Uber_Data_Pipeline.ipynb

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      "source": [
        "import io\n",
        "import pandas as pd\n",
        "import requests"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "id": "500446cc",
      "metadata": {
        "id": "500446cc"
      },
      "outputs": [],
      "source": [
        "url = 'https://storage.googleapis.com/uber-data-engineering-project/uber_data.csv'\n",
        "response = requests.get(url)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "id": "b37a1ace",
      "metadata": {
        "id": "b37a1ace"
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      "source": [
        "df = pd.read_csv(io.StringIO(response.text), sep=',')"
      ]
    },
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      "cell_type": "code",
      "execution_count": 4,
      "id": "edc6d495",
      "metadata": {
        "id": "edc6d495"
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      "outputs": [],
      "source": [
        "df['tpep_pickup_datetime'] = pd.to_datetime(df['tpep_pickup_datetime'])\n",
        "df['tpep_dropoff_datetime'] = pd.to_datetime(df['tpep_dropoff_datetime'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "id": "4d0c8281",
      "metadata": {
        "id": "4d0c8281"
      },
      "outputs": [],
      "source": [
        "#Remove duplicates\n",
        "df = df.drop_duplicates().reset_index(drop=True)\n",
        "df['trip_id'] = df.index"
      ]
    },
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              "   VendorID tpep_pickup_datetime tpep_dropoff_datetime  passenger_count  \\\n",
              "0         1           2016-03-01   2016-03-01 00:07:55                1   \n",
              "1         1           2016-03-01   2016-03-01 00:11:06                1   \n",
              "2         2           2016-03-01   2016-03-01 00:31:06                2   \n",
              "3         2           2016-03-01   2016-03-01 00:00:00                3   \n",
              "4         2           2016-03-01   2016-03-01 00:00:00                5   \n",
              "\n",
              "   trip_distance  pickup_longitude  pickup_latitude  RatecodeID  \\\n",
              "0           2.50        -73.976746        40.765152           1   \n",
              "1           2.90        -73.983482        40.767925           1   \n",
              "2          19.98        -73.782021        40.644810           1   \n",
              "3          10.78        -73.863419        40.769814           1   \n",
              "4          30.43        -73.971741        40.792183           3   \n",
              "\n",
              "  store_and_fwd_flag  dropoff_longitude  dropoff_latitude  payment_type  \\\n",
              "0                  N         -74.004265         40.746128             1   \n",
              "1                  N         -74.005943         40.733166             1   \n",
              "2                  N         -73.974541         40.675770             1   \n",
              "3                  N         -73.969650         40.757767             1   \n",
              "4                  N         -74.177170         40.695053             1   \n",
              "\n",
              "   fare_amount  extra  mta_tax  tip_amount  tolls_amount  \\\n",
              "0          9.0    0.5      0.5        2.05          0.00   \n",
              "1         11.0    0.5      0.5        3.05          0.00   \n",
              "2         54.5    0.5      0.5        8.00          0.00   \n",
              "3         31.5    0.0      0.5        3.78          5.54   \n",
              "4         98.0    0.0      0.0        0.00         15.50   \n",
              "\n",
              "   improvement_surcharge  total_amount  trip_id  \n",
              "0                    0.3         12.35        0  \n",
              "1                    0.3         15.35        1  \n",
              "2                    0.3         63.80        2  \n",
              "3                    0.3         41.62        3  \n",
              "4                    0.3        113.80        4  "
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            "text/plain": [
              "   datetime_id tpep_pickup_datetime  pick_hour  pick_day  pick_month  \\\n",
              "0            0           2016-03-01          0         1           3   \n",
              "1            1           2016-03-01          0         1           3   \n",
              "2            2           2016-03-01          0         1           3   \n",
              "3            3           2016-03-01          0         1           3   \n",
              "4            4           2016-03-01          0         1           3   \n",
              "\n",
              "   pick_year  pick_weekday tpep_dropoff_datetime  drop_hour  drop_day  \\\n",
              "0       2016             1   2016-03-01 00:07:55          0         1   \n",
              "1       2016             1   2016-03-01 00:11:06          0         1   \n",
              "2       2016             1   2016-03-01 00:31:06          0         1   \n",
              "3       2016             1   2016-03-01 00:00:00          0         1   \n",
