Aula07_Exercício_ExplorandoVariáveisQuantitativas_LIFE.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "# Exercício: <p> <center> Análise Exploratória - Variáveis Quantitativas\n",
    "___\n",
    "\n",
    "## Aula 07"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "<div id=\"indice\"></div>\n",
    "\n",
    "## Índice\n",
    "\n",
    "- [Expectativa de vida](#life)\n",
    "    - [Exercício 1](#ex1)\n",
    "    - [Exercício 2](#ex2)\n",
    "    - [Exercício 3](#ex3)\n",
    "    - [Exercício 4](#ex4)\n",
    "    - [Exercício 5](#ex5)    \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "\n",
    "from numpy import arange\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Esperamos trabalhar no diretório\n",
      "c:\\Users\\ribei\\OneDrive\\Área de Trabalho\\cdados\\cdados\n"
     ]
    }
   ],
   "source": [
    "print('Esperamos trabalhar no diretório')\n",
    "print(os.getcwd())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "<div id=\"life\"></div>\n",
    "\n",
    "# Expectativa de vida\n",
    "\n",
    "<img src=\"expectativavida.png\" height=\"200\">\n",
    "\n",
    "\n",
    "Fonte: extraído da internet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "O Banco Mundial (http://data.worldbank.org/brazilian-portuguese) disponibiliza bases de dados estatísticos para um pouco mais de 200 países do mundo desde o ano 1800, as quais consideram uma seleção abrangente de indicadores econômicos, sociais e ambientais. Um desses indicadores é a expectativa de vida (em anos) de cada país.\n",
    "\n",
    "O arquivo `Life.xlsx` contém a expectativa de vida de vários países para os anos 1800, 1926 e 2000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pais</th>\n",
       "      <th>L1800</th>\n",
       "      <th>L1926</th>\n",
       "      <th>L2000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>28.2110</td>\n",
       "      <td>26.919920</td>\n",
       "      <td>51.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>35.4000</td>\n",
       "      <td>35.400000</td>\n",
       "      <td>74.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>28.8224</td>\n",
       "      <td>30.968000</td>\n",
       "      <td>73.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Angola</td>\n",
       "      <td>26.9800</td>\n",
       "      <td>26.980000</td>\n",
       "      <td>52.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Antigua and Barbuda</td>\n",
       "      <td>33.5360</td>\n",
       "      <td>37.673931</td>\n",
       "      <td>73.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Pais    L1800      L1926  L2000\n",
       "0          Afghanistan  28.2110  26.919920   51.0\n",
       "1              Albania  35.4000  35.400000   74.2\n",
       "2              Algeria  28.8224  30.968000   73.2\n",
       "3               Angola  26.9800  26.980000   52.6\n",
       "4  Antigua and Barbuda  33.5360  37.673931   73.9"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dados = pd.read_excel('Life.xlsx')\n",
    "dados.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volta ao Índice](#indice)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "<div id=\"ex1\"></div>\n",
    "\n",
    "### EXERCÍCIO 1\n",
    "\n",
    "Calcule algumas medidas resumo para expectativa de vida para cada ano e interprete.\n",
    "\n",
    "Explore a evolução dessa medida ao longo do tempo usando essas informações numéricas."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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>L1800</th>\n",
       "      <th>L1926</th>\n",
       "      <th>L2000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>201.000000</td>\n",
       "      <td>201.000000</td>\n",
       "      <td>201.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>31.485800</td>\n",
       "      <td>36.353496</td>\n",
       "      <td>68.012856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.763625</td>\n",
       "      <td>9.590987</td>\n",
       "      <td>9.211812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>23.387000</td>\n",
       "      <td>23.387000</td>\n",
       "      <td>45.700000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>29.000000</td>\n",
       "      <td>30.400000</td>\n",
       "      <td>61.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>31.800000</td>\n",
       "      <td>32.800000</td>\n",
       "      <td>71.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>33.900000</td>\n",
