LibPandas.ipynb

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  "metadata": {
    "colab": {
      "name": "LibPandas.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "TFoTOhuAt40s"
      },
      "source": [
        "# Importando a biblioteca pandas as pd\n",
        "import pandas as pd"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "RiTraJf5uAsn",
        "outputId": "6a3e1c94-b071-4ea1-dfbd-ca3c38c113fb"
      },
      "source": [
        "# Criando a variavel que armazena o conteudo do arquivo e mostra na tela.\n",
        "df = pd.read_csv('/content/drive/MyDrive/Pandas/datasets/Gapminder.csv',sep=';')\n",
        "df"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>continent</th>\n",
              "      <th>year</th>\n",
              "      <th>lifeExp</th>\n",
              "      <th>pop</th>\n",
              "      <th>gdpPercap</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1952</td>\n",
              "      <td>28.801</td>\n",
              "      <td>8425333</td>\n",
              "      <td>779.445314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1957</td>\n",
              "      <td>30.332</td>\n",
              "      <td>9240934</td>\n",
              "      <td>820.853030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1962</td>\n",
              "      <td>31.997</td>\n",
              "      <td>10267083</td>\n",
              "      <td>853.100710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1967</td>\n",
              "      <td>34.020</td>\n",
              "      <td>11537966</td>\n",
              "      <td>836.197138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1972</td>\n",
              "      <td>36.088</td>\n",
              "      <td>13079460</td>\n",
              "      <td>739.981106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3307</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1987</td>\n",
              "      <td>62.351</td>\n",
              "      <td>9216418</td>\n",
              "      <td>706.157306</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3308</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1992</td>\n",
              "      <td>60.377</td>\n",
              "      <td>10704340</td>\n",
              "      <td>693.420786</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3309</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1997</td>\n",
              "      <td>46.809</td>\n",
              "      <td>11404948</td>\n",
              "      <td>792.449960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3310</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>2002</td>\n",
              "      <td>39.989</td>\n",
              "      <td>11926563</td>\n",
              "      <td>672.038623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3311</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>2007</td>\n",
              "      <td>43.487</td>\n",
              "      <td>12311143</td>\n",
              "      <td>469.709298</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3312 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          country continent  year  lifeExp       pop   gdpPercap\n",
              "0     Afghanistan      Asia  1952   28.801   8425333  779.445314\n",
              "1     Afghanistan      Asia  1957   30.332   9240934  820.853030\n",
              "2     Afghanistan      Asia  1962   31.997  10267083  853.100710\n",
              "3     Afghanistan      Asia  1967   34.020  11537966  836.197138\n",
              "4     Afghanistan      Asia  1972   36.088  13079460  739.981106\n",
              "...           ...       ...   ...      ...       ...         ...\n",
              "3307     Zimbabwe    Africa  1987   62.351   9216418  706.157306\n",
              "3308     Zimbabwe    Africa  1992   60.377  10704340  693.420786\n",
              "3309     Zimbabwe    Africa  1997   46.809  11404948  792.449960\n",
              "3310     Zimbabwe    Africa  2002   39.989  11926563  672.038623\n",
              "3311     Zimbabwe    Africa  2007   43.487  12311143  469.709298\n",
              "\n",
              "[3312 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "fuytAYc8u7Rx",
        "outputId": "bf1e5de2-9fe9-497f-fbc7-3572e85ff403"
      },
      "source": [
        "#Mostra as 5 primeiras linhas(ROW)\n",
        "df.head()"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>country</th>\n",
              "      <th>continent</th>\n",
              "      <th>year</th>\n",
              "      <th>lifeExp</th>\n",
              "      <th>pop</th>\n",
              "      <th>gdpPercap</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1952</td>\n",
              "      <td>28.801</td>\n",
              "      <td>8425333</td>\n",
              "      <td>779.445314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1957</td>\n",
              "      <td>30.332</td>\n",
              "      <td>9240934</td>\n",
              "      <td>820.853030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1962</td>\n",
              "      <td>31.997</td>\n",
              "      <td>10267083</td>\n",
              "      <td>853.100710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1967</td>\n",
              "      <td>34.020</td>\n",
              "      <td>11537966</td>\n",
