Cycle_rental_final_dataset.ipynb

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        "<a href=\"https://colab.research.google.com/github/debstS/London-cycle-rental-analysis/blob/main/Cycle_rental_final_dataset.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "# to mount Google drive files for accessing from within Google Colab\n",
        "\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import pandas as pd\n",
        "import glob\n"
      ],
      "metadata": {
        "id": "YDNHG7bfYAy5"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#copy and paste the path where the dataset is stored in your computer\n",
        "\n",
        "os.chdir(\"/content/drive/MyDrive/TFL Cycle rental analysis - datasets\")\n",
        "\n"
      ],
      "metadata": {
        "id": "-SLVN2cdYECI"
      },
      "execution_count": null,
      "outputs": []
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      "source": [
        "# Step 1: List all CSV files in the directory\n",
        "\n",
        "csv_files = glob.glob(\"*.csv\")  # Assumes all CSV files are in the same directory\n",
        "\n",
        "#csv_files\n",
        "\n",
        "# Step 2: Read each CSV file and store them in a list\n",
        "df_list = []\n",
        "for file in csv_files:\n",
        "  #print(file)\n",
        "    df = pd.read_csv(file,low_memory = False)\n",
        "    df.rename(columns = {'Rental Id':'Number', 'Duration':'Total duration', 'Bike Id':'Bike number', 'End Date':'End date', 'EndStation Id':'End station number', 'EndStation Name':'End station', 'Start Date':'Start date', 'StartStation Id':'Start station number','StartStation Name':'Start station'}, inplace=True)\n",
        "    #df = df[['Number', 'Start date','Start station number','Start station','End date','End station number','End station','Bike number','Total duration']]\n",
        "    #df = df.reindex(columns=['mean',0,1,2,3,4])\n",
        "    df_list.append(df)\n",
        "\n",
        "\n"
      ],
      "metadata": {
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      "source": [
        "total_records_in_142csv_files = 0\n",
        "for i, dfi in enumerate(df_list):\n",
        "  #print(dfi.shape[0])\n",
        "  total_records_in_142csv_files = total_records_in_142csv_files + dfi.shape[0]\n",
        "total_records_in_142csv_files #30786752"
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        "# #import polars as pl\n",
        "\n",
        "df1 = pd.DataFrame({\"A\":[1,2,3], \"B\":[87,88,30]})\n",
        "df2 = pd.DataFrame({\"B\":[4,5,6], \"A\":[1,2,3], \"C\":['a','c','c']})\n",
        "\n",
        "df = pd.concat([df1, df2])\n",
        "df"
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              "   A   B    C\n",
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              "1  2  88  NaN\n",
              "2  3  30  NaN\n",
              "0  1   4    a\n",
              "1  2   5    c\n",
              "2  3   6    c"
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        "final_df = pd.DataFrame()\n",
        "for i_list, dfi_list in enumerate(df_list):\n",
        "  final_df = pd.concat([final_df, dfi_list], ignore_index=True)\n",
        "\n",
        "final_df.shape"
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        "id": "eAPVFfeGUVm0",
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            "text/plain": [
              "(30786752, 11)"
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          "metadata": {},
          "execution_count": 39
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      "source": [
        "#final_df.head()\n",
        "final_df[final_df['Number'] == 127293433]"
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            "text/plain": [
              "             Number Total duration  Bike number          End date  \\\n",
              "21722499  127293433        15m 45s        57158  2022-12-05 00:14   \n",
              "\n",
              "         End station number                              End station  \\\n",
              "21722499               1182  Notting Hill Gate Station, Notting Hill   \n",
              "\n",
              "                Start date Start station number                Start station  \\\n",
              "21722499  2022-12-04 23:58                 1152  Marylebone Lane, Marylebone   \n",
              "\n",
              "         Bike model  Total duration (ms)  \n",
              "21722499    CLASSIC             945616.0  "
            ],
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              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-97322eb5-3bd9-4fe7-bf2d-8bf15ea376c2 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-97322eb5-3bd9-4fe7-bf2d-8bf15ea376c2');\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",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "repr_error": "0"
            }
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_list[5].head(4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 261
        },
        "id": "viOrDn_wig1E",
        "outputId": "96e4eebe-2743-4394-b9f2-f4db24c60756"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Number  Total duration  Bike number          End date  \\\n",
              "0  105305967            7260        18247  07/02/2021 21:32   \n",
              "1  105246421            4140        16694  03/02/2021 20:28   \n",
