Accenture_Data_Analysis.ipynb

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        "# Import necessary libraries\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from datetime import datetime\n",
        "%matplotlib inline"
      ]
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        "# Read the csv data\n",
        "content = pd.read_csv(\"/content/Content.csv\")\n",
        "reaction = pd.read_csv(\"/content/Reactions.csv\")\n",
        "reactiontypes = pd.read_csv(\"/content/ReactionTypes.csv\")"
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        "# Understand the data\n",
        "content.head(5)"
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              "        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>Unnamed: 0</th>\n",
              "      <th>Type</th>\n",
              "      <th>Sentiment</th>\n",
              "      <th>Score</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>heart</td>\n",
              "      <td>positive</td>\n",
              "      <td>60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>want</td>\n",
              "      <td>positive</td>\n",
              "      <td>70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>disgust</td>\n",
              "      <td>negative</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>hate</td>\n",
              "      <td>negative</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>interested</td>\n",
              "      <td>positive</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-83df7ce4-fe3c-4548-abf0-8cf29a0771d0')\"\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 0 24 24\"\n",
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              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      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",
              "    [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",
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              "  </style>\n",
              "\n",
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              "          document.querySelector('#df-83df7ce4-fe3c-4548-abf0-8cf29a0771d0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-83df7ce4-fe3c-4548-abf0-8cf29a0771d0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del content[\"Unnamed: 0\"]\n",
        "del reaction[\"Unnamed: 0\"]\n",
        "del reactiontypes[\"Unnamed: 0\"]"
      ],
      "metadata": {
        "id": "dVxpZmzzBtyv"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "content.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 112
        },
        "id": "pp0VToJTBt-J",
        "outputId": "4b4a4103-54df-4350-d7ef-4e5822c9628b"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             Content ID                               User ID  \\\n",
              "0  97522e57-d9ab-4bd6-97bf-c24d952602d2  8d3cd87d-8a31-4935-9a4f-b319bfe05f31   \n",
              "1  9f737e0a-3cdd-4d29-9d24-753f4e3be810  beb1f34e-7870-46d6-9fc7-2e12eb83ce43   \n",
              "\n",
              "    Type        Category                                                URL  \n",
              "0  photo        Studying  https://socialbuzz.cdn.com/content/storage/975...  \n",
              "1  photo  healthy eating  https://socialbuzz.cdn.com/content/storage/9f7...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d5b7df72-ada1-4e85-b2e6-e5d053301dcd\">\n",
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
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              "      <td>photo</td>\n",
              "      <td>Studying</td>\n",
              "      <td>https://socialbuzz.cdn.com/content/storage/975...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>9f737e0a-3cdd-4d29-9d24-753f4e3be810</td>\n",
              "      <td>beb1f34e-7870-46d6-9fc7-2e12eb83ce43</td>\n",
              "      <td>photo</td>\n",
              "      <td>healthy eating</td>\n",
              "      <td>https://socialbuzz.cdn.com/content/storage/9f7...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d5b7df72-ada1-4e85-b2e6-e5d053301dcd')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      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",
              "    [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-d5b7df72-ada1-4e85-b2e6-e5d053301dcd button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-d5b7df72-ada1-4e85-b2e6-e5d053301dcd');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "content[\"Category\"].head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZNRc8NEmBuG3",
        "outputId": "288777f3-c213-4ff9-ca71-6af8e60a48b2"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0           Studying\n",
              "1     healthy eating\n",
              "2     healthy eating\n",
              "3         technology\n",
              "4               food\n",
              "5            cooking\n",
              "6               dogs\n",
              "7         technology\n",
              "8             soccer\n",
              "9    public speaking\n",
              "Name: Category, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "content[\"Category\"]=content[\"Category\"].astype(str)"
      ],
      "metadata": {
        "id": "ZrXQAMhCBuL7"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def turn(x):\n",
        "    x =x.replace('\"', \"\")\n",
        "    return x\n",
        "\n",
        "content[\"Category\"]=content[\"Category\"].apply(lambda x : turn(x) )"
      ],
      "metadata": {
        "id": "UTEvb106BuTd"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "content[\"Category\"]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PsjAkJuVBua3",
