtz+cBAAD4EBrwAAAA6Fn7ZWhKqqT9J81kARCcVuVLD62U/neLtP8EXwICAAC/QAMeAAAAPZswXBoR4/rz8GjpsonSyBizmQAEj0anlFcoOS3p4xLp/22Q3t5rOhUAAECPwkwHAAAAgB8IcUhfmSyFhUiTEuxrwgOAt20pkSrq7LWzkjo/FwAAwIfQgAcAAEDvTBtpOgGAYLUq3348fpiUEmckCgAAgDtYggYAAAAA4LsOnpTyT9lruRkmkgAAALiNBjwAAAAAwHe1n/0+LJrfyAEAAH6DBjwAAAAAwDedOu3adLWteelSKB9lAQCAf+CuBQAAAH13pEr66+dS+WnTSQAEorWFktNqPQ4PkbJSzeUBAABwE5uwAgAAwH3bjkgrD0p7T7iOY8Kli8ebzQQgsDQ0SXkF9tqs0VJMhJk8AAAAfcAMeAAAALhve2lr812S1hXZZ6kCQH9tKZEq6+01Nl8FAAB+hgY8AAAA3Jedbj8+USt9fsxMFgCBx7Kklfn22oTh0ug4I3EAAAD6igY8AAAA3JceL6W2a4S1XyoCAPrq4CmpsNxeY/Y7AADwQzTgAQAA4D6Ho+Ms+M+OumbCA0B/rcq3Hw+LlqaNNBIFAACgP2jAAwAAoG/OHSVFhbUeW5LWFxmLAyBA1DS4NnpuKyddCnGYyQMAANAPNOABAADQN1Fh0sxR9tq6QqnJaSYPgMAwKFz6YY70b2Ok6DApIlTKSjOdCgAAoE/Cej4FAAAA6EJ2upRX2HpcXidtPypNTzKXCYD/SxgkfWWy9O/jXWvBDwo3nQgAAKBPmAEPAACAvkuJkzKH2GtsxgrAUyLDpPHDTacAAADoMxrwAAAA6J/2m7HuPC4drzGTBQAAAAB8CA14AAAA9M85ya51mttaW9j5uQAAAAAQRGjAAwAAoH8iQqXZKfba+iKpkc1YAbjBaZlOAAAA4HE04AEAANB/c9Psx1X10rYjZrIA8D8na6WHPpDe3itV1JlOAwAA4DE04AEAANB/yYOlccNaj0MdrAMPoPfWFEgnT0v/2CM9+IH08nbTiQAAADwirOdTAAAAgF7ITpPKT0tZadL5KdLgSNOJAPiD+ib7vhEsXwUAAAIIDXgAAAB4xoxRrkeIw3QSAP7k42KpusFey80wEgUAAMDTaMADAADAM2i8A3CXZUkr8+21SQmuZa0AAAACAGvAAwAAAADM2H9SOlRhr83PMBIFAADAG2jAAwAAAADMWHnQfpw4SJoywkwWAAAAL6ABDwAAAO+qb5Kq6k2nAOBrTtRKn5TaazkZLGcFAAACCmvAAwAAwDtKKqW8QmnTIWnmaOnrZ5pOBMCXrCmQnFbrcWSodH6KuTwAAABeQAMeAAAAnre2UHppe+vxh4elyydJUdx+ApDrN2PWFdprs1Ok6HAzeQAAALyEJWgAAADgeWckSm1XkTjdKG0uNhYHgI/56LBU3WCv5WQYiQIAAOBNNOABAADgecOiO26kuLaw83MBBBfLklbl22tnJEpJsUbiAAAAeBMNeAAAAHhHdpr9uLBcKjhlJAoAH7L3hHS40l7LzTASBQAAwNtowAMAAMA7poxwzYRvK49Z8EDQaz/7PXGQawY8AABAAKIBDwAAAO8IcUhZqfba5mKptqHz8wEEh7lp0pQ2DffcDNd4AQAAEIDCTAcAAABAAJuTKr21V3JaruP6JunDw2y2CASzMxJdj9Iq12/FzE4xnQgAAMBrmAEPAAAA74mPks4aaa/lFbo2YQQQ3EbGSleeIUWHm04CAADgNTTgAQAA4F3Z6fbj4krpwEkzWQAAAABgANGABwAAgHdNGO7aZLEtNmMFAAAAEARowAMAAMC7QhyuTRfb2lIiVdWbyQMAAAAAA4QGPAAAALzv/FQprM2tZ6NT2nTIXB4AA+sfe6StJVKT03QSAACAARVmOgAAAACCQGyEdHaS9FFxay2vULogU3I4zOUC4H1lNdI7eyVL0tAoKSdDmpcuRfFxFAAABD5mwAMAAGBgNG/GGhYizRwlXTvNbB4AA2N1gav5LkknT0v/3CdZVrcvAQAACBRMOQAAAMDAGDtUWjRVmp7kmhEPIPDVNUrr2m26PDtFig43kwcAAGCA0YAHAADAwHB0shkrgMD2UbFU22iv5WYYiQIAAGACS9AAAAAAADzPsqSVB+21KYnSiBgzeQAAAAygAQ8AAAAA8Lw9ZVJJlb02P9NMFgAAAENowAMAAAAAPG9lvv14ZIw0KcFIFAAAAFNowAMAAMCcukZpfZG0fJfpJAA86XiNtL3UXsvNkEIcRuIAAACYwiasAAAAGHiVddI7+6RNh1wbNDok5aRLQ6NNJwPgCavzJavNcVSYdF6KqTQAAADGMAMeAAAAAy88VNpQ5Gq+S65G3boio5EAeMjpL36zpa05qa4mPAAAQJChAQ8AAICBFxUmzRxtr60vkpqcZvIA8JwPD7d+uSa5fsNlXrqxOAAAACbRgAcAAIAZ2Wn241Onpc+OmskCwDMsS1qVb69NGSGNiDESBwAAwDQa8AAAADAjNV7KGGKv5RUaiQLAQ3aXSUeq7LX5GUaiAAAA+AIa8AAAADCn/Sz4ncek4zVmsgDov7pGaXibzZSTYqVJCebyAAAAGEYDHgAAAObMGCVFt9mY0ZK0llnwgN86K0n60Xzp1hnSxOFSbobkcJhOBQAAYAwNeAAAAJgTESqdl2KvbSiSGtmMFfBbIQ5XI/6e2R1/ywUAACDI0IAHAACAWe0bdJX10idHzGQB4FnMfgcAAEGOBjwAAADMSh4sjRtmr7EZKwAAAIAAQAMeAAAA5rWfBb+nTCqtMpMFAAAAADyEBjwAAADMm54kxUbYa2zGCviH4kqppNJ0CgAAAJ9EAx4AAADmhYdKs9ttxrrxkFTfZCYPgN5bvkv68RrpyU3S9lLJaZlOBAAA4DNowAMAAMA3zG23DE18lHSy1kwWAL1ztFr67Kjrz7uOS3/YLH142GwmAAAAHxJmOgAAAAAgSRoRI505QhoU7loTfsxQyeEwnQpAd1bn24+jw6Szk4xEAQAA8EU04AEAAOA7bj+XpjvgL043ShsO2WtZaVIkHzMBAACasQQNAAAAfAfNd8B/bDzkasI3c0jKSTcWBwAAwBfRgAcAAAAAuMdpSavy7bVpI6Xhg4zEAQAA8FU04AEAAAAA7tl5zLUBa1u5GUaiAAAA+DIa8AAAAPB9xZWmEwBoq/3s91GDpQnDjUQBAADwZeyOAwAAAN90ulHaXCytLZQKy6XvZUnpQ0ynAlBaJe04Zq/lZrCHAwAAQCdowAMAAMD3WJb0i/X2me9rC2nAA75gdYH9eFC4NGu0mSwAAAA+jiVoAAAA4HscDumcZHvto2KptsFMHgAutQ3ShiJ7LStVigg1kwcAAMDH0YAHAACAb5qTKoW0WdKivkn68LC5PACkjYekuqbWY4ekeenG4gAAAPg6GvAAAADwTUOipGkj7bW8QtfyNAAGntPquPnqWUnS8EFG4gAAAPgDGvAAAADwXdlp9uPiSunASTNZgGBXUimdPG2v5WYYiQIAAOAvaMADAADAd01MkBLbza7NKzSTBQh2o+Okn1wgXTrR9RsqowdL44eZTgUAAODTaMADAADAd4U4pKx2s+C3lEjV9WbyAMFucKR00Tjpx/Ol2851bZgMAACALtGABwAAgG87P0UKbdPka3S6NoIEYE5oCGu/AwAA9AINeAAAAPi2wZHS2cn2GpuxAgAAAPADNOABAADg+9pvxnq0WtpTZiYLAAAAAPQSDXgAAAD4vnHDpKRYe20tm7ECXue0pNONplMAAAD4LRrwAAAA8H0OhzS33Sz4bUekijozeYBgseOo9MD70l8/l45Vm04DAADgd2jAAwAAwD/MTpHC29y+Nllsxgp428p81wz4Dw5KD6+SXv/cdCIAAAC/QgMeAAAA/mFQuDRjlOvPKXHS18/suDY8AM8pqZR2HW89tiSNGmwsDgAAgD8KMx0AAAAA6LWFY11N94whrmVpAHjPqnz7cWyEdO4oI1EAAAD8FQ14AAAA+I+RsT2fA6D/ahqkTYfttaxUKTzUTB4AAAA/xRI0AAAAAAC7DUVSfVPrcYhDmpduLg8AAICfogEPAAAAAGjltDouPzM9SRoabSQOAACAP6MBDwAAAABo9dlRqazWXpufYSQKAACAv6MBDwAAAP9lWVL+KemFT1xNQwD9t/Kg/Tg1Thoz1EwWAAAAP8cmrAAAAPBPn5ZKb+2RiipcxxV10pkjzGYC/F1xpbS7zF6bnyk5HGbyAAAA+DlmwAMAAMA/Vde3Nt8l6fNjUlmNuTxAIGi/9ntshDQj2UgUAACAQEADHgAAAP5pxigpus0vdFqS1hYaiwP4vZoGadMhey07TQoPNZMHAAAgANCABwAAgH+KCJXOS7HXNhySGp1m8gD+bl2h1NDm30+IQ8pON5cHAAAgANCABwAAgP+am2Y/rqhzrQ0PwD1OS1pdYK+dkywNiTKTBwAAIEDQgAcAAID/GjVYGjfMXssr6PxcAF1zSLrxbOncUa6Z75KUm2EyEQAAQEAI6/kUAAAAwIfNTZP2nWg93l0mlVZJI2PNZQL8jcMhZQ51Pb4yWfrkiJQ5xHQqAAAAv8cMeAAAAPi3s5OkmHB7jc1Ygb4bEiXlZLia8gAAAOgXv27Ab9u2TQ888IAWLlyoxMREORwO5ebm9vl6H330kS655BINGTJEMTExmj17tl577bUuzy8pKdGNN96o5ORkRUVFaeLEifrJT36ihoaGPmcAAACAm8JDpfNT7bWNh6SGJjN5AAAAAOALfr0EzfLly7V06VJFRERowoQJOn78eJ+vtXLlSi1cuFBRUVH6+te/rsGDB+v111/X1VdfraKiIt133322848cOaLzzjtPhw4d0hVXXKHx48dr9erVevDBB/Xhhx9q+fLlcjBjBAAAYGDMTZP+daD1uLpB2lIinZdiLhMAAACAoOewLMsyHaKvduzYobq6Ok2dOlVlZWVKTk5WTk6OVq1a5dZ1GhsbNWnSJB06dEgbN27U9OnTJUnl5eWaNWuW8vPztWfPHqWnp7e85vrrr9fzzz+vP/zhD7rtttskSZZladGiRXrllVf00ksv6Zprrul1hoqKCsXHx6u8vFxxcXFu5QcAAICkJza61n9vNnaodN8cc3kAAAAABCR3erl+vQTNlClTdM455yg8PLznk7vxwQcfaP/+/Vq0aFFL812S4uPj9cADD6i+vl7PPfdcS72yslKvvvqqxowZo1tvvbWl7nA49Nhjj0mSnn766X5lAgAAgJuy0+3H+09KxZVmsgD+oMkp/f4jaV2hVM+STQAAAN7g1w14T2meMX/hhRd2eG7hwoWSpNWrV7fUNmzYoLq6On3pS1/qsMxMenq6Jk6cqHXr1qmpiZtYAACAAXPWSCku0l7LKzCTBfAH249Knx2VXtwu/eB9afkuV1MeAAAAHkMDXtLevXslSePHj+/wXFJSkmJjY1vO6en85np9fb0KCrr+wFdXV6eKigrbAwAAAP0QGiLNabMZa2SoFBFqLg/g61YebP1zdYO0+7gUwj5WAAAAnuTXm7B6Snl5uSTXkjOdiYuLazmnt+e3Pa8zS5cu1Y9+9KM+5QUAAEAXslKlz4+5NmU9d5QUxe0u0KlDFdLeE/ZabobkoAEPAADgScY/kdx3332qq6vr9fn33HNPlzPP/cn999+ve++9t+W4oqJCqamp3bwCAAAAPRo+SPr+XNMpAN+3Ot9+HBcpnZNsJAoAAEAgM96AX7Zsmaqrq3t9/pVXXunxBnzzTPauZqxXVFRo6NChbp3f9rzOREZGKjIyssvnAQAAAMArquqlDw/ba3PTpHCWbAIAAPA04w34qqoq0xFaGvp79+7VjBkzbM8dOXJEVVVVmjVrVqfnd2bv3r2KiIhQWlqalxIDAAAAQB+tL5Ia2my2GuqQsvnsAgAA4A1swiopJydHkvTuu+92eG7FihW2cyRp9uzZioiI0HvvvSfLsmznFxQUaPfu3crKylJYmPHvNwAAAACgVZOz4/Iz5yRL8VFG4gAAAAS6oGrANzQ0aNeuXdq/f7+tvmDBAo0ZM0YvvfSStm3b1lIvLy/XT3/6U0VEROib3/xmSz0uLk5f//rXdeDAAS1btqylblmW7r//fknSzTff7N0fBgAAAL1XXe/adBIIdp+WSidP22vzM81kAQAACAJ+PUV7165deuyxxyRJtbW1LbXFixe3nPPss8+2/Pnw4cOaPHmy0tPTlZ+f31IPCwvTM888o4ULF2revHn6+te/rsGDB+v1119XQUGBfvGLXygjI8P23o899phWrlypb3/72/rXv/6lcePGafXq1dq4caP+4z/+Q1//+te99WMDAACgNyxLOnhKWlsofVwsJcZIP8iWHA7TyQBzVubbjzOGuB4AAADwCofVfg0VP7Jq1SrNnz+/23Pa/nj5+fnKzMzs0IBv9uGHH2rJkiVav369GhoaNHXqVN177726+uqrO712SUmJHnzwQb311ls6efKk0tPT9c1vflPf/e53FRER4dbPUlFRofj4eJWXlysuLs6t1wIAAKATe8ukX220174zRxoz1EwewLSicmnpWnvthunSzNFG4gAAAPgrd3q5ft2ADyQ04AEAADzMaUlLVkplta2180ZL1083Fgkw6oVPpA2HWo/jIqVHL5DCgmplUgAAgH5zp5fLnRYAAAACU4hDyk631z4uca0HDwSbqnrpo2J7bV46zXcAAAAv424LAAAAgev8FCm0zZrvjU5p02FzeQBT1ha6/v43C3VIc9PM5QEAAAgSNOABAAAQuAZHStOT7LW8AtcGrUAwGREjjR7cejxjlGsJGgAAAHhVmOkAAAAAgFdlp7uWnmlWWi3tPSFNGG4uEzDQzkmWzk6S9p2QVuVL8zNMJwIAAAgKNOABAAAQ2MYPk0bGuBrvzdYW0oBH8HE4pPHDXQ8AAAAMCJagAQAAQGBzdLLW9dYSqbLOTB4AAAAAQYMGPAAAAALf7BQprM2tb5MlbThkLg8AAACAoEADHgAAAIEvJkKakWyvrS2UnGzGCgAAAMB7aMADAAAgOGSn24+P10i7jpvJAgyET45IB09KFl80AQAAmMImrAAAAAgOmUOkUYOl4srWWl6BdEaisUiA1zQ5pVc+k8rrpPR4KTdDOidZCg81nQwAACCoMAMeAAAAwcHhkLLbbca6/SibsSIwbT3iar5LUkG59NwnUkmV2UwAAABBiBnwAAAACB6zRkvLd7ma8eeNluamSYMjTacCPG9Vvv147FApLd5IFAAAgGBGAx4AAADBIzpcumOWlBonRXIrjABVcEo6cNJey80wkQQAACDo8akDAAAAwWXcMNMJAO9qP/t9SJQ0PclIFAAAgGDHGvAAAAAAECgq6qSPS+y1eelSKB/9AAAATOAuDAAAAAACxdpCqdHZehwWImWlmssDAAAQ5GjAAwAAAEAgaHRKeQX22sxRbDQMAABgEA14AAAABLeqeun9A9IvN0hNzp7PB3zV1hKpvM5eY/NVAAAAo9iEFQAAAMGp0Sn9+VNpS0nrkh2flErnJJvNBfRV+81Xxw2TUuONRAEAAIALM+ABAAAQnMJCpLIa+3rZawvN5QH6I/+UdPCUvcbsdwAAAONowAMAACB4zU2zH+86Lh2tNpMF6I/2s9+HRElnjTQSBQAAAK1owAMAACB4nZ0sxYTba8yCh78pPy19XGyv5aRLoXzcAwAAMI07MgAAAASviFBpdoq9tqFIamgykwfoi8OVrr/LzcJDpKy0rs8HAADAgKEBDwAAgODWfhma6gZp2xEzWYC+OCNR+skC6etnSiNjpJmjpdgI06kAAAAgKcx0AAAAAMCokbHSxOHS7rLWWl6hq4kJ+IuoMGleupSdJtXxGxwAAAC+ghnwAAAAQHa6/XjfCam40kwWoD8cDlczHgAAAD6BBjwAAAAwbaQ0uN2SHWzGCgAAAKCfaMADAAAAYSHSnFR7bdMhqZ6lPAAAAAD0HQ14AAAAQJKy0iRHm+PaRunjYmNxgG5V10uVdaZTAAAAoAc04AEAAABJShgknZFor+WxDA181AcHpR98ID3/iVRUbjoNAAAAukADHgAAAGjWfjPW/FM0N+F7GppcXw41OqWNh6Sla6V395tOBQAAgE7QgAcAAACaTUmUhkS1Ho8d6mpyAr7k4xKpqt5eO3OEmSwAAADoVpjpAAAAAIDPCA2RFmRKZbXS3DRp1GDTiQA7y5JW5dtrE4fzdxUAAMBH0YAHAAAA2lowxnQCoGsHTkqF7ZZFys0wEgUAAAA9YwkaAAAAAPAX7We/D4+Wpo40EgUAAAA9owEPAAAAAP7gZK209Yi9lpMhhTiMxAEAAEDPaMADAAAAgD/IK5ScVutxRKg0J9VcHgAAAPSIBjwAAADQE6cl7Tou1TSYToJg1dAkrS20184bLQ0KN5MHAAAAvcImrAAAAEBXquqlDUWuxuexGumqM6T5maZTIRhtLnb9fWyLzVcBAAB8HjPgAQAAgK68tkP6+y5X811yLQFiWd2/BvA0y+q4+eqkBCl5sJE4AAAA6D0a8AAAAEBXstqtr32kStp3wkwWBK/9J6WiCnuN2e8AAAB+gQY8AAAA0JUJw6URMfZaXmHn5wLe0n72e8Ig6cwRRqIAAADAPTTgAQAAgK44HFJ2mr22tUSqrDOTB8Gnql7adsRey0mXQhxm8gAAAMAtNOABAACA7pyXIoW1uW1usqSNh8zlQXCJjZB+kC3NS5ciQ12P81N7fh0AAAB8QpjpAAAAAIBPi42QzkmWPjzcWltbKC0YwyxkDIzkwdLXz5QunSgVlUuDwk0nAgAAQC8xAx4AAADoSftlaI7VSLuPm8mC4DUoXJqYYDoFAAAA3EADHgAAAOjJmKHSqMH2GpuxAgAAAOgBDXgAAACgJ51txvppqXTqtJk8AAAAAPwCDXgAAACgN2aNliJCW4+dlrShyFweBDbLMp0AAAAAHkADHgAAAOiN6HDp3FH22tpCVyMe8KQTtdLDq6T39ks1DabTAAAAoB9owAMAAAC91X4ZmpOnpR1HzWRB4FpT4Nro9++7pPv/Jb3+uelEAAAA6CMa8AAAAEBvpQ+R0uLttY+KjURBgKpvkta12eC3wSk1Os3lAQAAQL/QgAcAAADc0TwLfvww6VtnS9dNM5sHgeWjw1J1u2VncjKMRAEAAED/hZkOAAAAAPiVc0dJY4ZKyYNNJ0GgsSxpVb69dkailBRrJA4AAAD6jxnwAAAAgDsiw2i+wzv2npAOV9pruRlGogAAAMAzaMADAAAAgC9oP/s9cZBrBjwAAAD8Fg14AAAAADCtrEb65Ii9lpshhTiMxAEAAIBn0IAHAAAAPMWyTCeAv1pTILX96xMZKs1OMRYHAAAAnsEmrAAAAEB/OC1p13Epr8C1WeZlk0wngr+pb5LWFdlr56dK0eFm8gAAAMBjaMADAAAAfbX7uPTidul4jet4/0npkvFSeKjZXPAvHx6WahrstZx0M1kAAADgUSxBAwAAAPTVkKjW5rskVdVL2450fT7QnmV13Hx1SqI0MtZIHAAAAHgWDXgAAACgr0bGShOG22t5hWaywD/tKZOKK+213AwjUQAAAOB5NOABAACA/pibZj/ed0Iqqez8XKC99rPfR8RIkxONRAEAAIDn0YAHAAAA+mN6khQbYa+tZRY8eml2ijR+WOtxboYU4jAWBwAAAJ7FJqwAAABAf4SFSHNSpXf3t9Y2HpIumyRFsBkrenBWkutxqELKK3A15AEAABAwmAEPAAAA9NfcNKntpOXaRunjYmNx4IdS4qRrpkpRzJECAAAIJDTgAQAAgP5KGNRx3W42YwUAAACCHg14AAAAwBPab8aaf0oqKjcSBQAAAIBvoAEPAAAAeMLUEVJ8pL3GZqwAAABAUKMBDwAAAHhCaIiU1W4W/IeHpdONZvLAd729V9pxVHJappMAAADAy9jhBwAAAPCUrFTpnb1Sc1+1rkn66LCUnW40FnzI8RrprT2uvyMjYqScdNcXNxGhppMBAADAC5gBDwAAAHjK0Ghp6kh7bW2hZDHTGV9Ynd/6Bc3RaunNPcyEBwAACGA04AEAAABPym6zDM3gCOmMRKmJBivkWo5ofZG9NidViuIXkwEAAAIVd3oAAACAJ01OlM4dJZ01UjorSQpjzgu+8OFhqbbNngAOuZagAQAAQMCiAQ8AAAB4UohD+tbZplPA11iWtPKgvXbmCCkxxkweAAAADAim4wAAAACAt+06LpVW22vzM81kAQAAwIChAQ8AAAAA3rYy336cFCtNHG4kCgAAAAYODXgAAAAA8Kaj1dKOo/ZabobkcBiJAwAAgIFDAx4AAAAYCCdrpa0lplPAhDUFktXmODpMOm+0sTgAAAAYOGzCCgAAAHiL05J2HpPyCqXtpVJoiDR+uBQbYToZBsrpRml9kb02J1WK5KMYAABAMGAGPAAAAOAtNQ3Sso+lT0tdM6AbndKGoh5fhgCy6ZCrCd/MISknw1QaAAAADDAa8AAAAIC3xEZI5yTba2sLXTPjEficlrQq316bOlJKGGQkDgAAAAYeDXgAAADAm7LT7MfHaqQ9ZWayYGDtOi6VVttr8zOMRAEAAIAZNOABAAAAbxozVEqOtdfyCsxkwcCqaZDiIluPk2OlCcPN5QEAAMCAY+cfAAAAwJscDik7XXptR2vtk1Kp/LQUH2UuF7zv3FHS9CRpa4lrKZrzU11/HwAAABA0mAEPAAAAeNt5o6WI0NZjpyWtZzPWoBAWIs0cLf13ljQn1XQaAAAADDAa8AAAAIC3RYe7ZkO3ta6IzViDTQiz3wEAAIINDXgAAABgIMxttxnriVppx1EzWQAAAAAMCBrwAAAAwEBIj5dS4+y1tYVmsgAAAAAYEDTgAQAAgIHQvBlrW58ddc2ER+AoqZTKakynAAAAgI+gAQ8AAAAMlHNHSVFhrceWpHXMgg8or++UfrhSWrZZ2n1csljnHwAAIJjRgAcAAAAGSlSYNLPdZqzri6Qmp5k88KzSKunzY64vVj4plZ7YJH1cYjoVAAAADKIBDwAAAAyk9svQVNRJB08ZiQIPW5VvP44Jl6aNNBIFAAAAviGs51MAAAAAeExKnJQ5RCqrleakSlmp0vBBplOhv2obpI2H7LWsNCki1EweAAAA+AQa8AAAAMBAu/EcKT5SCuUXUgPGhkNSXVPrsUPSvPQuTwcAAEBwoAEPAAAADLRh0aYTwJOclrQ6316bnsT/zgAAAGANeAAAAADolx1HpWM19lpuhpEoAAAA8C004AEAAACgP9pvvpoSJ40bZiQKAAAAfAsNeAAAAMBXOC3TCeCukkpp53F7LTdDcjiMxAEAAIBvoQEPAAAAmHaiVnpzt/SD910NXfiP1QX245hw6dxRZrIAAADA57AJKwAAAGDSC59IGw9JzZPf1xZKV00xGgm9VNMgbTpkr81NkyJCzeQBAACAz2EGPAAAAGDS4MjW5rvkasbXNxmLAzdsKJLq2vxvFeKQstPN5QEAAIDPoQEPAAAAmJSVaj+ubZS2lJjJgt5zWh2Xn5meJA2LNpMHAAAAPokGPAAAAGBSYow0OcFeyyvo/Fz4jkMVrrX728rNMBIFAAAAvosGPAAAAGBa+2VLDp5yNXjhu9LipR/Ply4aJ8VGSKlx0tihplMBAADAx7AJKwAAAGDa1BFSfKRUXtdayyuQrplqLhN6NjRaunSidPE46eRpyeEwnQgAAAA+hhnwAAAAgGmhIdKcdmvBf3hYOt1oJg/cEx4qjYgxnQIAAAA+iAY8AAAA4Auy0qS2E6jrmqTNxcbiAAAAAOg/GvAAAACALxgWLZ05wl7LK5Asy0weAAAAAP1GAx4AAADwFXPT7MdFFVJBuZks6MhpSQ1NplMAAADAj9CABwAAAHzFlBGumfBt5RWYyYKOPjsq/eAD6f92SSdrTacBAACAH/DrBvy2bdv0wAMPaOHChUpMTJTD4VBubq7b1zl8+LB+/etf68ILL1RaWpoiIiKUlJSkr371q9q0aVOnr3n44YflcDi6fOTn5/fvhwMAAEDwCXFIWe02Y91cLNU0mMkDu5UHpap6acV+6aGV0pu7TScCAACAjwszHaA/li9frqVLlyoiIkITJkzQ8ePH+3Sd3/zmN/rZz36msWPH6sILL1RiYqL27t2r5cuXa/ny5XrppZd09dVXd/ra66+/XhkZGR3qQ4YM6VMWAAAABLk5qdJbe13LnUhSg1P68LCUm2E0VtArrpR2l7UeOy0pMcZcHgAAAPgFv27AX3XVVbr00ks1depUlZWVKTk5uU/XmTVrllatWqWcnBxbPS8vTwsWLNDtt9+uyy+/XJGRkR1eu3jx4j7NugcAAAA6FR8lnTVS2npEcsi1MevowaZTYVW+/Tg2QprRt88fAAAACB5+3YCfMmWKR67zla98pdN6dna25s+fr3fffVfbt2/Xueee65H3AwAAALo1P1NKipWy0jquCY+BV9MgbTpkr2WnSeGhZvIAAADAb/h1A34ghIeHS5LCwjr/T7VmzRpt2rRJISEhGj9+vP7t3/5NsbGxPV63rq5OdXV1LccVFRWeCQwAAAD/N26Y6wHfsK7QtRRQsxCHlJ1uLg8AAAD8Bg34bhQWFupf//qXkpOTNXXq1E7PWbJkie14yJAheuKJJ/TNb36z22svXbpUP/rRjzyWFQAAAIAXOC1pdYG9dk6yNCTKTB4AAAD4lRDTAXxVQ0ODrrvuOtXV1elnP/uZQkPtv1561lln6Y9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\n"},"metadata":{}}]},{"cell_type":"code","source":["X['AhorroFamilia_factor'] = pd.cut(X['Ahorro Familia'], 5)\n","plot_by_woe(woe_continous(X,'AhorroFamilia_factor',y))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"iqBNemFvhzkF","outputId":"80b90bdf-084b-45a8-a276-d844c37c9ab3"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 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\n"},"metadata":{}}]},{"cell_type":"code","source":["X['TotalPresup_factor'] = pd.cut(X['Total Presup. Proyecto'], 8)\n","plot_by_woe(woe_continous(X,'TotalPresup_factor',y))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":886},"id":"CSu5fpgBiDpd","outputId":"6f762ab7-6330-42a4-d88c-fca13c46bf35"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["X['TotalComplem_factor'] = pd.cut(X['Total Complem.'], 6)\n","plot_by_woe(woe_continous(X,'TotalComplem_factor',y))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":906},"id":"pQRQwDp-iN2s","outputId":"f1121b42-3bbd-49b2-8af1-aae8767d1d54"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 Axes>"],"image/png":"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= pd.cut(X['Total Incremento'], 2)\n","plot_by_woe(woe_continous(X,'TotalIncremento_factor',y))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":882},"id":"NvMoL-y3lDo5","outputId":"80838819-2ed4-4fa0-96f0-05f9b470ac7a"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 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\n"},"metadata":{}}]},{"cell_type":"code","source":["X['TotalAlbergue_factor'] = pd.cut(X['Total Albergue Transitorio'], 3)\n","plot_by_woe(woe_continous(X,'TotalAlbergue_factor',y))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":900},"id":"FEGAECJ_lcie","outputId":"f2e65d9d-d55f-41de-84d2-8daf87236262"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"text/plain":["<Figure size 1800x1200 with 1 