              "2  105320173             720        17329  09/02/2021 19:39   \n",
              "3  105255530             300         9078  04/02/2021 15:49   \n",
              "\n",
              "   End station number                                   End station  \\\n",
              "0                 785  Aquatic Centre, Queen Elizabeth Olympic Park   \n",
              "1                 785  Aquatic Centre, Queen Elizabeth Olympic Park   \n",
              "2                  57                  Guilford Street , Bloomsbury   \n",
              "3                 386                             Moor Street, Soho   \n",
              "\n",
              "         Start date  Start station number  \\\n",
              "0  07/02/2021 19:31                   785   \n",
              "1  03/02/2021 19:19                   785   \n",
              "2  09/02/2021 19:27                   804   \n",
              "3  04/02/2021 15:44                    88   \n",
              "\n",
              "                                  Start station  \n",
              "0  Aquatic Centre, Queen Elizabeth Olympic Park  \n",
              "1  Aquatic Centre, Queen Elizabeth Olympic Park  \n",
              "2                      Good's Way, King's Cross  \n",
              "3                    Bayley Street , Bloomsbury  "
            ],
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              "      <th></th>\n",
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              "      <th>Start date</th>\n",
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              "  </thead>\n",
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              "      <th>0</th>\n",
              "      <td>105305967</td>\n",
              "      <td>7260</td>\n",
              "      <td>18247</td>\n",
              "      <td>07/02/2021 21:32</td>\n",
              "      <td>785</td>\n",
              "      <td>Aquatic Centre, Queen Elizabeth Olympic Park</td>\n",
              "      <td>07/02/2021 19:31</td>\n",
              "      <td>785</td>\n",
              "      <td>Aquatic Centre, Queen Elizabeth Olympic Park</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>105246421</td>\n",
              "      <td>4140</td>\n",
              "      <td>16694</td>\n",
              "      <td>03/02/2021 20:28</td>\n",
              "      <td>785</td>\n",
              "      <td>Aquatic Centre, Queen Elizabeth Olympic Park</td>\n",
              "      <td>03/02/2021 19:19</td>\n",
              "      <td>785</td>\n",
              "      <td>Aquatic Centre, Queen Elizabeth Olympic Park</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>105320173</td>\n",
              "      <td>720</td>\n",
              "      <td>17329</td>\n",
              "      <td>09/02/2021 19:39</td>\n",
              "      <td>57</td>\n",
              "      <td>Guilford Street , Bloomsbury</td>\n",
              "      <td>09/02/2021 19:27</td>\n",
              "      <td>804</td>\n",
              "      <td>Good's Way, King's Cross</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>105255530</td>\n",
              "      <td>300</td>\n",
              "      <td>9078</td>\n",
              "      <td>04/02/2021 15:49</td>\n",
              "      <td>386</td>\n",
              "      <td>Moor Street, Soho</td>\n",
              "      <td>04/02/2021 15:44</td>\n",
              "      <td>88</td>\n",
              "      <td>Bayley Street , Bloomsbury</td>\n",
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              "  </svg>\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "\n",
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              "      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",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
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              "      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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              "      const buttonEl =\n",
              "        document.querySelector('#df-502b3d40-66b3-420c-af5a-2e40a53a2e20 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-502b3d40-66b3-420c-af5a-2e40a53a2e20');\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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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-a6661a47-8e20-4e5b-b558-f4a0fdbf9ef0 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_list[5]\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 36506,\n        \"min\": 105246421,\n        \"max\": 105320173,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          105246421,\n          105255530,\n          105305967\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Total duration\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3260,\n        \"min\": 300,\n        \"max\": 7260,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          4140,\n          300,\n          7260\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Bike number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4221,\n        \"min\": 9078,\n        \"max\": 18247,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          16694,\n          9078,\n          18247\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"End