              "      <td>836.197138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1972</td>\n",
              "      <td>36.088</td>\n",
              "      <td>13079460</td>\n",
              "      <td>739.981106</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       country continent  year  lifeExp       pop   gdpPercap\n",
              "0  Afghanistan      Asia  1952   28.801   8425333  779.445314\n",
              "1  Afghanistan      Asia  1957   30.332   9240934  820.853030\n",
              "2  Afghanistan      Asia  1962   31.997  10267083  853.100710\n",
              "3  Afghanistan      Asia  1967   34.020  11537966  836.197138\n",
              "4  Afghanistan      Asia  1972   36.088  13079460  739.981106"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hFTvml2rvEMK"
      },
      "source": [
        "#Renomeando as colunas\n",
        "df = df.rename(columns={'country':'Pais','continent':'Continente','year':'Ano','lifeExp':'Expectativa de Vida','pop':'populacao','gdpPercap':'PIB'})"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "NjjMttlcv3p8",
        "outputId": "3b8c8cac-1152-40bd-ca69-e15055b07273"
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pais</th>\n",
              "      <th>Continente</th>\n",
              "      <th>Ano</th>\n",
              "      <th>Expectativa de Vida</th>\n",
              "      <th>populacao</th>\n",
              "      <th>PIB</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1952</td>\n",
              "      <td>28.801</td>\n",
              "      <td>8425333</td>\n",
              "      <td>779.445314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1957</td>\n",
              "      <td>30.332</td>\n",
              "      <td>9240934</td>\n",
              "      <td>820.853030</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1962</td>\n",
              "      <td>31.997</td>\n",
              "      <td>10267083</td>\n",
              "      <td>853.100710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1967</td>\n",
              "      <td>34.020</td>\n",
              "      <td>11537966</td>\n",
              "      <td>836.197138</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Afghanistan</td>\n",
              "      <td>Asia</td>\n",
              "      <td>1972</td>\n",
              "      <td>36.088</td>\n",
              "      <td>13079460</td>\n",
              "      <td>739.981106</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Pais Continente   Ano  Expectativa de Vida  populacao         PIB\n",
              "0  Afghanistan       Asia  1952               28.801    8425333  779.445314\n",
              "1  Afghanistan       Asia  1957               30.332    9240934  820.853030\n",
              "2  Afghanistan       Asia  1962               31.997   10267083  853.100710\n",
              "3  Afghanistan       Asia  1967               34.020   11537966  836.197138\n",
              "4  Afghanistan       Asia  1972               36.088   13079460  739.981106"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2vyxr5FBwAlC",
        "outputId": "fab2e1f4-625c-4b1b-f8a4-b45741bd6f26"
      },
      "source": [
        "# Exibe total de Linhas e Colunas\n",
        "df.shape"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(3312, 6)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9U-VZyohwM6r",
        "outputId": "2fcf05f5-2fda-40f9-c0ce-bb9c709c3965"
      },
      "source": [
        "# Exibe os nomes das Colunas\n",
        "df.columns"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Pais', 'Continente', 'Ano', 'Expectativa de Vida', 'populacao', 'PIB'], dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IQ8c9ITQwVTk",
        "outputId": "03b3334e-65d9-4179-8062-20e8601a6469"
      },
      "source": [
        "# Exibe o tipo de dado de cada Coluna\n",
        "df.dtypes"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Pais                    object\n",
              "Continente              object\n",
              "Ano                      int64\n",
              "Expectativa de Vida    float64\n",
              "populacao                int64\n",
              "PIB                    float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "KTea5K2GwbuN",
        "outputId": "12f9b5a3-0646-4f1a-dd24-860a127e2cee"
      },
      "source": [
        "#Exibe as ultimas linhas da tabela\n",
        "df.tail()"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pais</th>\n",
              "      <th>Continente</th>\n",
              "      <th>Ano</th>\n",
              "      <th>Expectativa de Vida</th>\n",
              "      <th>populacao</th>\n",
              "      <th>PIB</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>3307</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1987</td>\n",
              "      <td>62.351</td>\n",
              "      <td>9216418</td>\n",
              "      <td>706.157306</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3308</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1992</td>\n",
              "      <td>60.377</td>\n",
              "      <td>10704340</td>\n",
              "      <td>693.420786</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3309</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>1997</td>\n",
              "      <td>46.809</td>\n",
              "      <td>11404948</td>\n",