        "outputId": "49706f5c-7bb7-488e-ef24-412ca3e76fdb"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0             Studying\n",
              "1       healthy eating\n",
              "2       healthy eating\n",
              "3           technology\n",
              "4                 food\n",
              "            ...       \n",
              "995    public speaking\n",
              "996         technology\n",
              "997           veganism\n",
              "998            culture\n",
              "999         technology\n",
              "Name: Category, Length: 1000, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "content = content.rename(columns={\"Type\":\"Content Type\"})\n"
      ],
      "metadata": {
        "id": "5BVdBm-xBug-"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "content.head()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 250
        },
        "id": "cOs47X3LBult",
        "outputId": "7e113a4f-8f88-4632-f853-1506db99279e"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             Content ID                               User ID  \\\n",
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              "\n",
              "  Content Type        Category  \\\n",
              "0        photo        Studying   \n",
              "1        photo  healthy eating   \n",
              "2        photo  healthy eating   \n",
              "3        photo      technology   \n",
              "4        video            food   \n",
              "\n",
              "                                                 URL  \n",
              "0  https://socialbuzz.cdn.com/content/storage/975...  \n",
              "1  https://socialbuzz.cdn.com/content/storage/9f7...  \n",
              "2  https://socialbuzz.cdn.com/content/storage/230...  \n",
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              "4  https://socialbuzz.cdn.com/content/storage/01a...  "
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              "\n",
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              "      <th>1</th>\n",
              "      <td>9f737e0a-3cdd-4d29-9d24-753f4e3be810</td>\n",
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              "      <td>photo</td>\n",
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              "      <th>2</th>\n",
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              "      <td>video</td>\n",
              "      <td>food</td>\n",
              "      <td>https://socialbuzz.cdn.com/content/storage/01a...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5a554dd7-5c89-46c1-ab2f-f957e85a927a')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "    .colab-df-container {\n",
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-5a554dd7-5c89-46c1-ab2f-f957e85a927a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "content.columns\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "86TYVxHkBurl",
        "outputId": "7bd33366-91b4-4ad4-fd58-1dd980787577"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Content ID', 'User ID', 'Content Type', 'Category', 'URL'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "reaction.columns\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5_eG7HZtBu7X",
        "outputId": "5007669f-3eb5-4e2d-f959-6b251e3a67ed"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Content ID', 'User ID', 'Type', 'Datetime'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "reactiontypes.columns\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y4kw9rBJBvjd",
        "outputId": "00c54c88-1784-4425-e59d-f802a913c419"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Type', 'Sentiment', 'Score'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del content[\"User ID\"]\n",
        "del reaction[\"User ID\"]"
      ],
      "metadata": {
        "id": "aV9OHR8pBwHQ"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "reaction.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "7kkUHXWIBwmI",
        "outputId": "872ddb87-2d2e-4260-e35c-751ac2229699"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             Content ID     Type             Datetime\n",
              "0  97522e57-d9ab-4bd6-97bf-c24d952602d2      NaN  2021-04-22 15:17:15\n",
              "1  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust  2020-11-07 09:43:50\n",
              "2  97522e57-d9ab-4bd6-97bf-c24d952602d2  dislike  2021-06-17 12:22:51\n",
              "3  97522e57-d9ab-4bd6-97bf-c24d952602d2   scared  2021-04-18 05:13:58\n",
              "4  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust  2021-01-06 19:13:01"
            ],
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              "      <td>2021-01-06 19:13:01</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
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      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             Content ID Content Type        Category  \\\n",
              "0  97522e57-d9ab-4bd6-97bf-c24d952602d2        photo        Studying   \n",
              "1  9f737e0a-3cdd-4d29-9d24-753f4e3be810        photo  healthy eating   \n",
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              "4  01ab84dd-6364-4236-abbb-3f237db77180        video            food   \n",
              "\n",
              "                                                 URL  \n",
              "0  https://socialbuzz.cdn.com/content/storage/975...  \n",
              "1  https://socialbuzz.cdn.com/content/storage/9f7...  \n",
              "2  https://socialbuzz.cdn.com/content/storage/230...  \n",