date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"03/02/2021 20:28\",\n          \"04/02/2021 15:49\",\n          \"07/02/2021 21:32\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"End station number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 351,\n        \"min\": 57,\n        \"max\": 785,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          785,\n          57,\n          386\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"End station\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Aquatic Centre, Queen Elizabeth Olympic Park\",\n          \"Guilford Street , Bloomsbury\",\n          \"Moor Street, Soho\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Start date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"03/02/2021 19:19\",\n          \"04/02/2021 15:44\",\n          \"07/02/2021 19:31\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Start station number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 351,\n        \"min\": 88,\n        \"max\": 804,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          785,\n          804,\n          88\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Start station\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Aquatic Centre, Queen Elizabeth Olympic Park\",\n          \"Good's Way, King's Cross\",\n          \"Bayley Street , Bloomsbury\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_list[140].head(4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 261
        },
        "id": "CWF7LtR9mZK2",
        "outputId": "64d77916-7024-4945-978d-a8f8f0410b84"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Number        Start date  Start station number            Start station  \\\n",
              "0  136236504  2023-12-14 23:59                  1052       Soho Square , Soho   \n",
              "1  136236505  2023-12-14 23:59                  1071    Tower Gardens , Tower   \n",
              "2  136236506  2023-12-14 23:59                200230  Maplin Street, Mile End   \n",
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          "metadata": {},
          "execution_count": 8
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    {
      "cell_type": "code",
      "source": [
        "pd_list = pd.DataFrame({'col':df_list})\n",
        "pd_list.head(5)"
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      "execution_count": null,
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        {
          "output_type": "execute_result",
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            "text/plain": [
              "                                                 col\n",
              "0         Rental Id  Duration  Bike Id          E...\n",
              "1         Rental Id  Duration  Bike Id          E...\n",
              "2         Rental Id  Duration  Bike Id          E...\n",
              "3         Rental Id  Duration  Bike Id          E...\n",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-9d8d395c-d6c2-4d3d-baaa-873b29f33437 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-9d8d395c-d6c2-4d3d-baaa-873b29f33437');\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",
              "\n",
              "\n",
              "<div id=\"df-01f0fbdb-3843-4c9a-9a66-11eb3dc002b9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-01f0fbdb-3843-4c9a-9a66-11eb3dc002b9')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-01f0fbdb-3843-4c9a-9a66-11eb3dc002b9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "pd_list",
              "summary": "{\n  \"name\": \"pd_list\",\n  \"rows\": 142,\n  \"fields\": [\n    {\n      \"column\": \"col\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "# Assuming df1 and df2 are your DataFrames\n",
        "\n",
        "# Concatenate the DataFrames along the rows\n",
        "#concatenated_df = pd.concat([df1, df2], ignore_index=True)\n",
        "\n",
        "#If you want to keep all columns from both DataFrames:\n",
        "#concatenated_df = pd.concat([df1, df2], ignore_index=True, sort=False)\n",
        "\n",
        "#If you want to keep only unique columns from both DataFrames:\n",
        "concatenated_df = pd.concat([df1, df2], ignore_index=True, sort=False).drop_duplicates()\n",
        "\n",
        "# ignore_index=True ensures that the index is reset to maintain a continuous index in the resulting DataFrame\n",
        "\n",
        "# Example:\n",
        "# df1:\n",
        "#    A  B  C\n",
        "# 0  1  2  3\n",
        "# 1  4  5  6\n",
        "\n",
        "# df2:\n",
        "#    A  C  D\n",
        "# 0  7  8  9\n",
        "# 1  10 11 12\n",
        "\n",
        "# concatenated_df:\n",
        "#     A   B   C     D\n",
        "# 0   1   2   3   NaN\n",
        "# 1   4   5   6   NaN\n",
        "# 2   7  NaN  8   9\n",
        "# 3  10  NaN  11  12\n"
      ],
      "metadata": {
        "id": "H4Uk74nzY8-k"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "dfs[141].head(1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 115
        },
        "id": "xFZatgwEbBd-",
        "outputId": "4ab9802a-1a1d-460f-bc94-02cb8e21d430"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Number        Start date  Start station number  \\\n",
              "0  136450327  2023-12-31 23:59                  3433   \n",
              "\n",
              "                     Start station          End date  End station number  \\\n",