              "      <td>792.449960</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3310</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>2002</td>\n",
              "      <td>39.989</td>\n",
              "      <td>11926563</td>\n",
              "      <td>672.038623</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3311</th>\n",
              "      <td>Zimbabwe</td>\n",
              "      <td>Africa</td>\n",
              "      <td>2007</td>\n",
              "      <td>43.487</td>\n",
              "      <td>12311143</td>\n",
              "      <td>469.709298</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Pais Continente   Ano  Expectativa de Vida  populacao         PIB\n",
              "3307  Zimbabwe     Africa  1987               62.351    9216418  706.157306\n",
              "3308  Zimbabwe     Africa  1992               60.377   10704340  693.420786\n",
              "3309  Zimbabwe     Africa  1997               46.809   11404948  792.449960\n",
              "3310  Zimbabwe     Africa  2002               39.989   11926563  672.038623\n",
              "3311  Zimbabwe     Africa  2007               43.487   12311143  469.709298"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "Bk3oMHYkwosn",
        "outputId": "9d50dbcd-a8c9-4efa-c675-ca8580862403"
      },
      "source": [
        "# informa alguns dados estatisticos sobre a tabela\n",
        "df.describe()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Ano</th>\n",
              "      <th>Expectativa de Vida</th>\n",
              "      <th>populacao</th>\n",
              "      <th>PIB</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>3312.000000</td>\n",
              "      <td>3312.000000</td>\n",
              "      <td>3.312000e+03</td>\n",
              "      <td>3312.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1980.301630</td>\n",
              "      <td>65.246871</td>\n",
              "      <td>3.161489e+07</td>\n",
              "      <td>11317.115805</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>16.927294</td>\n",
              "      <td>11.768412</td>\n",
              "      <td>1.041193e+08</td>\n",
              "      <td>11369.142739</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1950.000000</td>\n",
              "      <td>23.599000</td>\n",
              "      <td>5.941200e+04</td>\n",
              "      <td>241.165877</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1967.000000</td>\n",
              "      <td>58.337500</td>\n",
              "      <td>2.678572e+06</td>\n",
              "      <td>2514.625266</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1982.000000</td>\n",
              "      <td>69.610000</td>\n",
              "      <td>7.557218e+06</td>\n",
              "      <td>7838.505123</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1996.000000</td>\n",
              "      <td>73.657750</td>\n",
              "      <td>1.958522e+07</td>\n",
              "      <td>17357.879170</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2007.000000</td>\n",
              "      <td>82.670000</td>\n",
              "      <td>1.318683e+09</td>\n",
              "      <td>113523.132900</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               Ano  Expectativa de Vida     populacao            PIB\n",
              "count  3312.000000          3312.000000  3.312000e+03    3312.000000\n",
              "mean   1980.301630            65.246871  3.161489e+07   11317.115805\n",
              "std      16.927294            11.768412  1.041193e+08   11369.142739\n",
              "min    1950.000000            23.599000  5.941200e+04     241.165877\n",
              "25%    1967.000000            58.337500  2.678572e+06    2514.625266\n",
              "50%    1982.000000            69.610000  7.557218e+06    7838.505123\n",
              "75%    1996.000000            73.657750  1.958522e+07   17357.879170\n",
              "max    2007.000000            82.670000  1.318683e+09  113523.132900"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zq5xEqqLxAbm",
        "outputId": "20c1e7f7-ceec-4589-b493-e767d8e81ba7"
      },
      "source": [
        "#Retorna valores unicos e não repetidos.\n",
        "df['Continente'].unique()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Asia', 'Europe', 'Africa', 'Americas', nan, 'FSU', 'Oceania'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "2LOes551xTHn",
        "outputId": "88c58f6f-458b-4792-87cd-bde5cbf0ec84"
      },
      "source": [
        "# Filtrando Dados na tabela\n",
        "Oceania = df.loc[df['Continente'] == 'Oceania']\n",
        "Oceania.head()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Pais</th>\n",
              "      <th>Continente</th>\n",
              "      <th>Ano</th>\n",
              "      <th>Expectativa de Vida</th>\n",
              "      <th>populacao</th>\n",
              "      <th>PIB</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>975</th>\n",
              "      <td>Fiji</td>\n",
              "      <td>Oceania</td>\n",
              "      <td>1962</td>\n",
              "      <td>56.494</td>\n",
              "      <td>421869</td>\n",
              "      <td>2039.393277</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>976</th>\n",
              "      <td>Fiji</td>\n",
              "      <td>Oceania</td>\n",