              "3  https://socialbuzz.cdn.com/content/storage/356...  \n",
              "4  https://socialbuzz.cdn.com/content/storage/01a...  "
            ],
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              "          const element = document.querySelector('#df-4ee70b0d-2674-4209-b03b-049023bc8247');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
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              "  "
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              "                             Content ID     Type             Datetime  \\\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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      "execution_count": 23,
      "outputs": [
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          "data": {
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              "                             Content ID     Type             Datetime  \\\n",
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              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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      "outputs": []
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      "execution_count": 25,
      "outputs": [
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              "                                Content ID     Type             Datetime  \\\n",
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              "9793  9a2c328f-16aa-490c-8ca2-c7deaa90db3f    adore  2021-01-26 12:06:28   \n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>9f737e0a-3cdd-4d29-9d24-753f4e3be810</td>\n",
              "      <td>disgust</td>\n",
              "      <td>2021-03-28 21:15:26</td>\n",
              "      <td>healthy eating</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>230c4e4d-70c3-461d-b42c-ec09396efb3f</td>\n",
              "      <td>disgust</td>\n",
              "      <td>2020-08-04 05:40:33</td>\n",
              "      <td>healthy eating</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9789</th>\n",
              "      <td>91f7585b-c756-475b-9f21-877d7c48b579</td>\n",
              "      <td>adore</td>\n",
              "      <td>2021-06-09 08:11:09</td>\n",
              "      <td>soccer</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9790</th>\n",
              "      <td>9a2c328f-16aa-490c-8ca2-c7deaa90db3f</td>\n",
              "      <td>adore</td>\n",
              "      <td>2020-12-21 13:03:26</td>\n",
              "      <td>culture</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9791</th>\n",
              "      <td>9a2c328f-16aa-490c-8ca2-c7deaa90db3f</td>\n",
              "      <td>adore</td>\n",
              "      <td>2020-10-02 10:36:15</td>\n",
              "      <td>culture</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9792</th>\n",
              "      <td>9a2c328f-16aa-490c-8ca2-c7deaa90db3f</td>\n",
              "      <td>adore</td>\n",
              "      <td>2020-07-29 13:57:13</td>\n",
              "      <td>culture</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9793</th>\n",
              "      <td>9a2c328f-16aa-490c-8ca2-c7deaa90db3f</td>\n",
              "      <td>adore</td>\n",
              "      <td>2021-01-26 12:06:28</td>\n",
              "      <td>culture</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9794 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a036a8ec-357a-4c23-8085-3eba27be268d')\"\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 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\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",
              "    [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-a036a8ec-357a-4c23-8085-3eba27be268d button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a036a8ec-357a-4c23-8085-3eba27be268d');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "reactiontypes[\"Category\"].max()\n"
      ],
      "metadata": {
        "id": "7rhaUzklCnIj",
        "outputId": "d6fee148-e9a6-45a1-ac79-aa8f4c9fe5eb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        }
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'veganism'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(reactiontypes[\"Category\"]==\"veganism\")"
      ],
      "metadata": {
        "id": "oA_28BDdCnPp",
        "outputId": "d58218fa-fa57-4e38-c671-43331d7a04d3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "9794"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "reactiontypes.isnull().sum()"
      ],
      "metadata": {
        "id": "A1DzZ3SMCnW0",
        "outputId": "9532ec9e-766c-410d-c909-d41d71ce9117",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Content ID    0\n",
              "Type          0\n",
              "Datetime      0\n",
              "Category      0\n",
              "Score         0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Groupby calculation\n",
        "reaction = reaction.groupby(\"Category\")[\"Score\"].sum()"
      ],
      "metadata": {
        "id": "d-dpAlCRCndd"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "reaction = reaction.sort_values(ascending=False)"
      ],
      "metadata": {
        "id": "vFvH-WYnDDMX"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "reaction.to_csv(\"cleaned_data.csv\")"
      ],
      "metadata": {
        "id": "kpFtnYtWDDVm"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot the values\n",
        "\n",
        "y = reaction.values\n",
        "y = y[:5]\n",
        "x = reaction.index\n",
        "x = x[:5]\n",
        "plt.bar(x,y,width = 0.4,color=\"green\")\n",
        "plt.ylabel(\"Total Score\",fontsize = 16,color=\"black\")\n",
