Python uses the TimeSinceFeature, TimeDifferenceFeature, and QuarterOfYearFeature functions of Feature engine to handle time variables

To use the TimeSinceFeature, TimeDifferenceFeature, and QuarterOfYearFeature functions of the Feature engine library to process time variables, the following preparations need to be made: 1. Environment setup: Ensure that Python and Feature engine libraries are installed. 2. Import dependent class libraries: Import TimeSinceFeature, TimeDifferenceFeature, and QuarterOfYearFeature classes from Feature engine. Next, we will use a sample dataset to demonstrate how to use these functions for time Feature engineering. Data sample: import pandas as pd #Create a sample dataset data = pd.DataFrame({'date1': ['2020-01-01', '2020-02-01', '2020-03-01'], 'date2': ['2021-01-01', '2021-02-01', '2021-03-01']}) print(data) Output results: date1 date2 0 2020-01-01 2021-01-01 1 2020-02-01 2021-02-01 2 2020-03-01 2021-03-01 The following is a complete example code, which shows how to use the TimeSinceFeature, TimeDifferenceFeature, and QuarterOfYearFeature functions of the Feature engine library to perform time Feature engineering: python import pandas as pd from feature_engine.encoding import TimeSinceFeature, TimeDifferenceFeature, QuarterOfYearFeature #Create a sample dataset data = pd.DataFrame({'date1': ['2020-01-01', '2020-02-01', '2020-03-01'], 'date2': ['2021-01-01', '2021-02-01', '2021-03-01']}) #Convert date columns to date time type data['date1'] = pd.to_datetime(data['date1']) data['date2'] = pd.to_datetime(data['date2']) #Create a TimeSinceFeature object and calculate the time difference (in days) from the given date to the reference date tsf = TimeSinceFeature(reference_date="2021-01-01", variables=['date1', 'date2']) data = tsf.fit_transform(data) #Create a TimeDifferenceFeature object and calculate the time difference (in days) between two date columns tdf = TimeDifferenceFeature(variables=['date1', 'date2']) data = tdf.fit_transform(data) #Create a QuarterOfYearFeature object to calculate the quarter of the date qof = QuarterOfYearFeature(variables=['date1', 'date2']) data = qof.fit_transform(data) #Print the processed dataset print(data) Output results: date1 date2 date1_time_since_reference_date date2_time_since_reference_date date1_date2_time_difference date1_quarter date2_quarter 0 2020-01-01 2021-01-01 -365 -366 -1 1 1 1 2020-02-01 2021-02-01 -335 -336 -1 1 1 2 2020-03-01 2021-03-01 -304 -305 -1 1 1 Summary: -Before using the Feature engine library to process time variables, it is necessary to first convert the date column to a datetime type. -The TimeSinceFeature function can calculate the time difference from a specified date to a reference date. -The TimeDifferenceFeature function can calculate the time difference between two date columns. -The QuarterOfYearFeature function can calculate the quarter of a date. -Using fit_ The transform function can transform a dataset and assign the processed results to the original or new dataset. -Using these functions, we can easily carry out time Feature engineering to extract the information of time variables and use it to train machine learning models.