              "      <td>1967</td>\n",
              "      <td>58.607</td>\n",
              "      <td>485000</td>\n",
              "      <td>2170.073285</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>977</th>\n",
              "      <td>Fiji</td>\n",
              "      <td>Oceania</td>\n",
              "      <td>1972</td>\n",
              "      <td>60.642</td>\n",
              "      <td>544000</td>\n",
              "      <td>2797.759484</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>978</th>\n",
              "      <td>Fiji</td>\n",
              "      <td>Oceania</td>\n",
              "      <td>1977</td>\n",
              "      <td>62.669</td>\n",
              "      <td>599339</td>\n",
              "      <td>3182.569600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>979</th>\n",
              "      <td>Fiji</td>\n",
              "      <td>Oceania</td>\n",
              "      <td>1982</td>\n",
              "      <td>64.683</td>\n",
              "      <td>658906</td>\n",
              "      <td>3209.257468</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "     Pais Continente   Ano  Expectativa de Vida  populacao          PIB\n",
              "975  Fiji    Oceania  1962               56.494     421869  2039.393277\n",
              "976  Fiji    Oceania  1967               58.607     485000  2170.073285\n",
              "977  Fiji    Oceania  1972               60.642     544000  2797.759484\n",
              "978  Fiji    Oceania  1977               62.669     599339  3182.569600\n",
              "979  Fiji    Oceania  1982               64.683     658906  3209.257468"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aKc3h8hYx5Hz",
        "outputId": "fd9949be-555c-497c-dd3b-b0d8cded519a"
      },
      "source": [
        "# Agrupando em ordem de continente a quantidade de paises em cada um.\n",
        "df.groupby('Continente')['Pais'].nunique()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Continente\n",
              "Africa      51\n",
              "Americas    25\n",
              "Asia        41\n",
              "Europe      35\n",
              "FSU          6\n",
              "Oceania      3\n",
              "Name: Pais, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D30BidBMyhFK",
        "outputId": "62074e98-99bf-4563-82e8-01f5bd15ded9"
      },
      "source": [
        "# Agrupando pelo ANO e mostrando a média de Expectativa de vida.\n",
        "df.groupby('Ano')['Expectativa de Vida'].mean()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Ano\n",
              "1950    62.002568\n",
              "1951    65.904167\n",
              "1952    49.206867\n",
              "1953    66.674563\n",
              "1954    67.459817\n",
              "1955    67.806757\n",
              "1956    67.950637\n",
              "1957    51.614590\n",
              "1958    68.815936\n",
              "1959    68.226579\n",
              "1960    68.470837\n",
              "1961    68.862480\n",
              "1962    54.035234\n",
              "1963    69.595735\n",
              "1964    70.063105\n",
              "1965    70.259881\n",
              "1966    70.447526\n",
              "1967    56.263629\n",
              "1968    70.689081\n",
              "1969    70.653896\n",
              "1970    70.961141\n",
              "1971    71.103976\n",
              "1972    58.474481\n",
              "1973    71.500338\n",
              "1974    71.778504\n",
              "1975    71.939218\n",
              "1976    72.158050\n",
              "1977    60.429090\n",
              "1978    72.717567\n",
              "1979    73.018717\n",
              "1980    73.064524\n",
              "1981    73.337399\n",
              "1982    62.365871\n",
              "1983    73.787778\n",
              "1984    74.100741\n",
              "1985    74.112222\n",
              "1986    74.452222\n",
              "1987    63.984860\n",
              "1988    74.760000\n",
              "1989    74.924444\n",
              "1990    74.283437\n",
              "1991    74.374848\n",
              "1992    65.008443\n",
              "1993    74.324545\n",
              "1994    74.456667\n",
              "1995    74.552727\n",
              "1996    75.029394\n",
              "1997    65.873799\n",
              "1998    75.569697\n",
              "1999    75.703636\n",
              "2000    76.026364\n",
              "2001    76.257879\n",
              "2002    66.835695\n",
              "2003    76.586667\n",
              "2004    76.921563\n",
              "2005    76.718667\n",
              "2006    77.887778\n",
              "2007    67.868557\n",
              "Name: Expectativa de Vida, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XOlc0s9NzUAV",
        "outputId": "4a601920-6660-46da-ee95-3baf02785d96"
      },
      "source": [
        "# Média do PIB\n",
        "df['PIB'].mean()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "11317.115804696637"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9Hr64bt-zn1t",
        "outputId": "48d6e153-87c0-48f9-89e6-e059a749c5fb"
      },
      "source": [
        "# Soma do PIB\n",
        "df['PIB'].sum()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "37482287.5451553"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 23
        }
      ]
    }
  ]
}