asthana_ajeeta_taxi_data.ipynb

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              "   VendorID tpep_pickup_datetime tpep_dropoff_datetime  passenger_count  \\\n",
              "0         2          1/1/16 0:00           1/1/16 0:00                2   \n",
              "1         2          1/1/16 0:00           1/1/16 0:00                5   \n",
              "2         2          1/1/16 0:00           1/1/16 0:00                1   \n",
              "3         2          1/1/16 0:00           1/1/16 0:00                1   \n",
              "4         2          1/1/16 0:00           1/1/16 0:00                3   \n",
              "\n",
              "   trip_distance  pickup_longitude  pickup_latitude  RatecodeID  \\\n",
              "0           1.10        -73.990372        40.734695           1   \n",
              "1           4.90        -73.980782        40.729912           1   \n",
              "2          10.54        -73.984550        40.679565           1   \n",
              "3           4.75        -73.993469        40.718990           1   \n",
              "4           1.76        -73.960625        40.781330           1   \n",
              "\n",
              "  store_and_fwd_flag  dropoff_longitude  dropoff_latitude  payment_type  \\\n",
              "0                  N         -73.981842         40.732407             2   \n",
              "1                  N         -73.944473         40.716679             1   \n",
              "2                  N         -73.950272         40.788925             1   \n",
              "3                  N         -73.962242         40.657333             2   \n",
              "4                  N         -73.977264         40.758514             2   \n",
              "\n",
              "   fare_amount  extra  mta_tax  tip_amount  tolls_amount  \\\n",
              "0          7.5    0.5      0.5         0.0           0.0   \n",
              "1         18.0    0.5      0.5         0.0           0.0   \n",
              "2         33.0    0.5      0.5         0.0           0.0   \n",
              "3         16.5    0.0      0.5         0.0           0.0   \n",
              "4          8.0    0.0      0.5         0.0           0.0   \n",
              "\n",
              "   improvement_surcharge  total_amount  \n",
              "0                    0.3           8.8  \n",
              "1                    0.3          19.3  \n",
              "2                    0.3          34.3  \n",
              "3                    0.3          17.3  \n",
              "4                    0.3           8.8  "
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          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "import pandas as pd\n",
        "taxi = pd.read_csv(\"http://becomingvisual.com/python4data/taxi2016.csv\", header = 0)\n",
        "taxi.head(5)"
      ]
    },
    {
      "cell_type": "code",
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        "taxi.dtypes"
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      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "VendorID                   int64\n",
              "tpep_pickup_datetime      object\n",
              "tpep_dropoff_datetime     object\n",
              "passenger_count            int64\n",
              "trip_distance            float64\n",
              "pickup_longitude         float64\n",
              "pickup_latitude          float64\n",
              "RatecodeID                 int64\n",
              "store_and_fwd_flag        object\n",
              "dropoff_longitude        float64\n",
              "dropoff_latitude         float64\n",
              "payment_type               int64\n",
              "fare_amount              float64\n",
              "extra                    float64\n",
              "mta_tax                  float64\n",
              "tip_amount               float64\n",
              "tolls_amount             float64\n",
              "improvement_surcharge    float64\n",
              "total_amount             float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
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      "source": [
        "taxi.info()"
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        "id": "H-TuMHlB3J1K",
        "outputId": "24478785-1d33-4f96-adf3-fb452b99183a"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 1048575 entries, 0 to 1048574\n",
            "Data columns (total 19 columns):\n",
            " #   Column                 Non-Null Count    Dtype  \n",
            "---  ------                 --------------    -----  \n",
            " 0   VendorID               1048575 non-null  int64  \n",
            " 1   tpep_pickup_datetime   1048575 non-null  object \n",
            " 2   tpep_dropoff_datetime  1048575 non-null  object \n",
            " 3   passenger_count        1048575 non-null  int64  \n",
            " 4   trip_distance          1048575 non-null  float64\n",
            " 5   pickup_longitude       1048575 non-null  float64\n",
            " 6   pickup_latitude        1048575 non-null  float64\n",
            " 7   RatecodeID             1048575 non-null  int64  \n",
            " 8   store_and_fwd_flag     1048575 non-null  object \n",
            " 9   dropoff_longitude      1048575 non-null  float64\n",
            " 10  dropoff_latitude       1048575 non-null  float64\n",
            " 11  payment_type           1048575 non-null  int64  \n",
            " 12  fare_amount            1048575 non-null  float64\n",
            " 13  extra                  1048575 non-null  float64\n",
            " 14  mta_tax                1048575 non-null  float64\n",
            " 15  tip_amount             1048575 non-null  float64\n",
            " 16  tolls_amount           1048575 non-null  float64\n",
            " 17  improvement_surcharge  1048575 non-null  float64\n",
            " 18  total_amount           1048575 non-null  float64\n",
            "dtypes: float64(12), int64(4), object(3)\n",
            "memory usage: 152.0+ MB\n"
          ]
        }
      ]
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    {
      "cell_type": "code",
      "source": [
        "newvalues = taxi.loc[:, \"passenger_count\"].astype('float64')"
      ],
      "metadata": {
        "id": "oOWrlnQl3QZ-"
      },
      "execution_count": 6,
      "outputs": []
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      "source": [
        "taxi.loc[:, \"passenger_count\"] = newvalues"
      ],
      "metadata": {
        "id": "7T2CrXY43o9i"
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      "execution_count": 8,
      "outputs": []
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        "newvalues"
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        "outputId": "350f04c4-61d6-430d-94dd-b148cb47da15"
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      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0          2.0\n",
              "1          5.0\n",
              "2          1.0\n",
              "3          1.0\n",
              "4          3.0\n",
              "          ... \n",
              "1048570    1.0\n",
              "1048571    1.0\n",
              "1048572    1.0\n",
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      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "VendorID                   int64\n",
              "tpep_pickup_datetime      object\n",
              "tpep_dropoff_datetime     object\n",