              "4       2016             1   2016-03-01 00:00:00          0         1   \n",
              "\n",
              "   drop_month  drop_year  drop_weekday  \n",
              "0           3       2016             1  \n",
              "1           3       2016             1  \n",
              "2           3       2016             1  \n",
              "3           3       2016             1  \n",
              "4           3       2016             1  "
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              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-03-01 00:11:06</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-03-01 00:31:06</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-03-01 00:00:00</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>2016-03-01</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-03-01 00:00:00</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2016</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7012bea0-7f61-4e71-8500-07db2c0389ab')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-673dd824-51de-4525-9bb7-dcac0e4f3a2f\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-673dd824-51de-4525-9bb7-dcac0e4f3a2f')\"\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",
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              "        <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",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\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-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart: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",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-673dd824-51de-4525-9bb7-dcac0e4f3a2f button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-7012bea0-7f61-4e71-8500-07db2c0389ab 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-7012bea0-7f61-4e71-8500-07db2c0389ab');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "#For storing date and time,we need to assign hour,day,month,year and weekday so we are assigning for both drop and pick up with datetime_dim[] parameter\n",
        "datetime_dim = df[['tpep_pickup_datetime','tpep_dropoff_datetime']].reset_index(drop=True)\n",
        "datetime_dim['tpep_pickup_datetime'] = datetime_dim['tpep_pickup_datetime']\n",
        "datetime_dim['pick_hour'] = datetime_dim['tpep_pickup_datetime'].dt.hour\n",
        "datetime_dim['pick_day'] = datetime_dim['tpep_pickup_datetime'].dt.day\n",
        "datetime_dim['pick_month'] = datetime_dim['tpep_pickup_datetime'].dt.month\n",
        "datetime_dim['pick_year'] = datetime_dim['tpep_pickup_datetime'].dt.year\n",
        "datetime_dim['pick_weekday'] = datetime_dim['tpep_pickup_datetime'].dt.weekday\n",
        "\n",
        "datetime_dim['tpep_dropoff_datetime'] = datetime_dim['tpep_dropoff_datetime']\n",
        "datetime_dim['drop_hour'] = datetime_dim['tpep_dropoff_datetime'].dt.hour\n",
        "datetime_dim['drop_day'] = datetime_dim['tpep_dropoff_datetime'].dt.day\n",
        "datetime_dim['drop_month'] = datetime_dim['tpep_dropoff_datetime'].dt.month\n",
        "datetime_dim['drop_year'] = datetime_dim['tpep_dropoff_datetime'].dt.year\n",
        "datetime_dim['drop_weekday'] = datetime_dim['tpep_dropoff_datetime'].dt.weekday\n",
        "\n",
        "\n",
        "datetime_dim['datetime_id'] = datetime_dim.index\n",
        "\n",
        "# datetime_dim = datetime_dim.rename(columns={'tpep_pickup_datetime': 'datetime_id'}).reset_index(drop=True)\n",
        "datetime_dim = datetime_dim[['datetime_id', 'tpep_pickup_datetime', 'pick_hour', 'pick_day', 'pick_month', 'pick_year', 'pick_weekday',\n",
        "                             'tpep_dropoff_datetime', 'drop_hour', 'drop_day', 'drop_month', 'drop_year', 'drop_weekday']]\n",
        "#\n",
        "datetime_dim.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "id": "ba67912f",
      "metadata": {
        "id": "ba67912f"
      },
      "outputs": [],
      "source": [
        "#Count the number of passengers and distance with distance id and distance\n",
        "passenger_count_dim = df[['passenger_count']].reset_index(drop=True)\n",
        "passenger_count_dim['passenger_count_id'] = passenger_count_dim.index\n",
        "passenger_count_dim = passenger_count_dim[['passenger_count_id','passenger_count']]\n",
        "\n",
        "trip_distance_dim = df[['trip_distance']].reset_index(drop=True)\n",
        "trip_distance_dim['trip_distance_id'] = trip_distance_dim.index\n",
        "trip_distance_dim = trip_distance_dim[['trip_distance_id','trip_distance']]\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "id": "fb7c9704",
      "metadata": {
        "id": "fb7c9704"
      },
      "outputs": [],
      "source": [
        "#Create method rate_code_type and define the value by assigning values to name_type as per yellow dictionary\n",
        "rate_code_type = {\n",
        "    1:\"Standard rate\",\n",
        "    2:\"JFK\",\n",
        "    3:\"Newark\",\n",
        "    4:\"Nassau or Westchester\",\n",
        "    5:\"Negotiated fare\",\n",
        "    6:\"Group ride\"\n",
        "}\n",
        "\n",
        "rate_code_dim = df[['RatecodeID']].reset_index(drop=True)\n",
        "rate_code_dim['rate_code_id'] = rate_code_dim.index\n",