       "      <td>39.360000</td>\n",
       "      <td>75.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>42.845599</td>\n",
       "      <td>63.260000</td>\n",
       "      <td>81.100000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            L1800       L1926       L2000\n",
       "count  201.000000  201.000000  201.000000\n",
       "mean    31.485800   36.353496   68.012856\n",
       "std      3.763625    9.590987    9.211812\n",
       "min     23.387000   23.387000   45.700000\n",
       "25%     29.000000   30.400000   61.400000\n",
       "50%     31.800000   32.800000   71.200000\n",
       "75%     33.900000   39.360000   75.000000\n",
       "max     42.845599   63.260000   81.100000"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Escreva seu código aqui\n",
    "dados.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volta ao Índice](#indice)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "<div id=\"ex2\"></div>\n",
    "\n",
    "### EXERCÍCIO 2\n",
    "\n",
    "Construa um histograma para cada ano e interprete os gráficos. Compare-os.\n",
    "\n",
    "IMPORTANTE: lembre-se que o intuito aqui não é só saber como era a expectativa de vida em um particular ano, mas TAMBÉM compará-las ao longo tempo. Assim sendo, faça histogramas que permita que essa comparação também seja feita.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Escreva seu código aqui\n",
    "plt.figure(figsize=(20,5))\n",
    "plt.subplot(131)\n",
    "# plt.hist(dados.L1800, density=True, bins=8, edgecolor=\"black\")\n",
    "plt.hist(dados.L1800, density=True, bins=arange(22, 83, 2), edgecolor=\"black\")\n",
    "plt.ylim(0,0.12)\n",
    "plt.xlim(20, 90)\n",
    "\n",
    "plt.subplot(132)\n",
    "# plt.hist(dados.L1926, density=True, bins=8, edgecolor=\"black\")\n",
    "plt.hist(dados.L1926, density=True, bins=arange(22, 83, 2), edgecolor=\"black\")\n",
    "plt.ylim(0,0.12)\n",
    "plt.xlim(20, 90)\n",
    "\n",
    "plt.subplot(133)\n",
    "# plt.hist(dados.L2000, density=True, bins=8, edgecolor=\"black\")\n",
    "plt.hist(dados.L2000, density=True, bins=arange(22, 83, 2), edgecolor=\"black\")\n",
    "plt.ylim(0,0.12)\n",
    "plt.xlim(20, 90)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volta ao Índice](#indice)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "<div id=\"ex3\"></div>\n",
    "\n",
    "### EXERCÍCIO 3\n",
    "\n",
    "De acordo com o formato de um histograma, é possível classificar a distribuição dos dados como sendo: simétrica; assimétrica a direita (ou positiva); e assimétrica a esquerda (ou negativa). Veja figura a seguir (fonte: extraída da internet) \n",
    "![AssimSim](AssimSim.jpg)\n",
    "\n",
    "\n",
    "Observe novamente o formato de cada um dos três histogramas construídos para expectativa de vida no [Exercício 2](#ex2).\n",
    "\n",
    "Para cada ano, classifique os histogramas como sendo simétrico, assimétrico a direta ou assimétrico a esquerda. \n",
    "Argumente claramente o motivo de sua classificação. \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Coloque sua interpretação aqui.\n",
    "# 1 é simétrico, 2 à direita e 3 à esquerda"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volta ao Índice](#indice)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "<div id=\"ex4\"></div>\n",
    "\n",
    "### EXERCÍCIO 4\n",
    "\n",
    "Observe novamente os valores de média e mediana calculados no [Exercício 1](#ex1).\n",
    "\n",
    "Para cada um dos três anos, ordene os valores dessas medidas de posição.\n",
    "Verifique se ordem dessas medidas de posição é um mero acaso ou pode ser consequência do formato dos dados. Argumente claramente sua resposta."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Escreva seu código aqui"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volta ao Índice](#indice)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "<div id=\"ex5\"></div>\n",
    "\n",
    "### EXERCÍCIO 5\n",
    "\n",
    "Faça um boxplot da expectativa de vida de cada ano, todos na mesma janela gráfica.\n",
    "\n",
    "Interprete-o em termos do problema. As conclusões obtidas com o histograma se verificam no boxplot? Justifique sua resposta.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Escreva seu código aqui"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volta ao Índice](#indice)"
   ]
  }
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