              "passenger_count          float64\n",
              "trip_distance            float64\n",
              "pickup_longitude         float64\n",
              "pickup_latitude          float64\n",
              "RatecodeID                 int64\n",
              "store_and_fwd_flag        object\n",
              "dropoff_longitude        float64\n",
              "dropoff_latitude         float64\n",
              "payment_type               int64\n",
              "fare_amount              float64\n",
              "extra                    float64\n",
              "mta_tax                  float64\n",
              "tip_amount               float64\n",
              "tolls_amount             float64\n",
              "improvement_surcharge    float64\n",
              "total_amount             float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "newvalues = taxi.loc[:,\"passenger_count\"].astype('int64')\n",
        "taxi.loc[:, \"passenger_count\"] = newvalues"
      ],
      "metadata": {
        "id": "YvuQ2H0737yg"
      },
      "execution_count": 13,
      "outputs": []
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      "cell_type": "code",
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        "taxi.dtypes"
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        "outputId": "63bea9ef-6e66-4c30-99ca-cdeffae6ef99"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "VendorID                   int64\n",
              "tpep_pickup_datetime      object\n",
              "tpep_dropoff_datetime     object\n",
              "passenger_count            int64\n",
              "trip_distance            float64\n",
              "pickup_longitude         float64\n",
              "pickup_latitude          float64\n",
              "RatecodeID                 int64\n",
              "store_and_fwd_flag        object\n",
              "dropoff_longitude        float64\n",
              "dropoff_latitude         float64\n",
              "payment_type               int64\n",
              "fare_amount              float64\n",
              "extra                    float64\n",
              "mta_tax                  float64\n",
              "tip_amount               float64\n",
              "tolls_amount             float64\n",
              "improvement_surcharge    float64\n",
              "total_amount             float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "newvalues = pd.to_datetime(taxi.loc[:, \"tpep_pickup_datetime\"])\n",
        "taxi.loc[:, \"tpep_pickup_datetime\"] = newvalues\n",
        "taxi.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hWQ1sfXP4itn",
        "outputId": "5afae1b3-85eb-42d6-e67c-64a7c0b875c7"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "VendorID                          int64\n",
              "tpep_pickup_datetime     datetime64[ns]\n",
              "tpep_dropoff_datetime            object\n",
              "passenger_count                   int64\n",
              "trip_distance                   float64\n",
              "pickup_longitude                float64\n",
              "pickup_latitude                 float64\n",
              "RatecodeID                        int64\n",
              "store_and_fwd_flag               object\n",
              "dropoff_longitude               float64\n",
              "dropoff_latitude                float64\n",
              "payment_type                      int64\n",
              "fare_amount                     float64\n",
              "extra                           float64\n",
              "mta_tax                         float64\n",
              "tip_amount                      float64\n",
              "tolls_amount                    float64\n",
              "improvement_surcharge           float64\n",
              "total_amount                    float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "newvalues = pd.to_datetime(taxi.loc[:, \"tpep_dropoff_datetime\"])\n",
        "taxi.loc[:, \"tpep_dropoff_datetime\"] = newvalues\n",
        "taxi.dtypes"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QZPvaUoW5MYi",
        "outputId": "e36a8a69-bda6-47a9-a5ec-530e983e9859"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "VendorID                          int64\n",
              "tpep_pickup_datetime     datetime64[ns]\n",
              "tpep_dropoff_datetime    datetime64[ns]\n",
              "passenger_count                   int64\n",
              "trip_distance                   float64\n",
              "pickup_longitude                float64\n",
              "pickup_latitude                 float64\n",
              "RatecodeID                        int64\n",
              "store_and_fwd_flag               object\n",
              "dropoff_longitude               float64\n",
              "dropoff_latitude                float64\n",
              "payment_type                      int64\n",
              "fare_amount                     float64\n",
              "extra                           float64\n",
              "mta_tax                         float64\n",
              "tip_amount                      float64\n",
              "tolls_amount                    float64\n",
              "improvement_surcharge           float64\n",
              "total_amount                    float64\n",
              "dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "taxi_subset = taxi.loc[taxi.passenger_count == 1]\n",
        "taxi_subset.head(5)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 270
        },
        "id": "MBGBYPnB5tLf",
        "outputId": "6ab79589-077f-4dc8-d306-f9aed76a738f"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   VendorID tpep_pickup_datetime tpep_dropoff_datetime  passenger_count  \\\n",
              "2         2           2016-01-01   2016-01-01 00:00:00                1   \n",
              "3         2           2016-01-01   2016-01-01 00:00:00                1   \n",
              "7         1           2016-01-01   2016-01-01 00:11:00                1   \n",
              "8         1           2016-01-01   2016-01-01 00:11:00                1   \n",
              "9         2           2016-01-01   2016-01-01 00:11:00                1   \n",
              "\n",
              "   trip_distance  pickup_longitude  pickup_latitude  RatecodeID  \\\n",
              "2          10.54        -73.984550        40.679565           1   \n",
              "3           4.75        -73.993469        40.718990           1   \n",
              "7           1.20        -73.979424        40.744614           1   \n",
              "8           6.00        -73.947151        40.791046           1   \n",
              "9           3.21        -73.998344        40.723896           1   \n",
              "\n",
              "  store_and_fwd_flag  dropoff_longitude  dropoff_latitude  payment_type  \\\n",
              "2                  N         -73.950272         40.788925             1   \n",
              "3                  N         -73.962242         40.657333             2   \n",
              "7                  N         -73.992035         40.753944             2   \n",
              "8                  N         -73.920769         40.865578             2   \n",
              "9                  N         -73.995850         40.688400             2   \n",
              "\n",
              "   fare_amount  extra  mta_tax  tip_amount  tolls_amount  \\\n",
              "2         33.0    0.5      0.5         0.0           0.0   \n",