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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["######**Agrupamiento de las variables de acuerdo con los binnings propuestos**"],"metadata":{"id":"y8rhlRL9mfxf"}},{"cell_type":"code","source":["#Postula Proyecto:\n","df_modelo1 = df_modelo_1.loc[:,['target','PostulaProyecto:Sí']]\n","\n","#Tipología\n","df_modelo1['Tipologia:CCH'] = df_modelo_1.loc[:,'Tipologia:CCH']\n","\n","#etapa_1:\n","df_modelo1['etapa_1:Fecha_complem_1'] = df_modelo_1.loc[:,'etapa_1:Fecha_complem_1']\n","df_modelo1['etapa_1:Acta Entrega Terreno'] = df_modelo_1.loc[:,'etapa_1:Fecha Acta Entrega Terreno']\n","#df_modelo1['etapa_1:Fecha_incr1_Fecha_Aprob_Proy'] = sum([df_modelo_1.loc[:,'etapa_1:Fecha_incr_1'],df_modelo_1.loc[:,'etapa_1:Fecha RE Aprobación Proyecto']])\n","\n","#etapa 2:\n","#df_modelo1['etapa_2:Fecha Acta Entrega Terreno'] = df_modelo_1.loc[:,'etapa_2:Fecha Acta Entrega Terreno']\n","df_modelo1['etapa_2:Fecha Re Aprobación Proyecto'] = df_modelo_1.loc[:,'etapa_2:Fecha RE Aprobación Proyecto']\n","df_modelo1['etapa_2:Fecha_compl1_Fecha_1er_Incr_Alza_Materiales'] = sum([df_modelo_1.loc[:,'etapa_2:Fecha_complem_1'],df_modelo_1.loc[:,'etapa_2:Fecha RE 1er Incr. Alza Materiales']])\n","\n","#etapa 3:\n","df_modelo1['etapa_3:Fecha_incr1_Fecha_1er_Incr_Alza_Materiales'] = sum([df_modelo_1.loc[:,'etapa_3:Fecha_incr_1'],df_modelo_1.loc[:,'etapa_3:Fecha RE 1er Incr. Alza Materiales']])\n","#df_modelo1['etapa_3:Fecha_Aprob.Proyecto_Fecha_Entrega_Terreno_Fecha_Término_Obra'] = sum([df_modelo_1.loc[:,'etapa_3:Fecha RE Aprobación Proyecto'], df_modelo_1.loc[:,'etapa_3:Fecha Acta Entrega Terreno'], df_modelo_1.loc[:,'etapa_3:Fecha Término de Obra']])\n","df_modelo1['etapa_3:Fecha_complem_1'] = df_modelo_1.loc[:,'etapa_3:Fecha_complem_1']\n","\n","#etapa 4:\n","df_modelo1['etapa_4:Fecha RE 2do Incr. Alza Materiales'] = df_modelo_1.loc[:,'etapa_4:Fecha RE 2do Incr. Alza Materiales']\n","#df_modelo1['etapa_4:Fecha_Albergue_Fecha_Termino_Fecha_1er_Incr.Alza'] = sum([df_modelo_1.loc[:,'etapa_4:Fecha RE 1er Albergue Transitorio'], df_modelo_1.loc[:,'etapa_4:Fecha Término de Obra'], df_modelo_1.loc[:,'etapa_4:Fecha RE 1er Incr. Alza Materiales']])\n","df_modelo1['etapa_4:Fecha Acta Entrega Terreno'] = df_modelo_1.loc[:,'etapa_4:Fecha Acta Entrega Terreno']\n","\n","#Aporte MINVU\n","df_modelo1['AporteMINVU:11.0-14.0'] = np.where((df_modelo_1['Ahorro Eximido (Aporte MINVU)']>11.0) & (df_modelo_1['Ahorro Eximido (Aporte MINVU)']<=14.0),1,0)\n","df_modelo1['AporteMINVU:missing'] = np.where(df_modelo_1['Ahorro Eximido (Aporte MINVU)'].isnull(),1,0)\n","\n","#Ahorro Familia\n","df_modelo1['AhorroFamilia:>38.2'] = np.where(df_modelo_1['Ahorro Familia']>38.2,1,0)\n","df_modelo1['AhorroFamilia:missing'] = np.where(df_modelo_1['Ahorro Familia'].isnull(),1,0)\n","\n","#Total Presup. Proyecto\n","#df_modelo1['TotalPresup:<=1042.25'] = np.where(df_modelo_1['Total Presup. Proyecto']<=1042.25,1,0)\n","df_modelo1['TotalPresup:1042.25-1268.0'] = np.where((df_modelo_1['Total Presup. Proyecto']>1042.25) & (df_modelo_1['Total Presup. Proyecto']<=1268.0),1,0)\n","df_modelo1['TotalPresup:1268.0-1719.5'] = np.where((df_modelo_1['Total Presup. Proyecto']>1268.0) & (df_modelo_1['Total Presup. Proyecto']<=1719.5),1,0)\n","df_modelo1['TotalPresup:>1719.5'] = np.where(df_modelo_1['Total Presup. Proyecto']>1719.5,1,0)\n","\n","#Total Compl.\n","#df_modelo1['TotalComplem:<=70'] = np.where(df_modelo_1['Total Complem.']<=70,1,0)\n","df_modelo1['TotalComplem:70-350'] = np.where((df_modelo_1['Total Complem.']>70) & (df_modelo_1['Total Complem.']<-350),1,0)\n","df_modelo1['TotalComplem:>350'] = np.where(df_modelo_1['Total Complem.']>350,1,0)\n","\n","#Total Incremento\n","df_modelo1['TotalIncrem.:>0'] = np.where(df_modelo_1['Total Incremento']>0,1,0)\n","\n","#Total Albergue Transitorio\n","df_modelo1['TotalAlbergue:>0'] = np.where(df_modelo_1['Total Albergue Transitorio']>0,1,0)\n","\n"],"metadata":{"id":"giI4hnzcmfI-"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["Base de datos final"],"metadata":{"id":"a36K9hNcMi_G"}},{"cell_type":"code","source":["df_modelo1.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":308},"id":"mIlVJxt4zfhl","outputId":"e5df340c-93cb-49d7-ce2b-cb01c671f610"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["   target  PostulaProyecto:Sí  Tipologia:CCH  etapa_1:Fecha_complem_1  \\\n","0       0                   0              0                        0   \n","2       0                   0              0                        0   \n","4       0                   0              0                        0   \n","5       0                   0              0                        0   \n","6       0                   0              0                        0   \n","\n","   etapa_1:Acta Entrega Terreno  etapa_2:Fecha Re Aprobación Proyecto  \\\n","0                             1                                     1   \n","2                             