              "0  Sadlers Sports Centre, Finsbury  2024-01-01 00:19                3433   \n",
              "\n",
              "                       End station  Bike number Bike model Total duration  \\\n",
              "0  Sadlers Sports Centre, Finsbury        17711    CLASSIC         20m 6s   \n",
              "\n",
              "   Total duration (ms)  \n",
              "0              1206838  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-5bd7d857-fafb-4ae4-b24e-fd9d3fb18729\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Number</th>\n",
              "      <th>Start date</th>\n",
              "      <th>Start station number</th>\n",
              "      <th>Start station</th>\n",
              "      <th>End date</th>\n",
              "      <th>End station number</th>\n",
              "      <th>End station</th>\n",
              "      <th>Bike number</th>\n",
              "      <th>Bike model</th>\n",
              "      <th>Total duration</th>\n",
              "      <th>Total duration (ms)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>136450327</td>\n",
              "      <td>2023-12-31 23:59</td>\n",
              "      <td>3433</td>\n",
              "      <td>Sadlers Sports Centre, Finsbury</td>\n",
              "      <td>2024-01-01 00:19</td>\n",
              "      <td>3433</td>\n",
              "      <td>Sadlers Sports Centre, Finsbury</td>\n",
              "      <td>17711</td>\n",
              "      <td>CLASSIC</td>\n",
              "      <td>20m 6s</td>\n",
              "      <td>1206838</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5bd7d857-fafb-4ae4-b24e-fd9d3fb18729')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-5bd7d857-fafb-4ae4-b24e-fd9d3fb18729 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-5bd7d857-fafb-4ae4-b24e-fd9d3fb18729');\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",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"dfs[141]\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"Number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 136450327,\n        \"max\": 136450327,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          136450327\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Start date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"2023-12-31 23:59\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Start station number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 3433,\n        \"max\": 3433,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          3433\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Start station\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Sadlers Sports Centre, Finsbury\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"End date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"2024-01-01 00:19\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"End station number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 3433,\n        \"max\": 3433,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          3433\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"End station\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Sadlers Sports Centre, Finsbury\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Bike number\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 17711,\n        \"max\": 17711,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          17711\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Bike model\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"CLASSIC\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Total duration\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"20m 6s\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Total duration (ms)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1206838,\n        \"max\": 1206838,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1206838\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dfs[141].info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ihLPLlpHbI34",
        "outputId": "4a7de3a1-da89-4442-9af3-bf96f20284e6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 209428 entries, 0 to 209427\n",
            "Data columns (total 11 columns):\n",
            " #   Column                Non-Null Count   Dtype \n",
            "---  ------                --------------   ----- \n",
            " 0   Number                209428 non-null  int64 \n",
            " 1   Start date            209428 non-null  object\n",
            " 2   Start station number  209428 non-null  int64 \n",
            " 3   Start station         209428 non-null  object\n",
            " 4   End date              209428 non-null  object\n",
            " 5   End station number    209428 non-null  int64 \n",
            " 6   End station           209428 non-null  object\n",
            " 7   Bike number           209428 non-null  int64 \n",
            " 8   Bike model            209428 non-null  object\n",
            " 9   Total duration        209428 non-null  object\n",
            " 10  Total duration (ms)   209428 non-null  int64 \n",
            "dtypes: int64(5), object(6)\n",
            "memory usage: 17.6+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dfs[21].info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "x767fDkRcOPT",
