cabDataAnalysis/mageCabTransformation at main · umeshbedi/cabDataAnalysis · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
import pandas as pd

if "transformer" not in globals():
    from mage_ai.data_preparation.decorators import transformer
if "test" not in globals():
    from mage_ai.data_preparation.decorators import test


@transformer
def transform(data, *args, **kwargs):
    data["tpep_pickup_datetime"] = pd.to_datetime(data["tpep_pickup_datetime"])
    data["tpep_dropoff_datetime"] = pd.to_datetime(data["tpep_dropoff_datetime"])

    data = data.drop_duplicates().reset_index(drop=True)
    data["trip_id"] = data.index

    datetime_dim = data[["tpep_pickup_datetime", "tpep_dropoff_datetime"]].reset_index(
        drop=True
    )
    datetime_dim["tpep_pickup_datetime"] = datetime_dim["tpep_pickup_datetime"]
    datetime_dim["pick_hour"] = datetime_dim["tpep_pickup_datetime"].dt.hour
    datetime_dim["pick_day"] = datetime_dim["tpep_pickup_datetime"].dt.day
    datetime_dim["pick_month"] = datetime_dim["tpep_pickup_datetime"].dt.month
    datetime_dim["pick_year"] = datetime_dim["tpep_pickup_datetime"].dt.year
    datetime_dim["pick_weekday"] = datetime_dim["tpep_pickup_datetime"].dt.weekday

    datetime_dim["tpep_dropoff_datetime"] = datetime_dim["tpep_dropoff_datetime"]
    datetime_dim["drop_hour"] = datetime_dim["tpep_dropoff_datetime"].dt.hour
    datetime_dim["drop_day"] = datetime_dim["tpep_dropoff_datetime"].dt.day
    datetime_dim["drop_month"] = datetime_dim["tpep_dropoff_datetime"].dt.month
    datetime_dim["drop_year"] = datetime_dim["tpep_dropoff_datetime"].dt.year
    datetime_dim["drop_weekday"] = datetime_dim["tpep_dropoff_datetime"].dt.weekday

    datetime_dim["datetime_id"] = datetime_dim.index

    # datetime_dim = datetime_dim.rename(columns={'tpep_pickup_datetime': 'datetime_id'}).reset_index(drop=True)
    datetime_dim = datetime_dim[
        [
            "datetime_id",
            "tpep_pickup_datetime",
            "pick_hour",
            "pick_day",
            "pick_month",
            "pick_year",
            "pick_weekday",
            "tpep_dropoff_datetime",
            "drop_hour",
            "drop_day",
            "drop_month",
            "drop_year",
            "drop_weekday",
        ]
    ]

    passenger_count_dim = data[["passenger_count"]].reset_index(drop=True)
    passenger_count_dim["passenger_count_id"] = passenger_count_dim.index
    passenger_count_dim = passenger_count_dim[["passenger_count_id", "passenger_count"]]

    trip_distance_dim = data[["trip_distance"]].reset_index(drop=True)
    trip_distance_dim["trip_distance_id"] = trip_distance_dim.index
    trip_distance_dim = trip_distance_dim[["trip_distance_id", "trip_distance"]]
    rate_code_type = {
        1: "Standard rate",
        2: "JFK",
        3: "Newark",
        4: "Nassau or Westchester",
        5: "Negotiated fare",
        6: "Group ride",
    }

    rate_code_dim = data[["RatecodeID"]].reset_index(drop=True)
    rate_code_dim["rate_code_id"] = rate_code_dim.index
    rate_code_dim["rate_code_name"] = rate_code_dim["RatecodeID"].map(rate_code_type)
    rate_code_dim = rate_code_dim[["rate_code_id", "RatecodeID", "rate_code_name"]]

    pickup_location_dim = data[["pickup_longitude", "pickup_latitude"]].reset_index(
        drop=True
    )
    pickup_location_dim["pickup_location_id"] = pickup_location_dim.index
    pickup_location_dim = pickup_location_dim[
        ["pickup_location_id", "pickup_latitude", "pickup_longitude"]
    ]

    dropoff_location_dim = data[["dropoff_longitude", "dropoff_latitude"]].reset_index(
        drop=True
    )
    dropoff_location_dim["dropoff_location_id"] = dropoff_location_dim.index
    dropoff_location_dim = dropoff_location_dim[
        ["dropoff_location_id", "dropoff_latitude", "dropoff_longitude"]
    ]

    payment_type_name = {
        1: "Credit card",
        2: "Cash",
        3: "No charge",
        4: "Dispute",
        5: "Unknown",
        6: "Voided trip",
    }
    payment_type_dim = data[["payment_type"]].reset_index(drop=True)
    payment_type_dim["payment_type_id"] = payment_type_dim.index
    payment_type_dim["payment_type_name"] = payment_type_dim["payment_type"].map(
        payment_type_name
    )
    payment_type_dim = payment_type_dim[
        ["payment_type_id", "payment_type", "payment_type_name"]
    ]

    fact_table = (
        data.merge(
            passenger_count_dim, left_on="trip_id", right_on="passenger_count_id"
        )
        .merge(trip_distance_dim, left_on="trip_id", right_on="trip_distance_id")
        .merge(rate_code_dim, left_on="trip_id", right_on="rate_code_id")
        .merge(pickup_location_dim, left_on="trip_id", right_on="pickup_location_id")
        .merge(dropoff_location_dim, left_on="trip_id", right_on="dropoff_location_id")
        .merge(datetime_dim, left_on="trip_id", right_on="datetime_id")
        .merge(payment_type_dim, left_on="trip_id", right_on="payment_type_id")[
            [
                "trip_id",
                "VendorID",
                "datetime_id",
                "passenger_count_id",
                "trip_distance_id",
                "rate_code_id",
                "store_and_fwd_flag",
                "pickup_location_id",
                "dropoff_location_id",
                "payment_type_id",
                "fare_amount",
                "extra",
                "mta_tax",
                "tip_amount",
                "tolls_amount",
                "improvement_surcharge",
                "total_amount",
            ]
        ]
    )

    final_data = {
        "datetime_dim": datetime_dim.to_dict(orient="dict"),
        "passenger_count_dim": passenger_count_dim.to_dict(orient="dict"),
        "trip_distance_dim": trip_distance_dim.to_dict(orient="dict"),
        "rate_code_dim": rate_code_dim.to_dict(orient="dict"),
        "pickup_location_dim": pickup_location_dim.to_dict(orient="dict"),
        "dropoff_location_dim": dropoff_location_dim.to_dict(orient="dict"),
        "payment_type_dim": payment_type_dim.to_dict(orient="dict"),
        "fact_table": fact_table.to_dict(orient="dict"),
    }
    # something = pd.DataFrame(final_data["fact_table"])

    return final_data


@test
def test_output(output, *args) -> None:
    """
    Template code for testing the output of the block.
    """
    assert output is not None, "The output is undefined"