        "plt.xlabel(\"Category\",fontsize = 16,color=\"black\")\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "ilAEQrKmDDec",
        "outputId": "9aa994a4-2374-41c6-abe9-c0c7acf97f8d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        }
      },
      "execution_count": 32,
      "outputs": [
        {
          "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": [
        "reactiontypes\n"
      ],
      "metadata": {
        "id": "nIDy4EIhDDnS",
        "outputId": "0f59d2cb-e4e2-49b8-cddf-9eede4c5d608",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        }
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                Content ID     Type             Datetime  \\\n",
              "0     97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust  2020-11-07 09:43:50   \n",
              "1     97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust  2021-01-06 19:13:01   \n",
              "2     97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust  2021-04-09 02:46:20   \n",
              "3     9f737e0a-3cdd-4d29-9d24-753f4e3be810  disgust  2021-03-28 21:15:26   \n",
              "4     230c4e4d-70c3-461d-b42c-ec09396efb3f  disgust  2020-08-04 05:40:33   \n",
              "...                                    ...      ...                  ...   \n",
              "9789  91f7585b-c756-475b-9f21-877d7c48b579    adore  2021-06-09 08:11:09   \n",
              "9790  9a2c328f-16aa-490c-8ca2-c7deaa90db3f    adore  2020-12-21 13:03:26   \n",
              "9791  9a2c328f-16aa-490c-8ca2-c7deaa90db3f    adore  2020-10-02 10:36:15   \n",
              "9792  9a2c328f-16aa-490c-8ca2-c7deaa90db3f    adore  2020-07-29 13:57:13   \n",
              "9793  9a2c328f-16aa-490c-8ca2-c7deaa90db3f    adore  2021-01-26 12:06:28   \n",
              "\n",
              "            Category  Score  \n",
              "0           Studying      0  \n",
              "1           Studying      0  \n",
              "2           Studying      0  \n",
              "3     healthy eating      0  \n",
              "4     healthy eating      0  \n",
              "...              ...    ...  \n",
              "9789          soccer     72  \n",
              "9790         culture     72  \n",
              "9791         culture     72  \n",
              "9792         culture     72  \n",
              "9793         culture     72  \n",
              "\n",
              "[9794 rows x 5 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5d67d188-b249-4fd7-9823-f8609ec2192d\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Content ID</th>\n",
              "      <th>Type</th>\n",
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              "      <th>Category</th>\n",
              "      <th>Score</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
              "      <td>disgust</td>\n",
              "      <td>2020-11-07 09:43:50</td>\n",
              "      <td>Studying</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
              "      <td>disgust</td>\n",
              "      <td>2021-01-06 19:13:01</td>\n",
              "      <td>Studying</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>97522e57-d9ab-4bd6-97bf-c24d952602d2</td>\n",
              "      <td>disgust</td>\n",
              "      <td>2021-04-09 02:46:20</td>\n",
              "      <td>Studying</td>\n",
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              "      <td>9f737e0a-3cdd-4d29-9d24-753f4e3be810</td>\n",
              "      <td>disgust</td>\n",
              "      <td>2021-03-28 21:15:26</td>\n",
              "      <td>healthy eating</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>230c4e4d-70c3-461d-b42c-ec09396efb3f</td>\n",
              "      <td>disgust</td>\n",
              "      <td>2020-08-04 05:40:33</td>\n",
              "      <td>healthy eating</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9789</th>\n",
              "      <td>91f7585b-c756-475b-9f21-877d7c48b579</td>\n",
              "      <td>adore</td>\n",
              "      <td>2021-06-09 08:11:09</td>\n",
              "      <td>soccer</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9790</th>\n",
              "      <td>9a2c328f-16aa-490c-8ca2-c7deaa90db3f</td>\n",
              "      <td>adore</td>\n",
              "      <td>2020-12-21 13:03:26</td>\n",
              "      <td>culture</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9791</th>\n",
              "      <td>9a2c328f-16aa-490c-8ca2-c7deaa90db3f</td>\n",
              "      <td>adore</td>\n",
              "      <td>2020-10-02 10:36:15</td>\n",
              "      <td>culture</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9792</th>\n",
              "      <td>9a2c328f-16aa-490c-8ca2-c7deaa90db3f</td>\n",
              "      <td>adore</td>\n",
              "      <td>2020-07-29 13:57:13</td>\n",
              "      <td>culture</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9793</th>\n",
              "      <td>9a2c328f-16aa-490c-8ca2-c7deaa90db3f</td>\n",
              "      <td>adore</td>\n",
              "      <td>2021-01-26 12:06:28</td>\n",
              "      <td>culture</td>\n",
              "      <td>72</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9794 rows × 5 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5d67d188-b249-4fd7-9823-f8609ec2192d')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "        \n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Changing it to a respective date format\n",
        "reactiontypes['Datetime'] = pd.to_datetime(reactiontypes['Datetime'] ,infer_datetime_format=True)"
