Food_Channel_Scrapper.ipynb

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          "text": [
            "Requirement already satisfied: pandas==1.4.0 in /usr/local/lib/python3.10/dist-packages (1.4.0)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas==1.4.0) (2.8.2)\n",
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            "Requirement already satisfied: numpy>=1.21.0 in /usr/local/lib/python3.10/dist-packages (from pandas==1.4.0) (1.26.4)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas==1.4.0) (1.16.0)\n",
            "Requirement already satisfied: psycopg2-binary in /usr/local/lib/python3.10/dist-packages (2.9.9)\n"
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      "source": [
        "!pip install pandas==1.4.0\n",
        "#import libraries\n",
        "import requests\n",
        "import pandas as pd\n",
        "import time\n",
        "!pip install psycopg2-binary\n",
        "import psycopg2 as ps\n",
        "from numpy import e"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#keys\n",
        "ChANNEL_ID = \"UCyEd6QBSgat5kkC6svyjudA\"\n",
        "API_KEY = \"AIzaSyDFDfMvzcJD2bd7kURXXM1D1usZKNqDkJA\""
      ],
      "metadata": {
        "id": "kWdsCCgR9ShO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_video_details(video_id):\n",
        "\n",
        "      #collecting view, like, dislike, comment counts\n",
        "      url_video_stats = \"https://www.googleapis.com/youtube/v3/videos?id=\"+video_id+\"&part=statistics&key=\"+API_KEY\n",
        "\n",
        "      response_video_stats = requests.get(url_video_stats).json()\n",
        "\n",
        "      view_count = response_video_stats['items'][0]['statistics']['viewCount']\n",
        "      like_count = response_video_stats['items'][0]['statistics']['likeCount']\n",
        "      comment_count = response_video_stats['items'][0]['statistics']['commentCount']\n",
        "\n",
        "      return view_count, like_count, comment_count"
      ],
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      "execution_count": null,
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        "def get_videos(df):\n",
        "    #define an empty list to collect data\n",
        "    data = []\n",
        "    #make API call\n",
        "    pageToken = \"\"\n",
        "    url= \"https://www.googleapis.com/youtube/v3/search?key=\"+API_KEY+\"&channelId=\"+ChANNEL_ID+\"&part=snippet,id&order=date&maxResults=10000\"+pageToken\n",
        "\n",
        "    response = requests.get(url).json()\n",
        "    time.sleep(1)\n",
        "\n",
        "    for video in response['items']:\n",
        "        if video['id']['kind'] == \"youtube#video\":\n",
        "            video_id = video['id']['videoId']\n",
        "            video_title = video['snippet']['title']\n",
        "            upload_date = video['snippet']['publishedAt']\n",
        "            upload_date = str(upload_date).split(\"T\")[0]\n",
        "\n",
        "            view_count, like_count, comment_count = get_video_details(video_id)\n",
        "            #save data in the list\n",
        "            data.append({'video_id':video_id,'video_title':video_title,\n",
        "                            'upload_date':upload_date,'view_count':view_count,\n",
        "                            'like_count':like_count,'comment_count':comment_count})\n",
        "\n",
        "    # create a DataFrame from the list and concatenate\n",
        "    df = pd.concat([df, pd.DataFrame(data)], ignore_index=True)\n",
        "    return df"
      ],
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        "# build the dataframe\n",
        "df =pd.DataFrame(columns=[\"video_id\", \"video_title\",\"upload_date\",\"view_count\",\"like_count\",\"comment_count\"])\n",
        "\n",
        "df = get_videos(df)"
      ],
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        "df.head()"
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              "      video_id                                        video_title upload_date  \\\n",
              "0  8p_Ad9dCPVU  Island Seafood Paradise!! 🇲🇺 QUEEN OF SEAFOOD ...  2024-10-01   \n",
              "1  E3g-zgSmwUs  Street Food in Mauritius - FRIED CHICKEN TIKKA...  2024-09-28   \n",
              "2  rLfE_d538VM  Backyard Biryani Paradise!! EXTREME FOOD in Ma...  2024-09-24   \n",
              "3  nAF45YzUQ1w  Best STREET FOOD in Syria!! 🇸🇾 31 Syrian Meals...  2024-09-17   \n",
              "4  F2PTz6If3sY  Thai Street Food - BEST $5 MEALS in Phuket, Th...  2024-09-10   \n",
              "\n",
              "  view_count like_count comment_count  \n",
              "0     114010       4046           172  \n",
              "1     414661       8189           508  \n",
              "2     686354      11125           578  \n",
              "3     360046       6050           497  \n",
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    {
      "cell_type": "code",
      "source": [
        "!pip install google-colab\n",
        "import pandas as pd\n",
        "from google.colab import files\n",
        "\n",
        "df.to_excel(\"ytfood.xlsx\")\n",
        "files.download('ytfood.xlsx') # use the files object from google.colab\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ttMVjAhK9qcc",