0                                     0   \n","4                             0                                     0   \n","5                             0                                     0   \n","6                             0                                     0   \n","\n","   etapa_2:Fecha_compl1_Fecha_1er_Incr_Alza_Materiales  \\\n","0                                                  0     \n","2                                                  0     \n","4                                                  0     \n","5                                                  0     \n","6                                                  0     \n","\n","   etapa_3:Fecha_incr1_Fecha_1er_Incr_Alza_Materiales  \\\n","0                                                  1    \n","2                                                  1    \n","4                                                  1    \n","5                                                  1    \n","6                                                  1    \n","\n","   etapa_3:Fecha_complem_1  etapa_4:Fecha RE 2do Incr. 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Alza Materiales</th>\n","      <th>...</th>\n","      <th>AporteMINVU:missing</th>\n","      <th>AhorroFamilia:&gt;38.2</th>\n","      <th>AhorroFamilia:missing</th>\n","      <th>TotalPresup:1042.25-1268.0</th>\n","      <th>TotalPresup:1268.0-1719.5</th>\n","      <th>TotalPresup:&gt;1719.5</th>\n","      <th>TotalComplem:70-350</th>\n","      <th>TotalComplem:&gt;350</th>\n","      <th>TotalIncrem.:&gt;0</th>\n","      <th>TotalAlbergue:&gt;0</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>1</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>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>2</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>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>1</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>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>4</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>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>1</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>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>5</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>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>1</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>1</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>6</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>1</td>\n","      <td>0</td>\n","      <td>0</td>\n","      <td>...</td>\n","      <td>1</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>1</td>\n","      <td>0</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>5 rows × 22 columns</p>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-263e961f-2763-4199-a93f-d231739a2a74')\"\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 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\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","    .colab-df-buttons div {\n","      margin-bottom: 4px;\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-263e961f-2763-4199-a93f-d231739a2a74 button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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oversampling"],"metadata":{"id":"aujJTzAbMt71"}},{"cell_type":"code","source":["y_train.value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"-2MoLp4u27XB","outputId":"a5bd2b8b-4c2f-4fce-cb89-502ee40b4bc0"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["1    1866\n","0     684\n","Name: target, dtype: int64"]},"metadata":{},"execution_count":260}]},{"cell_type":"code","source":["from imblearn.over_sampling import RandomOverSampler\n","\n","#balanceado la muestra\n","os = RandomOverSampler()\n","X_train_o, y_train_o = os.fit_resample(X_train, y_train)\n","y_train_series = pd.Series(y_train_o)\n","#check value counts after oversampling\n","y_train_series.value_counts()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"whJ2u3-73aZ4","outputId":"d57c8a4e-f8db-453b-8a5e-72163ff69c94"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["1    1866\n","0    1866\n","Name: target, dtype: int64"]},"metadata":{},"execution_count":261}]},{"cell_type":"markdown","source":["#####Paso 5:Ajuste del modelo"],"metadata":{"id":"sTh6bVfv3xIr"}},{"cell_type":"code","source":["from sklearn.linear_model import LogisticRegression\n","model = LogisticRegression()\n","model.fit(X_train_o, y_train_o)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":75},"id":"yHkYzg4p3wQl","outputId":"5ac9175e-35b1-4125-c196-fd689c97a903"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["LogisticRegression()"],"text/html":["<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression()</pre></div></div></div></div></div>"]},"metadata":{},"execution_count":263}]},{"cell_type":"markdown","source":["Evaluación de los coeficientes