      ],
      "metadata": {
        "id": "m2i_gskTDD1q"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "reactiontypes[\"Datetime\"]\n"
      ],
      "metadata": {
        "id": "3bXRrTL9DFS-",
        "outputId": "33ae56d5-bb6b-4680-fdba-faac1c1b8935",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0      2020-11-07 09:43:50\n",
              "1      2021-01-06 19:13:01\n",
              "2      2021-04-09 02:46:20\n",
              "3      2021-03-28 21:15:26\n",
              "4      2020-08-04 05:40:33\n",
              "               ...        \n",
              "9789   2021-06-09 08:11:09\n",
              "9790   2020-12-21 13:03:26\n",
              "9791   2020-10-02 10:36:15\n",
              "9792   2020-07-29 13:57:13\n",
              "9793   2021-01-26 12:06:28\n",
              "Name: Datetime, Length: 9794, dtype: datetime64[ns]"
            ]
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "reactiontypes[\"Month\"] = reactiontypes[\"Datetime\"].dt.month\n"
      ],
      "metadata": {
        "id": "uA5jmxVkDFnB"
      },
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "reactiontypes[\"Month\"]\n"
      ],
      "metadata": {
        "id": "aVzaGfBvDFw5",
        "outputId": "a58d43dd-aea3-4bbb-ab18-0c3c20510709",
        "colab": {
          "base_uri": "https://localhost:8080/"
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      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0       11\n",
              "1        1\n",
              "2        4\n",
              "3        3\n",
              "4        8\n",
              "        ..\n",
              "9789     6\n",
              "9790    12\n",
              "9791    10\n",
              "9792     7\n",
              "9793     1\n",
              "Name: Month, Length: 9794, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = reactiontypes.copy()\n"
      ],
      "metadata": {
        "id": "kfvAD6sgDF5f"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
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      },
      "execution_count": 39,
      "outputs": [
        {
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              "                             Content ID     Type            Datetime  \\\n",
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              "3  healthy eating      0      3  \n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
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          },
          "metadata": {},
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      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              "Type          0\n",
              "Datetime      0\n",
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        "data[\"Count\"] = data.groupby('Month')['Month'].transform('count')\n"
      ],
      "metadata": {
        "id": "wQZgb8YlDGOU"
      },
      "execution_count": 41,
      "outputs": []
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    {
      "cell_type": "code",
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        "data =data.drop_duplicates(subset=[\"Month\"])\n"
      ],
      "metadata": {
        "id": "lZD28AlED1QN"
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      "execution_count": 42,
      "outputs": []
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      "execution_count": 43,
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              "                             Content ID     Type            Datetime  \\\n",
              "0  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust 2020-11-07 09:43:50   \n",
              "1  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust 2021-01-06 19:13:01   \n",
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              "4  230c4e4d-70c3-461d-b42c-ec09396efb3f  disgust 2020-08-04 05:40:33   \n",
              "\n",
              "         Category  Score  Month  Count  \n",
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              "1        Studying      0      1    866  \n",
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              "      <td>8</td>\n",
              "      <td>833</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a8d95000-0133-408a-8267-d6a2575552e7')\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
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              "    .colab-df-container {\n",
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              "    .colab-df-convert {\n",
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              "      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",
              "    [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-a8d95000-0133-408a-8267-d6a2575552e7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a8d95000-0133-408a-8267-d6a2575552e7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.reset_index()\n"
      ],
      "metadata": {
        "id": "plTULoARD1jE",
        "outputId": "f3b86220-1719-4586-89b3-4c8b1c8204e4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        }
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    index                            Content ID     Type            Datetime  \\\n",
              "0       0  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust 2020-11-07 09:43:50   \n",
              "1       1  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust 2021-01-06 19:13:01   \n",
              "2       2  97522e57-d9ab-4bd6-97bf-c24d952602d2  disgust 2021-04-09 02:46:20   \n",
              "3       3  9f737e0a-3cdd-4d29-9d24-753f4e3be810  disgust 2021-03-28 21:15:26   \n",