        "outputId": "5c979685-2216-4651-cd89-e0b100d8620e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: google-colab in /usr/local/lib/python3.10/dist-packages (1.0.0)\n",
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            "Collecting jedi>=0.16 (from ipython==7.34.0->google-colab)\n",
            "  Using cached jedi-0.19.1-py2.py3-none-any.whl.metadata (22 kB)\n",
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            "Requirement already satisfied: anyio<4,>=3.1.0 in /usr/local/lib/python3.10/dist-packages (from jupyter-server<3,>=1.8->notebook-shim>=0.2.3->nbclassic>=0.4.7->notebook==6.5.5->google-colab) (3.7.1)\n",
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            "Requirement already satisfied: sniffio>=1.1 in /usr/local/lib/python3.10/dist-packages (from anyio<4,>=3.1.0->jupyter-server<3,>=1.8->notebook-shim>=0.2.3->nbclassic>=0.4.7->notebook==6.5.5->google-colab) (1.3.1)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<4,>=3.1.0->jupyter-server<3,>=1.8->notebook-shim>=0.2.3->nbclassic>=0.4.7->notebook==6.5.5->google-colab) (1.2.2)\n",
            "Using cached jedi-0.19.1-py2.py3-none-any.whl (1.6 MB)\n",
            "Installing collected packages: jedi\n",
            "Successfully installed jedi-0.19.1\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "download(\"download_af6f2af2-fdbc-4948-99a5-66c2c2344595\", \"ytfood.xlsx\", 9934)"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#keys\n",
        "ChANNEL_ID = \"UCcAd5Np7fO8SeejB1FVKcYw\"\n",
        "API_KEY = \"AIzaSyDFDfMvzcJD2bd7kURXXM1D1usZKNqDkJA\"\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "avzonTg89qeO"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_video_details(video_id):\n",
        "\n",
        "      #collecting view, like, dislike, comment counts\n",
        "      url_video_stats = \"https://www.googleapis.com/youtube/v3/videos?id=\"+video_id+\"&part=statistics&key=\"+API_KEY\n",
        "\n",
        "      response_video_stats = requests.get(url_video_stats).json()\n",
        "\n",
        "      view_count = response_video_stats['items'][0]['statistics']['viewCount']\n",
        "      like_count = response_video_stats['items'][0]['statistics']['likeCount']\n",
        "      comment_count = response_video_stats['items'][0]['statistics']['commentCount']\n",
        "\n",
        "      return view_count, like_count, comment_count"
      ],
      "metadata": {
        "id": "t6jppoLl9qgU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def get_videos(df):\n",
        "    #make API call\n",
        "    pageToken = \"\"\n",
        "    url= \"https://www.googleapis.com/youtube/v3/search?key=\"+API_KEY+\"&channelId=\"+ChANNEL_ID+\"&part=snippet,id&order=date&maxResults=10000\"+pageToken\n",
        "\n",
        "    response = requests.get(url).json()\n",
        "    time.sleep(1)\n",
        "\n",
        "    for video in response['items']:\n",
        "        if video['id']['kind'] == \"youtube#video\":\n",
        "            video_id = video['id']['videoId']\n",
        "            video_title = video['snippet']['title']\n",
        "            upload_date = video['snippet']['publishedAt']\n",
        "            upload_date = str(upload_date).split(\"T\")[0]\n",
        "\n",
        "            view_count, like_count, comment_count = get_video_details(video_id)\n",
        "            #save data in pandas df\n",
        "            df = df.append({'video_id':video_id,'video_title':video_title,\n",
        "                            'upload_date':upload_date,'view_count':view_count,\n",
        "                            'like_count':like_count,'comment_count':comment_count},\n",
        "                          ignore_index=True)\n",
        "\n",
        "    return df"
      ],
      "metadata": {
        "id": "IdyySYO89qiZ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# build the dataframe\n",
        "df =pd.DataFrame(columns=[\"video_id\", \"video_title\",\"upload_date\",\"view_count\",\"like_count\",\"comment_count\"])\n",
        "\n",
        "df = get_videos(df)"
      ],
      "metadata": {
        "id": "4v3Gu32eApYX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0da9c66c-911a-4f79-8da7-b119233c7263"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n",
            "<ipython-input-4-cc8b6e68566f>:18: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
            "  df = df.append({'video_id':video_id,'video_title':video_title,\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "k7ESNtzPApfq",
        "outputId": "892d49ae-8c82-43ed-c132-e2166063687d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      video_id                                        video_title upload_date  \\\n",
              "0  WQXmBU3Pv-0  Traveling To The World&#39;s WORST Food Country!!  2024-09-27   \n",
              "1  mgAv3NSgyYs     Surviving Ghana!! Africa’s Most EXTREME Food!!  2024-09-20   \n",
              "2  Gt8U7ekFCC0  Eating in Africa&#39;s WILDEST Fish Market!! S...  2024-09-13   \n",
              "3  hi9fIuoUki4  How Eating Snails Could Save Africa&#39;s Bush...  2024-09-06   \n",
              "4  NqGJaobxyWk  Inside Africa’s Billion Dollar Bushmeat Indust...  2024-08-30   \n",
              "\n",
              "  view_count like_count comment_count  \n",
              "0    1098963      22933          2178  \n",
              "1     973424      11551           732  \n",