              "3         16.5    0.0      0.5         0.0           0.0   \n",
              "7          9.0    0.5      0.5         0.0           0.0   \n",
              "8         18.0    0.5      0.5         0.0           0.0   \n",
              "9         11.5    0.5      0.5         0.0           0.0   \n",
              "\n",
              "   improvement_surcharge  total_amount  \n",
              "2                    0.3          34.3  \n",
              "3                    0.3          17.3  \n",
              "7                    0.3          10.3  \n",
              "8                    0.3          19.3  \n",
              "9                    0.3          12.8  "
            ],
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>VendorID</th>\n",
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              "      <th>2</th>\n",
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              "      <td>2</td>\n",
              "      <td>2016-01-01</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>1</td>\n",
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              "      <td>-73.993469</td>\n",
              "      <td>40.718990</td>\n",
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              "      <td>N</td>\n",
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              "      <td>40.657333</td>\n",
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              "      <td>17.3</td>\n",
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              "      <th>7</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-01</td>\n",
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              "      <td>-73.979424</td>\n",
              "      <td>40.744614</td>\n",
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              "      <td>N</td>\n",
              "      <td>-73.992035</td>\n",
              "      <td>40.753944</td>\n",
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              "      <td>9.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.3</td>\n",
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              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-01</td>\n",
              "      <td>2016-01-01 00:11:00</td>\n",
              "      <td>1</td>\n",
              "      <td>6.00</td>\n",
              "      <td>-73.947151</td>\n",
              "      <td>40.791046</td>\n",
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              "      <td>N</td>\n",
              "      <td>-73.920769</td>\n",
              "      <td>40.865578</td>\n",
              "      <td>2</td>\n",
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              "      <td>0.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>19.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-01</td>\n",
              "      <td>2016-01-01 00:11:00</td>\n",
              "      <td>1</td>\n",
              "      <td>3.21</td>\n",
              "      <td>-73.998344</td>\n",
              "      <td>40.723896</td>\n",
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              "      <td>N</td>\n",
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              "      <td>0.5</td>\n",
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              "      <td>0.0</td>\n",
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      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         VendorID tpep_pickup_datetime tpep_dropoff_datetime  passenger_count  \\\n",
              "2               2  2016-01-01 00:00:00   2016-01-01 00:00:00                1   \n",
              "3               2  2016-01-01 00:00:00   2016-01-01 00:00:00                1   \n",
              "7               1  2016-01-01 00:00:00   2016-01-01 00:11:00                1   \n",
              "8               1  2016-01-01 00:00:00   2016-01-01 00:11:00                1   \n",
              "9               2  2016-01-01 00:00:00   2016-01-01 00:11:00                1   \n",
              "...           ...                  ...                   ...              ...   \n",
              "1048570         1  2016-01-04 17:28:00   2016-01-04 17:36:00                1   \n",
              "1048571         1  2016-01-04 17:28:00   2016-01-04 17:49:00                1   \n",
              "1048572         1  2016-01-04 17:28:00   2016-01-04 18:08:00                1   \n",
              "1048573         1  2016-01-04 17:28:00   2016-01-04 17:32:00                1   \n",
              "1048574         1  2016-01-04 17:28:00   2016-01-04 17:35:00                1   \n",
              "\n",
              "         trip_distance  pickup_longitude  pickup_latitude  RatecodeID  \\\n",
              "2                10.54        -73.984550        40.679565           1   \n",
              "3                 4.75        -73.993469        40.718990           1   \n",
              "7                 1.20        -73.979424        40.744614           1   \n",
              "8                 6.00        -73.947151        40.791046           1   \n",
              "9                 3.21        -73.998344        40.723896           1   \n",
              "...                ...               ...              ...         ...   \n",
              "1048570           1.10        -73.956001        40.782047           1   \n",
              "1048571           3.50        -73.975327        40.754677           1   \n",
              "1048572          10.40        -73.781860        40.644707           1   \n",
              "1048573           0.70        -73.984657        40.722603           1   \n",
              "1048574           2.20        -73.960930        40.760990           1   \n",
              "\n",
              "        store_and_fwd_flag  dropoff_longitude  dropoff_latitude  payment_type  \\\n",
              "2                        N         -73.950272         40.788925             1   \n",
              "3                        N         -73.962242         40.657333             2   \n",
              "7                        N         -73.992035         40.753944             2   \n",
              "8                        N         -73.920769         40.865578             2   \n",
              "9                        N         -73.995850         40.688400             2   \n",
              "...                    ...                ...               ...           ...   \n",
              "1048570                  N         -73.964256         40.767979             2   \n",
              "1048571                  N         -73.977791         40.789856             2   \n",
              "1048572                  N         -73.799858         40.588844             2   \n",
              "1048573                  N         -73.988297         40.729671             1   \n",
              "1048574                  N         -73.941177         40.788143             2   \n",
              "\n",
              "         fare_amount  extra  mta_tax  tip_amount  tolls_amount  \\\n",
              "2               33.0    0.5      0.5        0.00           0.0   \n",
              "3               16.5    0.0      0.5        0.00           0.0   \n",
              "7                9.0    0.5      0.5        0.00           0.0   \n",
              "8               18.0    0.5      0.5        0.00           0.0   \n",
              "9               11.5    0.5      0.5        0.00           0.0   \n",
              "...              ...    ...      ...         ...           ...   \n",