        "rate_code_dim['rate_code_name'] = rate_code_dim['RatecodeID'].map(rate_code_type)\n",
        "rate_code_dim = rate_code_dim[['rate_code_id','RatecodeID','rate_code_name']]\n",
        "\n",
        "# rate_code_dim.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "id": "4db826a1",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "4db826a1",
        "outputId": "2a6664c0-6d79-4367-e02d-73a32cf94eee"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   rate_code_id  RatecodeID rate_code_name\n",
              "0             0           1  Standard rate\n",
              "1             1           1  Standard rate\n",
              "2             2           1  Standard rate\n",
              "3             3           1  Standard rate\n",
              "4             4           3         Newark"
            ],
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              "      <th>rate_code_id</th>\n",
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              "      <th>0</th>\n",
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              "      <td>Standard rate</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>Standard rate</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
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              "      <th>4</th>\n",
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              "      <td>Newark</td>\n",
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              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-3aedeb0d-64d9-4bb7-a53d-eab37f038b4b')\"\n",
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              "      </button>\n",
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              "  .colab-df-quickchart: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",
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              "  [theme=dark] .colab-df-quickchart {\n",
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              "  [theme=dark] .colab-df-quickchart:hover {\n",
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              "    filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
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              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "    domScope.querySelector('#df-ece3838c-52da-4f58-b9a9-8261b2bad6ad button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
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              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
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              "\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-3aedeb0d-64d9-4bb7-a53d-eab37f038b4b 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-3aedeb0d-64d9-4bb7-a53d-eab37f038b4b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "rate_code_dim.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "id": "8048bdef",
      "metadata": {
        "id": "8048bdef"
      },
      "outputs": [],
      "source": [
        "pickup_location_dim = df[['pickup_longitude', 'pickup_latitude']].reset_index(drop=True)\n",
        "pickup_location_dim['pickup_location_id'] = pickup_location_dim.index\n",
        "pickup_location_dim = pickup_location_dim[['pickup_location_id','pickup_latitude','pickup_longitude']]\n",
        "\n",
        "\n",
        "dropoff_location_dim = df[['dropoff_longitude', 'dropoff_latitude']].reset_index(drop=True)\n",
        "dropoff_location_dim['dropoff_location_id'] = dropoff_location_dim.index\n",
        "dropoff_location_dim = dropoff_location_dim[['dropoff_location_id','dropoff_latitude','dropoff_longitude']]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "id": "bfb04993",
      "metadata": {
        "id": "bfb04993"
      },
      "outputs": [],
      "source": [
        "#Create the method payment_type_name and assign type for values such as 1 to'credit card'\n",
        "payment_type_name = {\n",
        "    1:\"Credit card\",\n",
        "    2:\"Cash\",\n",
        "    3:\"No charge\",\n",
        "    4:\"Dispute\",\n",
        "    5:\"Unknown\",\n",
        "    6:\"Voided trip\"\n",
        "}\n",
        "payment_type_dim = df[['payment_type']].reset_index(drop=True)\n",
        "payment_type_dim['payment_type_id'] = payment_type_dim.index\n",
        "payment_type_dim['payment_type_name'] = payment_type_dim['payment_type'].map(payment_type_name)\n",
        "payment_type_dim = payment_type_dim[['payment_type_id','payment_type','payment_type_name']]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "id": "e747865b",
      "metadata": {
        "id": "e747865b"
      },
      "outputs": [],
      "source": [
        "#Create fact table - The primary key value comes under fact table so we are taking all id types here...\n",
        "fact_table = df.merge(passenger_count_dim, left_on='trip_id', right_on='passenger_count_id') \\\n",
        "             .merge(trip_distance_dim, left_on='trip_id', right_on='trip_distance_id') \\\n",
        "             .merge(rate_code_dim, left_on='trip_id', right_on='rate_code_id') \\\n",
        "             .merge(pickup_location_dim, left_on='trip_id', right_on='pickup_location_id') \\\n",
        "             .merge(dropoff_location_dim, left_on='trip_id', right_on='dropoff_location_id')\\\n",