              "2    2326715      32898          2208  \n",
              "3     704453      17505          1158  \n",
              "4    1126531      23553          2051  "
            ],
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              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-b492c756-dbb0-4a90-b2c2-aa4dfe863783 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 48,\n  \"fields\": [\n    {\n      \"column\": \"video_id\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 48,\n        \"samples\": [\n          \"dimWbllQIAE\",\n          \"rh-OH0a4emg\",\n          \"nhwufI_lNRo\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"video_title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 48,\n        \"samples\": [\n          \"$1 Noodles VS $163 Noodles in Vietnam!! (RECORD BREAKING Bowl!!)\",\n          \"This Island\\u2019s Food SMASHES The Rest of the Caribbean!!\",\n          \"The Philippines Heartbreaking Street Food!! Garbage Can Chicken / Pag Pag!!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"upload_date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 48,\n        \"samples\": [\n          \"2024-03-31\",\n          \"2024-01-06\",\n          \"2024-04-05\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"view_count\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 48,\n        \"samples\": [\n          \"1877117\",\n          \"353682\",\n          \"3601096\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"like_count\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 48,\n        \"samples\": [\n          \"40592\",\n          \"8748\",\n          \"77843\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"comment_count\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 46,\n        \"samples\": [\n          \"1202\",\n          \"7559\",\n          \"1448\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_excel(\"ytfoodbandana.xlsx\")\n",
        "\n"
      ],
      "metadata": {
        "id": "OK3-KCfTAtih"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import files\n",
        "files.download('ytfoodbandana.xlsx')\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "id": "9yd2PuDaFAVg",
        "outputId": "47021ce0-b0b7-4ad0-df14-58cad36a3965"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "\n",
              "    async function download(id, filename, size) {\n",
              "      if (!google.colab.kernel.accessAllowed) {\n",
              "        return;\n",
              "      }\n",
              "      const div = document.createElement('div');\n",
              "      const label = document.createElement('label');\n",
              "      label.textContent = `Downloading \"${filename}\": `;\n",
              "      div.appendChild(label);\n",
              "      const progress = document.createElement('progress');\n",
              "      progress.max = size;\n",
              "      div.appendChild(progress);\n",
              "      document.body.appendChild(div);\n",
              "\n",
              "      const buffers = [];\n",
              "      let downloaded = 0;\n",
              "\n",
              "      const channel = await google.colab.kernel.comms.open(id);\n",
              "      // Send a message to notify the kernel that we're ready.\n",
              "      channel.send({})\n",
              "\n",
              "      for await (const message of channel.messages) {\n",
              "        // Send a message to notify the kernel that we're ready.\n",
              "        channel.send({})\n",
              "        if (message.buffers) {\n",
              "          for (const buffer of message.buffers) {\n",
              "            buffers.push(buffer);\n",
              "            downloaded += buffer.byteLength;\n",
              "            progress.value = downloaded;\n",
              "          }\n",
              "        }\n",
              "      }\n",
              "      const blob = new Blob(buffers, {type: 'application/binary'});\n",
              "      const a = document.createElement('a');\n",
              "      a.href = window.URL.createObjectURL(blob);\n",
              "      a.download = filename;\n",
              "      div.appendChild(a);\n",
              "      a.click();\n",
              "      div.remove();\n",
              "    }\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "download(\"download_0072071b-39ec-45ab-83b5-7681a2a4fb6b\", \"ytfoodbandana.xlsx\", 9182)"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "NOW WE ARE GOING TO EXTRACT THE COUNTRY FROM THE VIDEO TITLE"
      ],
      "metadata": {
        "id": "ldewb_voLdIa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "df = pd.read_excel(\"/Users/ellievanhattem/Desktop/Tracking food across the world/ytfood (1).xlsx\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 365
        },
        "id": "467SDrzKLWj2",
        "outputId": "64ac3063-004a-4324-8660-bb60896f4704"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "FileNotFoundError",