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              "1048572         35.5    1.0      0.5        0.00           0.0   \n",
              "1048573          4.5    1.0      0.5        1.85           0.0   \n",
              "1048574          8.5    1.0      0.5        0.00           0.0   \n",
              "\n",
              "         improvement_surcharge  total_amount  \n",
              "2                          0.3         34.30  \n",
              "3                          0.3         17.30  \n",
              "7                          0.3         10.30  \n",
              "8                          0.3         19.30  \n",
              "9                          0.3         12.80  \n",
              "...                        ...           ...  \n",
              "1048570                    0.3          9.30  \n",
              "1048571                    0.3         17.30  \n",
              "1048572                    0.3         37.30  \n",
              "1048573                    0.3          8.15  \n",
              "1048574                    0.3         10.30  \n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>VendorID</th>\n",
              "      <th>tpep_pickup_datetime</th>\n",
              "      <th>tpep_dropoff_datetime</th>\n",
              "      <th>passenger_count</th>\n",
              "      <th>trip_distance</th>\n",
              "      <th>pickup_longitude</th>\n",
              "      <th>pickup_latitude</th>\n",
              "      <th>RatecodeID</th>\n",
              "      <th>store_and_fwd_flag</th>\n",
              "      <th>dropoff_longitude</th>\n",
              "      <th>dropoff_latitude</th>\n",
              "      <th>payment_type</th>\n",
              "      <th>fare_amount</th>\n",
              "      <th>extra</th>\n",
              "      <th>mta_tax</th>\n",
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              "      <th>tolls_amount</th>\n",
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              "      <th>total_amount</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>1</td>\n",
              "      <td>10.54</td>\n",
              "      <td>-73.984550</td>\n",
              "      <td>40.679565</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.950272</td>\n",
              "      <td>40.788925</td>\n",
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              "      <td>33.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>34.30</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>1</td>\n",
              "      <td>4.75</td>\n",
              "      <td>-73.993469</td>\n",
              "      <td>40.718990</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.962242</td>\n",
              "      <td>40.657333</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.5</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>17.30</td>\n",
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              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:11:00</td>\n",
              "      <td>1</td>\n",
              "      <td>1.20</td>\n",
              "      <td>-73.979424</td>\n",
              "      <td>40.744614</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.992035</td>\n",
              "      <td>40.753944</td>\n",
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              "      <td>9.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:11:00</td>\n",
              "      <td>1</td>\n",
              "      <td>6.00</td>\n",
              "      <td>-73.947151</td>\n",
              "      <td>40.791046</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.920769</td>\n",
              "      <td>40.865578</td>\n",
              "      <td>2</td>\n",
              "      <td>18.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>19.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:11:00</td>\n",
              "      <td>1</td>\n",
              "      <td>3.21</td>\n",
              "      <td>-73.998344</td>\n",
              "      <td>40.723896</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.995850</td>\n",
              "      <td>40.688400</td>\n",
              "      <td>2</td>\n",
              "      <td>11.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>12.80</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
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              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>1048570</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 17:36:00</td>\n",
              "      <td>1</td>\n",
              "      <td>1.10</td>\n",
              "      <td>-73.956001</td>\n",
              "      <td>40.782047</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.964256</td>\n",
              "      <td>40.767979</td>\n",
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              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>9.30</td>\n",
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              "    <tr>\n",
              "      <th>1048571</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 17:49:00</td>\n",
              "      <td>1</td>\n",
              "      <td>3.50</td>\n",
              "      <td>-73.975327</td>\n",
              "      <td>40.754677</td>\n",
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              "      <td>N</td>\n",
              "      <td>-73.977791</td>\n",
              "      <td>40.789856</td>\n",
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              "      <td>1.0</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>17.30</td>\n",
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              "    <tr>\n",
              "      <th>1048572</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 18:08:00</td>\n",
              "      <td>1</td>\n",
              "      <td>10.40</td>\n",
              "      <td>-73.781860</td>\n",
              "      <td>40.644707</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.799858</td>\n",
              "      <td>40.588844</td>\n",
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              "      <td>0.3</td>\n",
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              "    <tr>\n",
              "      <th>1048573</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 17:32:00</td>\n",
              "      <td>1</td>\n",
              "      <td>0.70</td>\n",
              "      <td>-73.984657</td>\n",
              "      <td>40.722603</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.988297</td>\n",
              "      <td>40.729671</td>\n",
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              "      <td>8.15</td>\n",
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              "    <tr>\n",
              "      <th>1048574</th>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 17:35:00</td>\n",
              "      <td>1</td>\n",
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              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.30</td>\n",
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              "<p>701857 rows × 19 columns</p>\n",
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      "source": [
        "taxi_subset.reset_index(inplace = True, drop = False)"
      ],
      "metadata": {
        "id": "qDBN1OTL6HUV"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "taxi_subset"
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          "height": 488