obtenidos"],"metadata":{"id":"lFgS4Q-nNCcL"}},{"cell_type":"code","source":["model.coef_"],"metadata":{"id":"fLwwNOcH6QpI","outputId":"84b127c4-2e0c-44e8-927c-eb3dda6e5227","colab":{"base_uri":"https://localhost:8080/"}},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[ 5.44736976e+00,  5.13585200e-02,  3.59856545e-03,\n","         1.06672182e+00,  5.94547544e-01,  1.18494711e+00,\n","        -3.33883675e+00,  2.10920087e+00, -6.30300020e-01,\n","         6.50420793e-02, -8.74973012e-01,  9.59024716e-01,\n","        -4.45962862e-01,  1.06394925e+00, -2.22932826e-01,\n","        -1.84315768e-02,  3.46623311e+00,  0.00000000e+00,\n","         1.89755582e+00, -1.25010380e+00, -1.10165284e+00]])"]},"metadata":{},"execution_count":272}]},{"cell_type":"markdown","source":["#####Paso 6:Evaluación del Modelo"],"metadata":{"id":"WXRRrzRK4B9H"}},{"cell_type":"markdown","source":["######1.Matrix de confusión"],"metadata":{"id":"7EOyvj69NRau"}},{"cell_type":"code","source":["from sklearn.metrics import confusion_matrix, classification_report, roc_curve, roc_auc_score, precision_recall_curve\n","#predición\n","y_preds = model.predict(X_test)\n","#classification report\n","print(classification_report(y_test, y_preds))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"XgxosFSc4EEM","outputId":"94e0ffdb-5f9a-4258-8d86-2e35c75ed705"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["              precision    recall  f1-score   support\n","\n","           0       0.65      0.56      0.60       293\n","           1       0.85      0.89      0.87       801\n","\n","    accuracy                           0.80      1094\n","   macro avg       0.75      0.72      0.73      1094\n","weighted avg       0.79      0.80      0.80      1094\n","\n"]}]},{"cell_type":"markdown","source":["######2.Curva ROC"],"metadata":{"id":"4-zCab_DNWB-"}},{"cell_type":"code","source":["#valores para la curva ROC\n","y_hat_test_proba = model.predict_proba(X_test)\n","y_hat_test_proba = y_hat_test_proba[:][: , 1]\n","y_test_temp = y_test.copy()\n","y_test_temp.reset_index(drop = True, inplace = True)\n","y_test_proba = pd.concat([y_test_temp, pd.DataFrame(y_hat_test_proba), pd.DataFrame(y_preds)], axis = 1)\n","y_test_proba.columns = ['y_test_class_actual', 'y_hat_test_proba', 'y_hat_test']\n","y_test_proba.index = X_test.index\n","y_test_proba.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"F6exdCgu4cxb","outputId":"685a5b6c-fbaa-4b64-bfe6-43ca27f7df13"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["       y_test_class_actual  y_hat_test_proba  y_hat_test\n","9573                     1          0.979510           1\n","8100                     1          0.534464           1\n","8971                     1          0.998851           1\n","10708                    1          0.563673           1\n","8944                     1          0.996951           1"],"text/html":["\n","  <div id=\"df-bad9b458-9e7a-4f61-b1ae-4cccad29e99e\" 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 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>y_test_class_actual</th>\n","      <th>y_hat_test_proba</th>\n","      <th>y_hat_test</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>9573</th>\n","      <td>1</td>\n","      <td>0.979510</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>8100</th>\n","      <td>1</td>\n","      <td>0.534464</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>8971</th>\n","      <td>1</td>\n","      <td>0.998851</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>10708</th>\n","      <td>1</td>\n","      <td>0.563673</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>8944</th>\n","      <td>1</td>\n","      <td>0.996951</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bad9b458-9e7a-4f61-b1ae-4cccad29e99e')\"\n","            title=\"Convert this dataframe to an interactive table.\"\n","            style=\"display:none;\">\n","\n","  <svg 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Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["######3.AUROC y Gini"],"metadata":{"id":"nLNXZivhNbrt"}},{"cell_type":"code","source":["\n","#Area under receiver operating charateristic cure\n","AUROC = roc_auc_score(y_test_proba['y_test_class_actual'], y_test_proba['y_hat_test_proba'])\n","AUROC"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"l7c4DRbZ4o1d","outputId":"5cd3d044-4940-4d20-d0f7-de887a5e1be3"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.8164559658788288"]},"metadata":{},"execution_count":267}]},{"cell_type":"code","source":["Gini = AUROC * 2 - 1\n","Gini"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"nk8J1PL-4ucJ","outputId":"c84173c1-539a-4df7-a0d8-4d41bed4276c"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["0.6329119317576577"]},"metadata":{},"execution_count":268}]},{"cell_type":"markdown","source":["######4.Curva KS"],"metadata":{"id":"OxEFrf6uNut8"}},{"cell_type":"code","source":["# calcualting ks