          "evalue": "[Errno 2] No such file or directory: '/Users/ellievanhattem/Desktop/Tracking food across the world/ytfood (1).xlsx'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-9-71a52f333531>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_excel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"/Users/ellievanhattem/Desktop/Tracking food across the world/ytfood (1).xlsx\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/util/_decorators.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    309\u001b[0m                     \u001b[0mstacklevel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstacklevel\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m                 )\n\u001b[0;32m--> 311\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    312\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    313\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/excel/_base.py\u001b[0m in \u001b[0;36mread_excel\u001b[0;34m(io, sheet_name, header, names, index_col, usecols, squeeze, dtype, engine, converters, true_values, false_values, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, parse_dates, date_parser, thousands, decimal, comment, skipfooter, convert_float, mangle_dupe_cols, storage_options)\u001b[0m\n\u001b[1;32m    455\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mExcelFile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    456\u001b[0m         \u001b[0mshould_close\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 457\u001b[0;31m         \u001b[0mio\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mExcelFile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstorage_options\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstorage_options\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    458\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m!=\u001b[0m \u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    459\u001b[0m         raise ValueError(\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/excel/_base.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, path_or_buffer, engine, storage_options)\u001b[0m\n\u001b[1;32m   1374\u001b[0m                 \u001b[0mext\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"xls\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1375\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1376\u001b[0;31m                 ext = inspect_excel_format(\n\u001b[0m\u001b[1;32m   1377\u001b[0m                     \u001b[0mcontent_or_path\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstorage_options\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstorage_options\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1378\u001b[0m                 )\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/excel/_base.py\u001b[0m in \u001b[0;36minspect_excel_format\u001b[0;34m(content_or_path, storage_options)\u001b[0m\n\u001b[1;32m   1248\u001b[0m         \u001b[0mcontent_or_path\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcontent_or_path\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1249\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1250\u001b[0;31m     with get_handle(\n\u001b[0m\u001b[1;32m   1251\u001b[0m         \u001b[0mcontent_or_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"rb\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstorage_options\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstorage_options\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mis_text\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1252\u001b[0m     ) as handle:\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/io/common.py\u001b[0m in \u001b[0;36mget_handle\u001b[0;34m(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options)\u001b[0m\n\u001b[1;32m    796\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    797\u001b[0m             \u001b[0;31m# Binary mode\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 798\u001b[0;31m             \u001b[0mhandle\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mioargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmode\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    799\u001b[0m         \u001b[0mhandles\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhandle\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    800\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/Users/ellievanhattem/Desktop/Tracking food across the world/ytfood (1).xlsx'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pycountry\n",
        "\n",
        "# Create a dictionary of country names and their key words\n",
        "countries = {}\n",
        "for country in pycountry.countries:\n",
        "    name = country.name\n",
        "    alpha2 = country.alpha_2\n",
        "    alpha3 = country.alpha_3\n",
        "    keywords = [name, alpha2, alpha3]\n",
        "    countries[name] = keywords\n"
      ],
      "metadata": {
        "id": "snH1OEvoLx50"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def extract_location(title):\n",
        "    for country, keywords in countries.items():\n",
        "        for keyword in keywords:\n",
        "            if keyword in title:\n",
        "                return country\n",
        "    return \"Unknown\"\n"
      ],
      "metadata": {
        "id": "FF_-g7AvL4eJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['location'] = df['video_title'].apply(extract_location)\n"
      ],
      "metadata": {
        "id": "cW7ONMxoL46R"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df.to_excel(\"video_titles_with_location.xlsx\")\n",
        "files.download('ytfood.xlsx')\n"
      ],
      "metadata": {
        "id": "z1ntaPRxL9MR"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}