        "outputId": "99e0ec16-6293-45d3-fbf6-bd860a817f6e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 296473 entries, 0 to 296472\n",
            "Data columns (total 9 columns):\n",
            " #   Column             Non-Null Count   Dtype \n",
            "---  ------             --------------   ----- \n",
            " 0   Rental Id          296473 non-null  int64 \n",
            " 1   Duration           296473 non-null  int64 \n",
            " 2   Bike Id            296473 non-null  int64 \n",
            " 3   End Date           296473 non-null  object\n",
            " 4   EndStation Id      296473 non-null  int64 \n",
            " 5   EndStation Name    296473 non-null  object\n",
            " 6   Start Date         296473 non-null  object\n",
            " 7   StartStation Id    296473 non-null  int64 \n",
            " 8   StartStation Name  296473 non-null  object\n",
            "dtypes: int64(5), object(4)\n",
            "memory usage: 20.4+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dfs[141].head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 310
        },
        "id": "mqgHg2NFdrQU",
        "outputId": "b57b69d9-08f5-4be4-c571-ba457341e0e0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "      Number        Start date  Start station number  \\\n",
              "0  136450327  2023-12-31 23:59                  3433   \n",
              "1  136450328  2023-12-31 23:59                200094   \n",
              "2  136450329  2023-12-31 23:59                  1196   \n",
              "3  136450330  2023-12-31 23:59                  1220   \n",
              "4  136450331  2023-12-31 23:59                   964   \n",
              "\n",
              "                     Start station          End date  End station number  \\\n",
              "0  Sadlers Sports Centre, Finsbury  2024-01-01 00:19                3433   \n",
              "1        St. Bride Street, Holborn  2024-01-01 00:50                1135   \n",
              "2      Vincent Square, Westminster  2024-01-01 00:16                1196   \n",
              "3  Imperial College, Knightsbridge  2024-01-01 00:12                3464   \n",
              "4          Bath Street, St. Luke's  2024-01-01 00:32                3437   \n",
              "\n",
              "                       End station  Bike number Bike model Total duration  \\\n",
              "0  Sadlers Sports Centre, Finsbury        17711    CLASSIC         20m 6s   \n",
              "1        Claverton Street, Pimlico        30722    CLASSIC        51m 11s   \n",
              "2      Vincent Square, Westminster        52107    CLASSIC         17m 3s   \n",
              "3            Green Street, Mayfair        58456    CLASSIC        12m 51s   \n",
              "4           Curzon Street, Mayfair        50838    CLASSIC        32m 25s   \n",
              "\n",
              "   Total duration (ms)  \n",
              "0              1206838  \n",
              "1              3071423  \n",
              "2              1023305  \n",
              "3               771575  \n",
              "4              1945176  "
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          "metadata": {},
          "execution_count": 15
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    },
    {
      "cell_type": "code",
      "source": [
        "dfs[21].head(4)"
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        "id": "uezkF58KfcVV",
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      "execution_count": null,
      "outputs": [
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            "text/plain": [
              "   Rental Id  Duration  Bike Id          End Date  EndStation Id  \\\n",
              "0  108236168      1080      461  28/05/2021 09:17            452   \n",
              "1  108248572       840    19135  28/05/2021 15:32            841   \n",
              "2  108240926      1140    20426  28/05/2021 12:11            624   \n",
              "3  108165670       420    18717  26/05/2021 09:03            772   \n",
              "\n",
              "                   EndStation Name        Start Date  StartStation Id  \\\n",
              "0       St. Katharine's Way, Tower  28/05/2021 08:59              134   \n",
              "1          Tower Wharf, Bermondsey  28/05/2021 15:18              134   \n",
              "2  Courland Grove, Wandsworth Road  28/05/2021 11:52              624   \n",
              "3         Binfield Road, Stockwell  26/05/2021 08:56              624   \n",
              "\n",
              "                 StartStation Name  \n",
              "0     Wapping High Street, Wapping  \n",
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              "2  Courland Grove, Wandsworth Road  \n",
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              "      <td>28/05/2021 15:18</td>\n",
              "      <td>134</td>\n",
              "      <td>Wapping High Street, Wapping</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>108240926</td>\n",
              "      <td>1140</td>\n",
              "      <td>20426</td>\n",
              "      <td>28/05/2021 12:11</td>\n",
              "      <td>624</td>\n",
              "      <td>Courland Grove, Wandsworth Road</td>\n",
              "      <td>28/05/2021 11:52</td>\n",
              "      <td>624</td>\n",