statistic\n","actual_predicted_probs_df = y_test_proba.sort_values('y_hat_test_proba')\n","actual_predicted_probs_df = actual_predicted_probs_df.reset_index()\n","actual_predicted_probs_df['cum_n_pop'] = actual_predicted_probs_df.index +1\n","actual_predicted_probs_df['cum_good'] = actual_predicted_probs_df['y_test_class_actual'].cumsum()\n","actual_predicted_probs_df['cum_bad'] = actual_predicted_probs_df['cum_n_pop'] - actual_predicted_probs_df['y_test_class_actual'].cumsum()\n","actual_predicted_probs_df['cum_n_%'] = actual_predicted_probs_df['cum_n_pop']/(actual_predicted_probs_df.shape[0])\n","actual_predicted_probs_df['cum_good_%'] = actual_predicted_probs_df['cum_good']/actual_predicted_probs_df['y_test_class_actual'].sum()\n","actual_predicted_probs_df['cum_bad_%'] = actual_predicted_probs_df['cum_bad']/ (actual_predicted_probs_df.shape[0]-actual_predicted_probs_df['y_test_class_actual'].sum())\n","plt.plot(actual_predicted_probs_df['cum_n_%'], actual_predicted_probs_df['cum_bad_%'])\n","plt.plot(actual_predicted_probs_df['cum_n_%'], actual_predicted_probs_df['cum_n_%'], linestyle='--', c='k')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":448},"id":"D_ADHbkn44cw","outputId":"ef9b0add-5bbe-442c-8574-d00262cff11c"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[<matplotlib.lines.Line2D at 0x7b607ba91180>]"]},"metadata":{},"execution_count":269},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["plt.plot(actual_predicted_probs_df['y_hat_test_proba'], actual_predicted_probs_df['cum_bad_%'], c='r')\n","plt.plot(actual_predicted_probs_df['y_hat_test_proba'], actual_predicted_probs_df['cum_good_%'], c='g')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":448},"id":"fnNeLsq35ABJ","outputId":"8fae9696-ea44-4355-8e08-955be51869ad"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[<matplotlib.lines.Line2D at 0x7b607b905450>]"]},"metadata":{},"execution_count":270},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["---\n","###Parte 6: Análisis de los tiempos de conclusión de los proyectos - Proximas etapas"],"metadata":{"id":"7fpLr7RLmMfN"}},{"cell_type":"code","source":["data.sample(2)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":196},"id":"Zo6fNO-Ej53l","outputId":"085581a1-b3f9-47cb-b2df-640ae62a7044"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["       ID PHR Postula Con Proyecto Desarrollado  Año Programa  \\\n","6646  LA10854                                Sí          2022   \n","6878  LA11062                                Sí          2023   \n","\n","     Fecha Publicación DO Región Ejecución Provincia Tipo de Expediente  \\\n","6646           2022-03-14        Araucanía   Malleco          Colectivo   \n","6878           2022-05-05        Araucanía    Cautín          Colectivo   \n","\n","     Tipología Madre Tipo de Intervención N° Expediente  ...  etapa_5  \\\n","6646             CSR       Vivienda Nueva         32579  ...      NaN   \n","6878             CSR       Vivienda Nueva         32609  ...      NaN   \n","\n","      duracao_5  etapa_6  duracao_6  etapa_7  duracao_7  Fecha_final  \\\n","6646        NaN      NaN        NaN      NaN        NaN   2023-08-31   \n","6878        NaN      NaN        NaN      NaN        NaN   2023-08-31   \n","\n","      Duracion_total target censura  \n","6646        1.465753      1       1  \n","6878        1.323288      1       1  \n","\n","[2 rows x 60 columns]"],"text/html":["\n","  <div id=\"df-8abbc26e-9a3e-4164-a41f-c97f893ae99c\" 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 th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>ID PHR</th>\n","      <th>Postula Con Proyecto Desarrollado</th>\n","      <th>Año Programa</th>\n","      <th>Fecha Publicación DO</th>\n","      <th>Región Ejecución</th>\n","      <th>Provincia</th>\n","      <th>Tipo de Expediente</th>\n","      <th>Tipología Madre</th>\n","      <th>Tipo de Intervención</th>\n","      <th>N° Expediente</th>\n","      <th>...</th>\n","      <th>etapa_5</th>\n","      <th>duracao_5</th>\n","      <th>etapa_6</th>\n","      <th>duracao_6</th>\n","      <th>etapa_7</th>\n","      <th>duracao_7</th>\n","      <th>Fecha_final</th>\n","      <th>Duracion_total</th>\n","      <th>target</th>\n","      <th>censura</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>6646</th>\n","      <td>LA10854</td>\n","      <td>Sí</td>\n","      <td>2022</td>\n","      <td>2022-03-14</td>\n","      <td>Araucanía</td>\n","      <td>Malleco</td>\n","      <td>Colectivo</td>\n","      <td>CSR</td>\n","      <td>Vivienda Nueva</td>\n","      <td>32579</td>\n","      <td>...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>2023-08-31</td>\n","      <td>1.465753</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>6878</th>\n","      <td>LA11062</td>\n","      <td>Sí</td>\n","      <td>2023</td>\n","      <td>2022-05-05</td>\n","      <td>Araucanía</td>\n","      <td>Cautín</td>\n","      <td>Colectivo</td>\n","      <td>CSR</td>\n","      <td>Vivienda Nueva</td>\n","      <td>32609</td>\n","      <td>...