fake_news_code_d.ipynb

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    "colab": {
      "name": "fake news code_d.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "UzRteWfLyDwf"
      },
      "source": [
        "# This Python 3 environment comes with many helpful analytics libraries installed\n",
        "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
        "# For example, here's several helpful packages to load\n",
        "\n",
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
        "\n",
        "# Input data files are available in the read-only \"../input/\" directory\n",
        "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
        "\n"
      ],
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wdEW4Ow5bSpr"
      },
      "source": [
        "# Modelling Algorithms\n",
        "from sklearn.naive_bayes import MultinomialNB\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.linear_model import PassiveAggressiveClassifier\n",
        "\n",
        "# Modelling Helpers\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.feature_extraction.text import CountVectorizer\n",
        "from sklearn import metrics\n",
        "\n",
        "# Computations\n",
        "import itertools\n",
        "\n",
        "# Visualization\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PP6IetIfv7pv"
      },
      "source": [
        "test  = pd.read_csv (\"test.csv\")\n",
        "submit  = pd.read_csv (\"submit.csv\")"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YBLqrTSKxEVg"
      },
      "source": [
        "train = pd.read_csv(\"test.csv\")"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "T7lxKKMj1czM",
        "outputId": "972a64e9-abbb-49a2-8344-085fb0471018"
      },
      "source": [
        "train.head()"
      ],
      "execution_count": 39,
      "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>id</th>\n",
              "      <th>title</th>\n",
              "      <th>author</th>\n",
              "      <th>text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20800</td>\n",
              "      <td>Specter of Trump Loosens Tongues, if Not Purse...</td>\n",
              "      <td>David Streitfeld</td>\n",
              "      <td>PALO ALTO, Calif.  —   After years of scorning...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20801</td>\n",
              "      <td>Russian warships ready to strike terrorists ne...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Russian warships ready to strike terrorists ne...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20802</td>\n",
              "      <td>#NoDAPL: Native American Leaders Vow to Stay A...</td>\n",
              "      <td>Common Dreams</td>\n",
              "      <td>Videos #NoDAPL: Native American Leaders Vow to...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20803</td>\n",
              "      <td>Tim Tebow Will Attempt Another Comeback, This ...</td>\n",
              "      <td>Daniel Victor</td>\n",
              "      <td>If at first you don’t succeed, try a different...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20804</td>\n",
              "      <td>Keiser Report: Meme Wars (E995)</td>\n",
              "      <td>Truth Broadcast Network</td>\n",
              "      <td>42 mins ago 1 Views 0 Comments 0 Likes 'For th...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      id  ...                                               text\n",
              "0  20800  ...  PALO ALTO, Calif.  —   After years of scorning...\n",
              "1  20801  ...  Russian warships ready to strike terrorists ne...\n",
              "2  20802  ...  Videos #NoDAPL: Native American Leaders Vow to...\n",
              "3  20803  ...  If at first you don’t succeed, try a different...\n",
              "4  20804  ...  42 mins ago 1 Views 0 Comments 0 Likes 'For th...\n",
              "\n",
              "[5 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3U5rzwM2z6w7",
        "outputId": "89ff7b91-5fbf-47e1-d585-76af466b35cd"
      },
      "source": [
        "print(f\"Train Shape : {train.shape}\")\n",
        "print(f\"Test Shape : {test.shape}\")\n",
        "print(f\"Submit Shape : {submit.shape}\")"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Train Shape : (5200, 4)\n",
            "Test Shape : (5200, 4)\n",
            "Submit Shape : (5200, 2)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RGGMXSj0z-yA",
        "outputId": "32b26ca4-dc80-47e4-bca5-7890fdbca596"
      },
      "source": [
        "train.info()"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5200 entries, 0 to 5199\n",
            "Data columns (total 4 columns):\n",
            " #   Column  Non-Null Count  Dtype \n",
            "---  ------  --------------  ----- \n",
            " 0   id      5200 non-null   int64 \n",
            " 1   title   5078 non-null   object\n",
            " 2   author  4697 non-null   object\n",
            " 3   text    5193 non-null   object\n",
            "dtypes: int64(1), object(3)\n",
            "memory usage: 162.6+ KB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HYlIaspqz-s4",
        "outputId": "98b0b2a2-a2ad-4441-fb21-9ed9cc6322eb"
      },
      "source": [
        "train.isnull().sum()"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "id          0\n",