        "             .merge(datetime_dim, left_on='trip_id', right_on='datetime_id') \\\n",
        "             .merge(payment_type_dim, left_on='trip_id', right_on='payment_type_id') \\\n",
        "             [['trip_id','VendorID', 'datetime_id', 'passenger_count_id',\n",
        "               'trip_distance_id', 'rate_code_id', 'store_and_fwd_flag', 'pickup_location_id', 'dropoff_location_id',\n",
        "               'payment_type_id', 'fare_amount', 'extra', 'mta_tax', 'tip_amount', 'tolls_amount',\n",
        "               'improvement_surcharge', 'total_amount']]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "id": "9acdb41a",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9acdb41a",
        "outputId": "ef107a75-a193-46f2-aec1-fdaf180373f5"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['payment_type_id', 'payment_type', 'payment_type_name'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ],
      "source": [
        "payment_type_dim.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "id": "62e05477",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "62e05477",
        "outputId": "9f4528fb-ecab-4b8a-f751-c37b79848d91"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['trip_id', 'VendorID', 'datetime_id', 'passenger_count_id',\n",
              "       'trip_distance_id', 'rate_code_id', 'store_and_fwd_flag',\n",
              "       'pickup_location_id', 'dropoff_location_id', 'payment_type_id',\n",
              "       'fare_amount', 'extra', 'mta_tax', 'tip_amount', 'tolls_amount',\n",
              "       'improvement_surcharge', 'total_amount'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ],
      "source": [
        "fact_table.columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "id": "254ff9ad",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "254ff9ad",
        "outputId": "d69f8081-8d4a-4311-b1d8-367e2351707b"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "       trip_id  VendorID  datetime_id  passenger_count_id  trip_distance_id  \\\n",
              "0            0         1            0                   0                 0   \n",
              "1            1         1            1                   1                 1   \n",
              "2            2         2            2                   2                 2   \n",
              "3            3         2            3                   3                 3   \n",
              "4            4         2            4                   4                 4   \n",
              "...        ...       ...          ...                 ...               ...   \n",
              "99995    99995         1        99995               99995             99995   \n",
              "99996    99996         1        99996               99996             99996   \n",
              "99997    99997         1        99997               99997             99997   \n",
              "99998    99998         2        99998               99998             99998   \n",
              "99999    99999         1        99999               99999             99999   \n",
              "\n",
              "       rate_code_id store_and_fwd_flag  pickup_location_id  \\\n",
              "0                 0                  N                   0   \n",
              "1                 1                  N                   1   \n",
              "2                 2                  N                   2   \n",
              "3                 3                  N                   3   \n",
              "4                 4                  N                   4   \n",
              "...             ...                ...                 ...   \n",
              "99995         99995                  N               99995   \n",
              "99996         99996                  N               99996   \n",
              "99997         99997                  N               99997   \n",
              "99998         99998                  N               99998   \n",
              "99999         99999                  N               99999   \n",
              "\n",
              "       dropoff_location_id  payment_type_id  fare_amount  extra  mta_tax  \\\n",
              "0                        0                0          9.0    0.5      0.5   \n",
              "1                        1                1         11.0    0.5      0.5   \n",
              "2                        2                2         54.5    0.5      0.5   \n",
              "3                        3                3         31.5    0.0      0.5   \n",
              "4                        4                4         98.0    0.0      0.0   \n",
              "...                    ...              ...          ...    ...      ...   \n",
              "99995                99995            99995          5.0    0.0      0.5   \n",
              "99996                99996            99996         14.0    0.0      0.5   \n",
              "99997                99997            99997         29.0    0.0      0.5   \n",
              "99998                99998            99998          5.5    0.5      0.5   \n",