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        "id": "Qafre9fs6R_t",
        "outputId": "f78daf52-f327-42a0-80db-7558e6d86715"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "          index  VendorID tpep_pickup_datetime tpep_dropoff_datetime  \\\n",
              "0             2         2  2016-01-01 00:00:00   2016-01-01 00:00:00   \n",
              "1             3         2  2016-01-01 00:00:00   2016-01-01 00:00:00   \n",
              "2             7         1  2016-01-01 00:00:00   2016-01-01 00:11:00   \n",
              "3             8         1  2016-01-01 00:00:00   2016-01-01 00:11:00   \n",
              "4             9         2  2016-01-01 00:00:00   2016-01-01 00:11:00   \n",
              "...         ...       ...                  ...                   ...   \n",
              "701852  1048570         1  2016-01-04 17:28:00   2016-01-04 17:36:00   \n",
              "701853  1048571         1  2016-01-04 17:28:00   2016-01-04 17:49:00   \n",
              "701854  1048572         1  2016-01-04 17:28:00   2016-01-04 18:08:00   \n",
              "701855  1048573         1  2016-01-04 17:28:00   2016-01-04 17:32:00   \n",
              "701856  1048574         1  2016-01-04 17:28:00   2016-01-04 17:35:00   \n",
              "\n",
              "        passenger_count  trip_distance  pickup_longitude  pickup_latitude  \\\n",
              "0                     1          10.54        -73.984550        40.679565   \n",
              "1                     1           4.75        -73.993469        40.718990   \n",
              "2                     1           1.20        -73.979424        40.744614   \n",
              "3                     1           6.00        -73.947151        40.791046   \n",
              "4                     1           3.21        -73.998344        40.723896   \n",
              "...                 ...            ...               ...              ...   \n",
              "701852                1           1.10        -73.956001        40.782047   \n",
              "701853                1           3.50        -73.975327        40.754677   \n",
              "701854                1          10.40        -73.781860        40.644707   \n",
              "701855                1           0.70        -73.984657        40.722603   \n",
              "701856                1           2.20        -73.960930        40.760990   \n",
              "\n",
              "        RatecodeID store_and_fwd_flag  dropoff_longitude  dropoff_latitude  \\\n",
              "0                1                  N         -73.950272         40.788925   \n",
              "1                1                  N         -73.962242         40.657333   \n",
              "2                1                  N         -73.992035         40.753944   \n",
              "3                1                  N         -73.920769         40.865578   \n",
              "4                1                  N         -73.995850         40.688400   \n",
              "...            ...                ...                ...               ...   \n",
              "701852           1                  N         -73.964256         40.767979   \n",
              "701853           1                  N         -73.977791         40.789856   \n",
              "701854           1                  N         -73.799858         40.588844   \n",
              "701855           1                  N         -73.988297         40.729671   \n",
              "701856           1                  N         -73.941177         40.788143   \n",
              "\n",
              "        payment_type  fare_amount  extra  mta_tax  tip_amount  tolls_amount  \\\n",
              "0                  1         33.0    0.5      0.5        0.00           0.0   \n",
              "1                  2         16.5    0.0      0.5        0.00           0.0   \n",
              "2                  2          9.0    0.5      0.5        0.00           0.0   \n",
              "3                  2         18.0    0.5      0.5        0.00           0.0   \n",
              "4                  2         11.5    0.5      0.5        0.00           0.0   \n",
              "...              ...          ...    ...      ...         ...           ...   \n",
              "701852             2          7.5    1.0      0.5        0.00           0.0   \n",
              "701853             2         15.5    1.0      0.5        0.00           0.0   \n",
              "701854             2         35.5    1.0      0.5        0.00           0.0   \n",
              "701855             1          4.5    1.0      0.5        1.85           0.0   \n",
              "701856             2          8.5    1.0      0.5        0.00           0.0   \n",
              "\n",
              "        improvement_surcharge  total_amount  \n",
              "0                         0.3         34.30  \n",
              "1                         0.3         17.30  \n",
              "2                         0.3         10.30  \n",
              "3                         0.3         19.30  \n",
              "4                         0.3         12.80  \n",
              "...                       ...           ...  \n",
              "701852                    0.3          9.30  \n",
              "701853                    0.3         17.30  \n",
              "701854                    0.3         37.30  \n",
              "701855                    0.3          8.15  \n",
              "701856                    0.3         10.30  \n",
              "\n",
              "[701857 rows x 20 columns]"
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              "        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>index</th>\n",
              "      <th>VendorID</th>\n",
              "      <th>tpep_pickup_datetime</th>\n",
              "      <th>tpep_dropoff_datetime</th>\n",
              "      <th>passenger_count</th>\n",
              "      <th>trip_distance</th>\n",
              "      <th>pickup_longitude</th>\n",
              "      <th>pickup_latitude</th>\n",
              "      <th>RatecodeID</th>\n",
              "      <th>store_and_fwd_flag</th>\n",
              "      <th>dropoff_longitude</th>\n",
              "      <th>dropoff_latitude</th>\n",
              "      <th>payment_type</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>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>1</td>\n",
              "      <td>10.54</td>\n",
              "      <td>-73.984550</td>\n",
              "      <td>40.679565</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.950272</td>\n",
              "      <td>40.788925</td>\n",
              "      <td>1</td>\n",
              "      <td>33.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>34.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>1</td>\n",
              "      <td>4.75</td>\n",
              "      <td>-73.993469</td>\n",
              "      <td>40.718990</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.962242</td>\n",
              "      <td>40.657333</td>\n",
              "      <td>2</td>\n",
              "      <td>16.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>17.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:11:00</td>\n",
              "      <td>1</td>\n",
              "      <td>1.20</td>\n",
              "      <td>-73.979424</td>\n",
              "      <td>40.744614</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.992035</td>\n",