              "title     122\n",
              "author    503\n",
              "text        7\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vEtMre7pz6Nh",
        "outputId": "3a7ef26e-1a15-4777-af43-472167b19a50"
      },
      "source": [
        "train.dtypes.value_counts()"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "object    3\n",
              "int64     1\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NtMz6Lli0C_t"
      },
      "source": [
        "test=test.fillna(' ')\n",
        "train=train.fillna(' ')"
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5umpCfm40C86"
      },
      "source": [
        "# Create a column with all the data available\n",
        "test['total']=test['title']+' '+test['author']+' '+test['text']\n",
        "train['total']=train['title']+' '+train['author']+' '+train['text']"
      ],
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 408
        },
        "id": "wHCDs1mp0C6B",
        "outputId": "890d0b78-55d3-4545-e31b-49b246ec344b"
      },
      "source": [
        "# Have a glance at our training set\n",
        "train.info()\n",
        "train.head()"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 5200 entries, 0 to 5199\n",
            "Data columns (total 5 columns):\n",
            " #   Column  Non-Null Count  Dtype \n",
            "---  ------  --------------  ----- \n",
            " 0   id      5200 non-null   int64 \n",
            " 1   title   5200 non-null   object\n",
            " 2   author  5200 non-null   object\n",
            " 3   text    5200 non-null   object\n",
            " 4   total   5200 non-null   object\n",
            "dtypes: int64(1), object(4)\n",
            "memory usage: 203.2+ KB\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "      <th>id</th>\n",
              "      <th>title</th>\n",
              "      <th>author</th>\n",
              "      <th>text</th>\n",
              "      <th>total</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>20800</td>\n",
              "      <td>Specter of Trump Loosens Tongues, if Not Purse...</td>\n",
              "      <td>David Streitfeld</td>\n",
              "      <td>PALO ALTO, Calif.  —   After years of scorning...</td>\n",
              "      <td>Specter of Trump Loosens Tongues, if Not Purse...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>20801</td>\n",
              "      <td>Russian warships ready to strike terrorists ne...</td>\n",
              "      <td></td>\n",
              "      <td>Russian warships ready to strike terrorists ne...</td>\n",
              "      <td>Russian warships ready to strike terrorists ne...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20802</td>\n",
              "      <td>#NoDAPL: Native American Leaders Vow to Stay A...</td>\n",
              "      <td>Common Dreams</td>\n",
              "      <td>Videos #NoDAPL: Native American Leaders Vow to...</td>\n",
              "      <td>#NoDAPL: Native American Leaders Vow to Stay A...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>20803</td>\n",
              "      <td>Tim Tebow Will Attempt Another Comeback, This ...</td>\n",
              "      <td>Daniel Victor</td>\n",
              "      <td>If at first you don’t succeed, try a different...</td>\n",
              "      <td>Tim Tebow Will Attempt Another Comeback, This ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>20804</td>\n",
              "      <td>Keiser Report: Meme Wars (E995)</td>\n",
              "      <td>Truth Broadcast Network</td>\n",
              "      <td>42 mins ago 1 Views 0 Comments 0 Likes 'For th...</td>\n",
              "      <td>Keiser Report: Meme Wars (E995) Truth Broadcas...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      id  ...                                              total\n",
              "0  20800  ...  Specter of Trump Loosens Tongues, if Not Purse...\n",
              "1  20801  ...  Russian warships ready to strike terrorists ne...\n",
              "2  20802  ...  #NoDAPL: Native American Leaders Vow to Stay A...\n",
              "3  20803  ...  Tim Tebow Will Attempt Another Comeback, This ...\n",
              "4  20804  ...  Keiser Report: Meme Wars (E995) Truth Broadcas...\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hMkU_ZNd9qxc"
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      "source": [
        ""
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      "execution_count": null,
      "outputs": []
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    {
      "cell_type": "code",
      "metadata": {
        "id": "RAdYCyNQOkCT"
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      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "juOiuukbOjrY"
      },
      "source": [
        "Hi WAIT ............\n",
        "\n",
        "This is Just Small Demo. \n",
        "\n",
        "Full Code is long... \n",
        "\n",
        "Full Project is Available with Porject Report and PPT.\n",
        "\n",
        "##Mail me at **Vatshayan007@mail.com** to get this project."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m42H-lyNOjY1"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_PzDiGs9OjVt"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
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}