              "99999                99999            99999          6.0    0.0      0.5   \n",
              "\n",
              "       tip_amount  tolls_amount  improvement_surcharge  total_amount  \n",
              "0            2.05          0.00                    0.3         12.35  \n",
              "1            3.05          0.00                    0.3         15.35  \n",
              "2            8.00          0.00                    0.3         63.80  \n",
              "3            3.78          5.54                    0.3         41.62  \n",
              "4            0.00         15.50                    0.3        113.80  \n",
              "...           ...           ...                    ...           ...  \n",
              "99995        0.00          0.00                    0.3          5.80  \n",
              "99996        2.00          0.00                    0.3         16.80  \n",
              "99997        8.80          5.54                    0.3         44.14  \n",
              "99998        1.36          0.00                    0.3          8.16  \n",
              "99999        0.00          0.00                    0.3          6.80  \n",
              "\n",
              "[100000 rows x 17 columns]"
            ],
            "text/html": [
              "\n",
              "\n",
              "  <div id=\"df-c9be69e4-b11d-4315-afd2-17846c7f5ed0\">\n",
              "    <div 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",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>trip_id</th>\n",
              "      <th>VendorID</th>\n",
              "      <th>datetime_id</th>\n",
              "      <th>passenger_count_id</th>\n",
              "      <th>trip_distance_id</th>\n",
              "      <th>rate_code_id</th>\n",
              "      <th>store_and_fwd_flag</th>\n",
              "      <th>pickup_location_id</th>\n",
              "      <th>dropoff_location_id</th>\n",
              "      <th>payment_type_id</th>\n",
              "      <th>fare_amount</th>\n",
              "      <th>extra</th>\n",
              "      <th>mta_tax</th>\n",
              "      <th>tip_amount</th>\n",
              "      <th>tolls_amount</th>\n",
              "      <th>improvement_surcharge</th>\n",
              "      <th>total_amount</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>N</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>2.05</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.3</td>\n",
              "      <td>12.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>11.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>3.05</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.3</td>\n",
              "      <td>15.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>N</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>54.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>8.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.3</td>\n",
              "      <td>63.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>N</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>31.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>3.78</td>\n",
              "      <td>5.54</td>\n",
              "      <td>0.3</td>\n",
              "      <td>41.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>N</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>98.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>15.50</td>\n",
              "      <td>0.3</td>\n",
              "      <td>113.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99995</th>\n",
              "      <td>99995</td>\n",
              "      <td>1</td>\n",
              "      <td>99995</td>\n",
              "      <td>99995</td>\n",
              "      <td>99995</td>\n",
              "      <td>99995</td>\n",
              "      <td>N</td>\n",
              "      <td>99995</td>\n",
              "      <td>99995</td>\n",
              "      <td>99995</td>\n",
              "      <td>5.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.3</td>\n",
              "      <td>5.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99996</th>\n",
              "      <td>99996</td>\n",
              "      <td>1</td>\n",
              "      <td>99996</td>\n",
              "      <td>99996</td>\n",
              "      <td>99996</td>\n",
              "      <td>99996</td>\n",
              "      <td>N</td>\n",
              "      <td>99996</td>\n",
              "      <td>99996</td>\n",
              "      <td>99996</td>\n",
              "      <td>14.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>2.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.3</td>\n",
              "      <td>16.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99997</th>\n",
              "      <td>99997</td>\n",
              "      <td>1</td>\n",
              "      <td>99997</td>\n",
              "      <td>99997</td>\n",
              "      <td>99997</td>\n",
              "      <td>99997</td>\n",
              "      <td>N</td>\n",
              "      <td>99997</td>\n",
              "      <td>99997</td>\n",
              "      <td>99997</td>\n",
              "      <td>29.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>8.80</td>\n",