              "      <td>Courland Grove, Wandsworth Road</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>108165670</td>\n",
              "      <td>420</td>\n",
              "      <td>18717</td>\n",
              "      <td>26/05/2021 09:03</td>\n",
              "      <td>772</td>\n",
              "      <td>Binfield Road, Stockwell</td>\n",
              "      <td>26/05/2021 08:56</td>\n",
              "      <td>624</td>\n",
              "      <td>Courland Grove, Wandsworth Road</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"dfs[21]\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Rental Id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 38450,\n        \"min\": 108165670,\n        \"max\": 108248572,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          108248572,\n          108165670,\n          108236168\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Duration\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 326,\n        \"min\": 420,\n        \"max\": 1140,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          840,\n          420,\n          1080\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Bike Id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 9510,\n        \"min\": 461,\n        \"max\": 20426,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          19135,\n          18717,\n          461\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"End Date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"28/05/2021 15:32\",\n          \"26/05/2021 09:03\",\n          \"28/05/2021 09:17\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"EndStation Id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 172,\n        \"min\": 452,\n        \"max\": 841,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          841,\n          772,\n          452\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"EndStation Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Tower Wharf, Bermondsey\",\n          \"Binfield Road, Stockwell\",\n          \"St. Katharine's Way, Tower\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Start Date\",\n      \"properties\": {\n        \"dtype\": \"object\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"28/05/2021 15:18\",\n          \"26/05/2021 08:56\",\n          \"28/05/2021 08:59\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"StartStation Id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 282,\n        \"min\": 134,\n        \"max\": 624,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          624,\n          134\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"StartStation Name\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Courland Grove, Wandsworth Road\",\n          \"Wapping High Street, Wapping\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(dfs)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OvMpkyf4cprW",
        "outputId": "98db16d3-c9cb-4012-8d32-7b941de8286c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "142"
            ]
          },
          "metadata": {},
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Step 3: Merge DataFrames\n",
        "merged_df = pd.concat(dfs, ignore_index=True)\n",
        "\n"
      ],
      "metadata": {
        "id": "1D0Ga-YicRxo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "merged_df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OR4k1PBGc3tX",
        "outputId": "f9442445-1e2c-47c9-8abc-858565fb924b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(30786752, 20)"
            ]
          },
          "metadata": {},
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "merged_df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 469
        },
        "id": "Wzz_1KXJdQx4",
        "outputId": "d3a90c88-c663-49b5-8148-7aee11d6e000"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Rental Id  Duration  Bike Id          End Date  EndStation Id  \\\n",
              "0  104820582.0    1620.0     22.0  03/01/2021 15:14           11.0   \n",
              "1  104816169.0    1740.0  10755.0  03/01/2021 13:26          542.0   \n",
              "2  104757113.0    1620.0  18908.0  30/12/2020 15:00          239.0   \n",
              "3  104749458.0     780.0  18499.0  30/12/2020 09:21          766.0   \n",
              "4  104788389.0    5400.0  15668.0  01/01/2021 16:29          655.0   \n",
              "\n",
              "                 EndStation Name        Start Date  StartStation Id  \\\n",
              "0   Brunswick Square, Bloomsbury  03/01/2021 14:47            542.0   \n",
              "1         Salmon Lane, Limehouse  03/01/2021 12:57            546.0   \n",
              "2  Warren Street Station, Euston  30/12/2020 14:33            779.0   \n",
              "3         Ram Street, Wandsworth  30/12/2020 09:08            653.0   \n",
              "4          Crabtree Lane, Fulham  01/01/2021 14:59            655.0   \n",
              "\n",
              "                  StartStation Name  Number Start date Start station number  \\\n",
              "0            Salmon Lane, Limehouse     NaN        NaN                  NaN   \n",
              "1          New Fetter Lane, Holborn     NaN        NaN                  NaN   \n",
              "2              Houndsditch, Aldgate     NaN        NaN                  NaN   \n",
              "3  Simpson Street, Clapham Junction     NaN        NaN                  NaN   \n",