              "      <td>40.753944</td>\n",
              "      <td>2</td>\n",
              "      <td>9.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:11:00</td>\n",
              "      <td>1</td>\n",
              "      <td>6.00</td>\n",
              "      <td>-73.947151</td>\n",
              "      <td>40.791046</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.920769</td>\n",
              "      <td>40.865578</td>\n",
              "      <td>2</td>\n",
              "      <td>18.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>19.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>2016-01-01 00:00:00</td>\n",
              "      <td>2016-01-01 00:11:00</td>\n",
              "      <td>1</td>\n",
              "      <td>3.21</td>\n",
              "      <td>-73.998344</td>\n",
              "      <td>40.723896</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.995850</td>\n",
              "      <td>40.688400</td>\n",
              "      <td>2</td>\n",
              "      <td>11.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>12.80</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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>701852</th>\n",
              "      <td>1048570</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 17:36:00</td>\n",
              "      <td>1</td>\n",
              "      <td>1.10</td>\n",
              "      <td>-73.956001</td>\n",
              "      <td>40.782047</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.964256</td>\n",
              "      <td>40.767979</td>\n",
              "      <td>2</td>\n",
              "      <td>7.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>9.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>701853</th>\n",
              "      <td>1048571</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 17:49:00</td>\n",
              "      <td>1</td>\n",
              "      <td>3.50</td>\n",
              "      <td>-73.975327</td>\n",
              "      <td>40.754677</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.977791</td>\n",
              "      <td>40.789856</td>\n",
              "      <td>2</td>\n",
              "      <td>15.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>17.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>701854</th>\n",
              "      <td>1048572</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 18:08:00</td>\n",
              "      <td>1</td>\n",
              "      <td>10.40</td>\n",
              "      <td>-73.781860</td>\n",
              "      <td>40.644707</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.799858</td>\n",
              "      <td>40.588844</td>\n",
              "      <td>2</td>\n",
              "      <td>35.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>37.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>701855</th>\n",
              "      <td>1048573</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 17:32:00</td>\n",
              "      <td>1</td>\n",
              "      <td>0.70</td>\n",
              "      <td>-73.984657</td>\n",
              "      <td>40.722603</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.988297</td>\n",
              "      <td>40.729671</td>\n",
              "      <td>1</td>\n",
              "      <td>4.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.85</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>8.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>701856</th>\n",
              "      <td>1048574</td>\n",
              "      <td>1</td>\n",
              "      <td>2016-01-04 17:28:00</td>\n",
              "      <td>2016-01-04 17:35:00</td>\n",
              "      <td>1</td>\n",
              "      <td>2.20</td>\n",
              "      <td>-73.960930</td>\n",
              "      <td>40.760990</td>\n",
              "      <td>1</td>\n",
              "      <td>N</td>\n",
              "      <td>-73.941177</td>\n",
              "      <td>40.788143</td>\n",
              "      <td>2</td>\n",
              "      <td>8.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>10.30</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>701857 rows × 20 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-fd408142-c797-4087-aaa4-4e0ea392d0c2')\"\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",
              "  <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",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-fd408142-c797-4087-aaa4-4e0ea392d0c2 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-fd408142-c797-4087-aaa4-4e0ea392d0c2');\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",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#calculate average tip amount \n",
        "cust_avg_tip_amt = sum(taxi_subset.tip_amount) / taxi_subset.shape[0]\n",
        "cust_avg_tip_amt"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-XKcq27k6XhE",
        "outputId": "a35a37ed-3b45-43e8-da45-4ff71efb80a8"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.5173728978977554"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "taxi_subset.tip_amount.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DTw4Ucei8IWn",
        "outputId": "0d38d20b-6118-4a13-9c64-a652714fa76a"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.517372897898005"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "taxi_subset.fare_amount.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FATdcZbu8OX9",
        "outputId": "e8711437-d525-48aa-ad97-d13f1306aeba"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "12.397635316025916"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# find range min, max\n",
        "taxi_subset.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 364
        },
        "id": "mFX9aEkW8YUj",
        "outputId": "e6a2ab42-18d7-40eb-93f8-89154b94772e"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              index       VendorID  passenger_count  trip_distance  \\\n",
              "count  7.018570e+05  701857.000000         701857.0   7.018570e+05   \n",
              "mean   5.402985e+05       1.447925              1.0   1.541061e+01   \n",
              "std    3.082967e+05       0.497281              0.0   9.579025e+03   \n",
              "min    2.000000e+00       1.000000              1.0   0.000000e+00   \n",
              "25%    2.715380e+05       1.000000              1.0   1.000000e+00   \n",
              "50%    5.441110e+05       1.000000              1.0   1.790000e+00   \n",
              "75%    8.120470e+05       2.000000              1.0   3.400000e+00   \n",
              "max    1.048574e+06       2.000000              1.0   8.000010e+06   \n",
              "\n",
              "       pickup_longitude  pickup_latitude     RatecodeID  dropoff_longitude  \\\n",
              "count     701857.000000    701857.000000  701857.000000      701857.000000   \n",
              "mean         -72.658424        40.027262       1.043314         -72.716525   \n",
              "std            9.765014         5.379454       0.472436           9.553603   \n",
              "min          -81.101891         0.000000       1.000000         -74.953789   \n",
              "25%          -73.991241        40.734043       1.000000         -73.990738   \n",
              "50%          -73.981102        40.752548       1.000000         -73.978989   \n",
              "75%          -73.963150        40.768894       1.000000         -73.959259   \n",
              "max            0.000000        57.269276      99.000000           0.000000   \n",