</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>NaN</td>\n","      <td>2023-08-31</td>\n","      <td>1.323288</td>\n","      <td>1</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>2 rows × 60 columns</p>\n","</div>\n","    <div class=\"colab-df-buttons\">\n","\n","  <div class=\"colab-df-container\">\n","    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8abbc26e-9a3e-4164-a41f-c97f893ae99c')\"\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 -960 960 960\">\n","    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n","  </svg>\n","    </button>\n","\n","  <style>\n","    .colab-df-container {\n","      display:flex;\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","    .colab-df-buttons div {\n","      margin-bottom: 4px;\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-8abbc26e-9a3e-4164-a41f-c97f893ae99c button.colab-df-convert');\n","      buttonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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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","\n","\n","<div id=\"df-f8274db1-ba31-4417-9cc3-7c39ef15cccd\">\n","  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f8274db1-ba31-4417-9cc3-7c39ef15cccd')\"\n","            title=\"Suggest charts\"\n","            style=\"display:none;\">\n","\n","<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","     width=\"24px\">\n","    <g>\n","        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n","    </g>\n","</svg>\n","  </button>\n","\n","<style>\n","  .colab-df-quickchart {\n","      --bg-color: #E8F0FE;\n","      --fill-color: #1967D2;\n","      --hover-bg-color: #E2EBFA;\n","      --hover-fill-color: #174EA6;\n","      --disabled-fill-color: #AAA;\n","      --disabled-bg-color: #DDD;\n","  }\n","\n","  [theme=dark] .colab-df-quickchart {\n","      --bg-color: #3B4455;\n","      --fill-color: #D2E3FC;\n","      --hover-bg-color: #434B5C;\n","      --hover-fill-color: #FFFFFF;\n","      --disabled-bg-color: #3B4455;\n","      --disabled-fill-color: #666;\n","  }\n","\n","  .colab-df-quickchart {\n","    background-color: var(--bg-color);\n","    border: none;\n","    border-radius: 50%;\n","    cursor: pointer;\n","    display: none;\n","    fill: var(--fill-color);\n","    height: 32px;\n","    padding: 0;\n","    width: 32px;\n","  }\n","\n","  .colab-df-quickchart:hover {\n","    background-color: var(--hover-bg-color);\n","    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n","    fill: var(--button-hover-fill-color);\n","  }\n","\n","  .colab-df-quickchart-complete:disabled,\n","  .colab-df-quickchart-complete:disabled:hover {\n","    background-color: var(--disabled-bg-color);\n","    fill: var(--disabled-fill-color);\n","    box-shadow: none;\n","  }\n","\n","  .colab-df-spinner {\n","    border: 2px solid var(--fill-color);\n","    border-color: transparent;\n","    border-bottom-color: var(--fill-color);\n","    animation:\n","      spin 1s steps(1) infinite;\n","  }\n","\n","  @keyframes spin {\n","    0% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","      border-left-color: var(--fill-color);\n","    }\n","    20% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    30% {\n","      border-color: transparent;\n","      border-left-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","      border-right-color: var(--fill-color);\n","    }\n","    40% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-top-color: var(--fill-color);\n","    }\n","    60% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","    }\n","    80% {\n","      border-color: transparent;\n","      border-right-color: var(--fill-color);\n","      border-bottom-color: var(--fill-color);\n","    }\n","    90% {\n","      border-color: transparent;\n","      border-bottom-color: var(--fill-color);\n","    }\n","  }\n","</style>\n","\n","  <script>\n","    async function quickchart(key) {\n","      const quickchartButtonEl =\n","        document.querySelector('#' + key + ' button');\n","      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n","      quickchartButtonEl.classList.add('colab-df-spinner');\n","      try {\n","        const charts = await google.colab.kernel.invokeFunction(\n","            'suggestCharts', [key], {});\n","      } catch (error) {\n","        console.error('Error during call to suggestCharts:', error);\n","      }\n","      quickchartButtonEl.classList.remove('colab-df-spinner');\n","      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n","    }\n","    (() => {\n","      let quickchartButtonEl =\n","        document.querySelector('#df-f8274db1-ba31-4417-9cc3-7c39ef15cccd button');\n","      quickchartButtonEl.style.display =\n","        google.colab.kernel.accessAllowed ? 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