              "4             Crabtree Lane, Fulham     NaN        NaN                  NaN   \n",
              "\n",
              "  Start station End date End station number End station  Bike number  \\\n",
              "0           NaN      NaN                NaN         NaN          NaN   \n",
              "1           NaN      NaN                NaN         NaN          NaN   \n",
              "2           NaN      NaN                NaN         NaN          NaN   \n",
              "3           NaN      NaN                NaN         NaN          NaN   \n",
              "4           NaN      NaN                NaN         NaN          NaN   \n",
              "\n",
              "  Bike model Total duration  Total duration (ms)  \n",
              "0        NaN            NaN                  NaN  \n",
              "1        NaN            NaN                  NaN  \n",
              "2        NaN            NaN                  NaN  \n",
              "3        NaN            NaN                  NaN  \n",
              "4        NaN            NaN                  NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ec83d37f-dc28-48c2-8b1c-dc0c4ccdff5e\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Rental Id</th>\n",
              "      <th>Duration</th>\n",
              "      <th>Bike Id</th>\n",
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              "      <th>EndStation Id</th>\n",
              "      <th>EndStation Name</th>\n",
              "      <th>Start Date</th>\n",
              "      <th>StartStation Id</th>\n",
              "      <th>StartStation Name</th>\n",
              "      <th>Number</th>\n",
              "      <th>Start date</th>\n",
              "      <th>Start station number</th>\n",
              "      <th>Start station</th>\n",
              "      <th>End date</th>\n",
              "      <th>End station number</th>\n",
              "      <th>End station</th>\n",
              "      <th>Bike number</th>\n",
              "      <th>Bike model</th>\n",
              "      <th>Total duration</th>\n",
              "      <th>Total duration (ms)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>104820582.0</td>\n",
              "      <td>1620.0</td>\n",
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              "      <td>11.0</td>\n",
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              "      <td>03/01/2021 14:47</td>\n",
              "      <td>542.0</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <th>1</th>\n",
              "      <td>104816169.0</td>\n",
              "      <td>1740.0</td>\n",
              "      <td>10755.0</td>\n",
              "      <td>03/01/2021 13:26</td>\n",
              "      <td>542.0</td>\n",
              "      <td>Salmon Lane, Limehouse</td>\n",
              "      <td>03/01/2021 12:57</td>\n",
              "      <td>546.0</td>\n",
              "      <td>New Fetter Lane, Holborn</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>104757113.0</td>\n",
              "      <td>1620.0</td>\n",
              "      <td>18908.0</td>\n",
              "      <td>30/12/2020 15:00</td>\n",
              "      <td>239.0</td>\n",
              "      <td>Warren Street Station, Euston</td>\n",
              "      <td>30/12/2020 14:33</td>\n",
              "      <td>779.0</td>\n",
              "      <td>Houndsditch, Aldgate</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>104749458.0</td>\n",
              "      <td>780.0</td>\n",
              "      <td>18499.0</td>\n",
              "      <td>30/12/2020 09:21</td>\n",
              "      <td>766.0</td>\n",
              "      <td>Ram Street, Wandsworth</td>\n",
              "      <td>30/12/2020 09:08</td>\n",
              "      <td>653.0</td>\n",
              "      <td>Simpson Street, Clapham Junction</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>104788389.0</td>\n",
              "      <td>5400.0</td>\n",
              "      <td>15668.0</td>\n",
              "      <td>01/01/2021 16:29</td>\n",
              "      <td>655.0</td>\n",
              "      <td>Crabtree Lane, Fulham</td>\n",
              "      <td>01/01/2021 14:59</td>\n",
              "      <td>655.0</td>\n",
              "      <td>Crabtree Lane, Fulham</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-ec83d37f-dc28-48c2-8b1c-dc0c4ccdff5e')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-ec83d37f-dc28-48c2-8b1c-dc0c4ccdff5e 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-ec83d37f-dc28-48c2-8b1c-dc0c4ccdff5e');\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",
              "\n",
              "\n",
              "<div id=\"df-50e4403d-29e8-4689-9c72-9eea4680a382\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-50e4403d-29e8-4689-9c72-9eea4680a382')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-50e4403d-29e8-4689-9c72-9eea4680a382 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "merged_df"
            }
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Step 4: Write the merged DataFrame to a new CSV file\n",
        "merged_df.to_csv(\"merged_file.csv\", index=False)\n",
        "\n",
        "print(\"Merged file created successfully.\")"
      ],
      "metadata": {
        "id": "it8wntAzcU2I"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}