              "\n",
              "       dropoff_latitude   payment_type    fare_amount          extra  \\\n",
              "count     701857.000000  701857.000000  701857.000000  701857.000000   \n",
              "mean          40.059766       1.433393      12.397635       0.209689   \n",
              "std            5.263318       0.516904      11.340193       0.277158   \n",
              "min            0.000000       1.000000    -300.000000      -0.500000   \n",
              "25%           40.732914       1.000000       6.000000       0.000000   \n",
              "50%           40.752796       1.000000       9.000000       0.000000   \n",
              "75%           40.769886       2.000000      14.000000       0.500000   \n",
              "max           48.233334       4.000000    1463.750000       7.000000   \n",
              "\n",
              "             mta_tax     tip_amount   tolls_amount  improvement_surcharge  \\\n",
              "count  701857.000000  701857.000000  701857.000000          701857.000000   \n",
              "mean        0.497442       1.517373       0.279194               0.299742   \n",
              "std         0.038067       2.745683       2.033600               0.011971   \n",
              "min        -0.500000      -3.000000     -12.500000              -0.300000   \n",
              "25%         0.500000       0.000000       0.000000               0.300000   \n",
              "50%         0.500000       1.000000       0.000000               0.300000   \n",
              "75%         0.500000       2.000000       0.000000               0.300000   \n",
              "max         0.890000     800.000000     923.580000               0.300000   \n",
              "\n",
              "        total_amount  \n",
              "count  701857.000000  \n",
              "mean       15.201072  \n",
              "std        13.706221  \n",
              "min      -300.800000  \n",
              "25%         7.800000  \n",
              "50%        10.800000  \n",
              "75%        16.560000  \n",
              "max      1463.750000  "
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>index</th>\n",
              "      <th>VendorID</th>\n",
              "      <th>passenger_count</th>\n",
              "      <th>trip_distance</th>\n",
              "      <th>pickup_longitude</th>\n",
              "      <th>pickup_latitude</th>\n",
              "      <th>RatecodeID</th>\n",
              "      <th>dropoff_longitude</th>\n",
              "      <th>dropoff_latitude</th>\n",
              "      <th>payment_type</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>count</th>\n",
              "      <td>7.018570e+05</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.0</td>\n",
              "      <td>7.018570e+05</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "      <td>701857.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>5.402985e+05</td>\n",
              "      <td>1.447925</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.541061e+01</td>\n",
              "      <td>-72.658424</td>\n",
              "      <td>40.027262</td>\n",
              "      <td>1.043314</td>\n",
              "      <td>-72.716525</td>\n",
              "      <td>40.059766</td>\n",
              "      <td>1.433393</td>\n",
              "      <td>12.397635</td>\n",
              "      <td>0.209689</td>\n",
              "      <td>0.497442</td>\n",
              "      <td>1.517373</td>\n",
              "      <td>0.279194</td>\n",
              "      <td>0.299742</td>\n",
              "      <td>15.201072</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>3.082967e+05</td>\n",
              "      <td>0.497281</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.579025e+03</td>\n",
              "      <td>9.765014</td>\n",
              "      <td>5.379454</td>\n",
              "      <td>0.472436</td>\n",
              "      <td>9.553603</td>\n",
              "      <td>5.263318</td>\n",
              "      <td>0.516904</td>\n",
              "      <td>11.340193</td>\n",
              "      <td>0.277158</td>\n",
              "      <td>0.038067</td>\n",
              "      <td>2.745683</td>\n",
              "      <td>2.033600</td>\n",
              "      <td>0.011971</td>\n",
              "      <td>13.706221</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>2.000000e+00</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>-81.101891</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-74.953789</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-300.000000</td>\n",
              "      <td>-0.500000</td>\n",
              "      <td>-0.500000</td>\n",
              "      <td>-3.000000</td>\n",
              "      <td>-12.500000</td>\n",
              "      <td>-0.300000</td>\n",
              "      <td>-300.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>2.715380e+05</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.000000e+00</td>\n",
              "      <td>-73.991241</td>\n",
              "      <td>40.734043</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-73.990738</td>\n",
              "      <td>40.732914</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>7.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>5.441110e+05</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.790000e+00</td>\n",
              "      <td>-73.981102</td>\n",
              "      <td>40.752548</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-73.978989</td>\n",
              "      <td>40.752796</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>10.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>8.120470e+05</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.400000e+00</td>\n",
              "      <td>-73.963150</td>\n",
              "      <td>40.768894</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-73.959259</td>\n",
              "      <td>40.769886</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>14.000000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>16.560000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.048574e+06</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.0</td>\n",
              "      <td>8.000010e+06</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>57.269276</td>\n",
              "      <td>99.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>48.233334</td>\n",
              "      <td>4.000000</td>\n",
              "      <td>1463.750000</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>0.890000</td>\n",
              "      <td>800.000000</td>\n",
              "      <td>923.580000</td>\n",
              "      <td>0.300000</td>\n",
              "      <td>1463.750000</td>\n",
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              "\n",
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              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"The maximum tip was: \", taxi_subset.fare_amount.min())\n",
        "print(\"The maximum tip was: \", taxi_subset.fare_amount.max())\n",
        "print(\"The range of the tip was: \", taxi_subset.fare_amount.min(),\":\",taxi_subset.fare_amount.max())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DuLf-9mO8rR1",
        "outputId": "54a087eb-7d9b-43c4-8230-aad23e3a64f8"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The maximum tip was:  -300.0\n",
            "The maximum tip was:  1463.75\n",