              "4       4  230c4e4d-70c3-461d-b42c-ec09396efb3f  disgust 2020-08-04 05:40:33   \n",
              "5       7  3f8590c7-6ab2-4973-805a-90cdec355f05  disgust 2021-02-11 20:10:20   \n",
              "6       8  b18cb63f-4c8e-44ee-a47f-541e95191d11  disgust 2021-05-27 01:44:22   \n",
              "7      12  0be59876-d70c-486c-8e0b-a06bef7a2cd6  disgust 2020-09-11 16:22:49   \n",
              "8      13  0be59876-d70c-486c-8e0b-a06bef7a2cd6  disgust 2020-10-13 16:31:34   \n",
              "9      14  0be59876-d70c-486c-8e0b-a06bef7a2cd6  disgust 2020-07-23 19:31:31   \n",
              "10     15  81abd65a-3b76-4574-a0a7-db6bf7184ae2  disgust 2020-12-08 13:12:56   \n",
              "11     22  a2e93b29-9259-4092-a4d7-62d5e823bb74  disgust 2021-06-09 09:41:37   \n",
              "\n",
              "           Category  Score  Month  Count  \n",
              "0          Studying      0     11    822  \n",
              "1          Studying      0      1    866  \n",
              "2          Studying      0      4    789  \n",
              "3    healthy eating      0      3    800  \n",
              "4    healthy eating      0      8    833  \n",
              "5              dogs      0      2    773  \n",
              "6   public speaking      0      5    863  \n",
              "7            tennis      0      9    810  \n",
              "8            tennis      0     10    808  \n",
              "9            tennis      0      7    821  \n",
              "10             food      0     12    789  \n",
              "11  public speaking      0      6    820  "
            ],
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              "      <td>disgust</td>\n",
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              "      <td>healthy eating</td>\n",
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              "      <td>disgust</td>\n",
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              "      <td>healthy eating</td>\n",
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              "      <td>dogs</td>\n",
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              "      <td>2</td>\n",
              "      <td>773</td>\n",
              "    </tr>\n",
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              "      <th>6</th>\n",
              "      <td>8</td>\n",
              "      <td>b18cb63f-4c8e-44ee-a47f-541e95191d11</td>\n",
              "      <td>disgust</td>\n",
              "      <td>2021-05-27 01:44:22</td>\n",
              "      <td>public speaking</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>863</td>\n",
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              "      <td>tennis</td>\n",
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              "      <td>14</td>\n",
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              "      <td>disgust</td>\n",
              "      <td>2020-07-23 19:31:31</td>\n",
              "      <td>tennis</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>821</td>\n",
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              "      <td>15</td>\n",
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              "      <td>disgust</td>\n",
              "      <td>2020-12-08 13:12:56</td>\n",
              "      <td>food</td>\n",
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              "      <td>12</td>\n",
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              "      <td>6</td>\n",
              "      <td>820</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-31a9e6f9-61d3-46f5-a943-47ba756401a9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      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",
              "    [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",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-31a9e6f9-61d3-46f5-a943-47ba756401a9 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-31a9e6f9-61d3-46f5-a943-47ba756401a9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? 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",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fig = plt.figure(figsize=(15,5), dpi = 150)\n",
        "ax = plt.subplot()\n",
        "x = data[\"Month\"]\n",
        "y = data[\"Count\"]\n",
        "ax.set_xticks(np.arange(13))\n",
        "plt.title(\"Total Posts vs Month\")\n",
        "plt.xlabel(\"Month\")\n",
        "plt.ylabel(\"Posts\")\n",
        "colors = [\"green\" if i != 5 else \"yellow\" for i in x]\n",
        "plt.bar(x, y,color=colors)\n",
        "plt.show"
      ],
      "metadata": {
        "id": "8mznev7KD1sU",
        "outputId": "aa559284-5a9e-4112-a762-85dc8e0ad9b6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        }
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<function matplotlib.pyplot.show(close=None, block=None)>"
            ]
          },
          "metadata": {},
          "execution_count": 45
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2250x750 with 1 Axes>"
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            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "GnzQFQh5D14Z"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "IgSoip07D2B_"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "oU7WYKLnD2Oe"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "TOpIkjcSD2aX"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "FW7YBm0LD2nM"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "uoK2N4mMD375"
      },
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "aNcpnzxcD4Id"
      },
      "execution_count": 45,
      "outputs": []
    }
  ]
}