how to convert timestamp column of pandas dataframe into hour and day features using transformer

from sklearn.base import BaseEstimator, TransformerMixin
import pandas as pd

class dayandhour_Transformer(BaseEstimator, TransformerMixin):

    # Class Constructor

    def __init__(self):

        print('initialized')

 

    # Return self, nothing else to do here

    def fit(self, X, y=None):

       return self

 


    # Customized transformer method

    def transform(self, X_, y=None):

        X = X_.copy()

        X['dayofweek']=pd.to_datetime(X['timestamp']).dt.dayofweek

        X['hour']=pd.to_datetime(X['timestamp']).dt.hour

        X = X.drop('timestamp',axis=1)

        return X

   

dayandhour_transformer = dayandhour_Transformer() 

 

df = dayandhour_transformer.transform(df)

Suppose we have a dataframe df with a column “timestamp”.

before apply the code, we have:

print(df['timestamp'])

0        2021-03-28 03:28:10.205000

1        2021-03-28 21:31:43.290000

2        2021-03-28 21:16:18.771000

3        2021-03-28 18:39:13.344000

4        2021-03-28 00:54:57.544000

after we apply the code, we have:

print( df[['hour','dayofweek']])

       hour  dayofweek

0         3          6

1        21          6

2        21          6

3        18          6

4         0          6