              "      <td>5.54</td>\n",
              "      <td>0.3</td>\n",
              "      <td>44.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99998</th>\n",
              "      <td>99998</td>\n",
              "      <td>2</td>\n",
              "      <td>99998</td>\n",
              "      <td>99998</td>\n",
              "      <td>99998</td>\n",
              "      <td>99998</td>\n",
              "      <td>N</td>\n",
              "      <td>99998</td>\n",
              "      <td>99998</td>\n",
              "      <td>99998</td>\n",
              "      <td>5.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.36</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.3</td>\n",
              "      <td>8.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>99999</th>\n",
              "      <td>99999</td>\n",
              "      <td>1</td>\n",
              "      <td>99999</td>\n",
              "      <td>99999</td>\n",
              "      <td>99999</td>\n",
              "      <td>99999</td>\n",
              "      <td>N</td>\n",
              "      <td>99999</td>\n",
              "      <td>99999</td>\n",
              "      <td>99999</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.3</td>\n",
              "      <td>6.80</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>100000 rows × 17 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c9be69e4-b11d-4315-afd2-17846c7f5ed0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "\n",
              "\n",
              "\n",
              "    <div id=\"df-d89000c8-5d8b-4967-99f5-d32b87888293\">\n",
              "      <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d89000c8-5d8b-4967-99f5-d32b87888293')\"\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",
              "    </div>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\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-quickchart:hover {\n",
              "    background-color: #E2EBFA;\n",
              "    box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: #174EA6;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "    background-color: #3B4455;\n",
              "    fill: #D2E3FC;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart: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",
              "      async function quickchart(key) {\n",
              "        const containerElement = document.querySelector('#' + key);\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      }\n",
              "    </script>\n",
              "\n",
              "      <script>\n",
              "\n",
              "function displayQuickchartButton(domScope) {\n",
              "  let quickchartButtonEl =\n",
              "    domScope.querySelector('#df-d89000c8-5d8b-4967-99f5-d32b87888293 button.colab-df-quickchart');\n",
              "  quickchartButtonEl.style.display =\n",
              "    google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "}\n",
              "\n",
              "        displayQuickchartButton(document);\n",
              "      </script>\n",
              "      <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c9be69e4-b11d-4315-afd2-17846c7f5ed0 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-c9be69e4-b11d-4315-afd2-17846c7f5ed0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ],
      "source": [
        "fact_table"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "id": "a45c58d1",
      "metadata": {
        "id": "a45c58d1"
      },
      "outputs": [],
      "source": [
        "# CREATE OR REPLACE TABLE `data-with-darshil.uber_dataset.tbl_analysis_report` AS (\n",
        "# SELECT\n",
        "#   f.VendorID,\n",
        "#   f.tpep_pickup_datetime,\n",
        "#   f.tpep_dropoff_datetime,\n",
        "#   p.passenger_count,\n",
        "#   td.trip_distance,\n",
        "#   rc.RatecodeID,\n",
        "#   f.store_and_fwd_flag,\n",
        "#   pl.pickup_latitude,\n",
        "#   pl.pickup_longitude,\n",
        "#   dl.dropoff_latitude,\n",
        "#   dl.dropoff_longitude,\n",
        "#   pt.payment_type,\n",
        "#   f.fare_amount,\n",
        "#   f.extra,\n",
        "#   f.mta_tax,\n",
        "#   f.tip_amount,\n",
        "#   f.tolls_amount,\n",
        "#   f.improvement_surcharge,\n",
        "#   f.total_amount\n",
        "# FROM\n",
        "#   `data-with-darshil.uber_dataset.fact_table` f\n",
        "#   JOIN `data-with-darshil.uber_dataset.passenger_count_dim` p ON f.passenger_count_id = p.passenger_count_id\n",
        "#   JOIN `data-with-darshil.uber_dataset.trip_distance_dim` td ON f.trip_distance_id = td.trip_distance_id\n",
        "#   JOIN `data-with-darshil.uber_dataset.rate_code_dim` rc ON f.rate_code_id = rc.rate_code_id\n",
        "#   JOIN `data-with-darshil.uber_dataset.pickup_location_dim` pl ON f.pickup_location_id = pl.pickup_location_id\n",
        "#   JOIN `data-with-darshil.uber_dataset.dropoff_location_dim` dl ON f.dropoff_location_id = dl.dropoff_location_id\n",
        "#   JOIN `data-with-darshil.uber_dataset.payment_type_dim` pt ON f.payment_type_id = pt.payment_type_id);"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.6"
    },
    "colab": {
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}