            "The range of the tip was:  -300.0 : 1463.75\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(taxi_subset.loc[taxi_subset.fare_amount == -300]))\n",
        "taxi_subset.loc[taxi_subset.fare_amount == -300]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 163
        },
        "id": "f1TR9fVF9PYS",
        "outputId": "fdbe272a-d79e-4a2a-8510-aaa11cbdb11d"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "         index  VendorID tpep_pickup_datetime tpep_dropoff_datetime  \\\n",
              "124590  193432         2  2016-01-01 09:06:00   2016-01-01 09:11:00   \n",
              "\n",
              "        passenger_count  trip_distance  pickup_longitude  pickup_latitude  \\\n",
              "124590                1            0.0        -73.989738        40.714378   \n",
              "\n",
              "        RatecodeID store_and_fwd_flag  dropoff_longitude  dropoff_latitude  \\\n",
              "124590           5                  N         -73.989693         40.714432   \n",
              "\n",
              "        payment_type  fare_amount  extra  mta_tax  tip_amount  tolls_amount  \\\n",
              "124590             4       -300.0    0.0     -0.5         0.0           0.0   \n",
              "\n",
              "        improvement_surcharge  total_amount  \n",
              "124590                   -0.3        -300.8  "
            ],
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              "      <th>124590</th>\n",
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              "          const element = document.querySelector('#df-006b5edb-558e-4658-b8ce-87b5e5a23136');\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": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "taxi.groupby(['passenger_count']).size()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D_f0WEYs9zvI",
        "outputId": "01499f81-4273-45c6-fb6b-0d57a70bbc00"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "passenger_count\n",
              "0        59\n",
              "1    701857\n",
              "2    177159\n",
              "3     52765\n",
              "4     30259\n",
              "5     54017\n",
              "6     32451\n",
              "7         3\n",
              "8         5\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "taxi.groupby(by=['payment_type']).size()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sMG2xJ9X-ph0",
        "outputId": "1158a9e3-0bd4-433e-dae3-268b9bfe4642"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "payment_type\n",
              "1    594378\n",
              "2    447875\n",
              "3      4664\n",
              "4      1658\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#calculate the total distance, total fare, mean tip amount \n",
        "taxi.groupby(by=['payment_type'])['trip_distance','tip_amount', 'total_amount'].mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 249
        },
        "id": "r9xLRLac_DP5",
        "outputId": "c70f7ad3-c4cf-426e-e495-7732515fa3f6"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:2: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  \n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              trip_distance  tip_amount  total_amount\n",
              "payment_type                                         \n",
              "1                  3.451713    2.694059     17.506710\n",
              "2                 22.182675    0.000072     13.085020\n",
              "3                  3.328171   -0.000540     13.987985\n",
              "4                  3.316912   -0.000145     12.960440"
            ],
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              "\n",
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              "      <th>trip_distance</th>\n",
              "      <th>tip_amount</th>\n",
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              "    <tr>\n",
              "      <th>payment_type</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3.451713</td>\n",
              "      <td>2.694059</td>\n",
              "      <td>17.506710</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>22.182675</td>\n",
              "      <td>0.000072</td>\n",
              "      <td>13.085020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3.328171</td>\n",
              "      <td>-0.000540</td>\n",
              "      <td>13.987985</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3.316912</td>\n",
              "      <td>-0.000145</td>\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<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",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
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        }
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    {
      "cell_type": "code",
      "source": [
        " x = taxi.groupby(by=['payment_type'])['trip_distance','tip_amount', 'total_amount'].mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
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      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x.info()"
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      "metadata": {
        "colab": {
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        "id": "RpKTo47WAg3F",
        "outputId": "5a818d68-9c29-4b44-9bae-c36f2d2815e6"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 4 entries, 1 to 4\n",
            "Data columns (total 3 columns):\n",
            " #   Column         Non-Null Count  Dtype  \n",
            "---  ------         --------------  -----  \n",
            " 0   trip_distance  4 non-null      float64\n",
            " 1   tip_amount     4 non-null      float64\n",
            " 2   total_amount   4 non-null      float64\n",
            "dtypes: float64(3)\n",
            "memory usage: 128.0 bytes\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "taxi.groupby(by=['payment_type'])['trip_distance','tip_amount','total_amount'].max()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 262
        },
        "id": "Gkb-Td_-Alz_",
        "outputId": "caae618b-a79a-45a2-d97b-d48706fa9543"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              trip_distance  tip_amount  total_amount\n",
              "payment_type                                         \n",
              "1                     518.2      998.14       1004.94\n",
              "2                 8000010.0       11.67       1463.75\n",
              "3                     199.2        2.16        656.15\n",
              "4                     208.1        1.46        500.30"
            ],
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>518.2</td>\n",
              "      <td>998.14</td>\n",
              "      <td>1004.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8000010.0</td>\n",
              "      <td>11.67</td>\n",
              "      <td>1463.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>199.2</td>\n",
              "      <td>2.16</td>\n",
              "      <td>656.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>208.1</td>\n",
              "      <td>1.46</td>\n",
              "      <td>500.30</td>\n",
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              "                                                     [key], {});\n",
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              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
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          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    }
  ]
}