featuretools.primitives.DiffDatetime#
- class featuretools.primitives.DiffDatetime(periods=0)[source]#
- Computes the timedelta between a datetime in a list and the previous datetime in that list. - Parameters:
- periods (int) – The number of periods by which to shift the index row. Default is 0. Periods correspond to rows. 
 - Description:
- Given a list of datetimes, compute the difference from the previous item in the list. The result for the first element of the list will always be NaT. 
 - Examples - >>> from datetime import datetime >>> dt_values = [datetime(2019, 3, 1), datetime(2019, 6, 30), datetime(2019, 11, 17), datetime(2020, 1, 30), datetime(2020, 3, 11)] >>> diff_dt = DiffDatetime() >>> diff_dt(dt_values).tolist() [NaT, Timedelta('121 days 00:00:00'), Timedelta('140 days 00:00:00'), Timedelta('74 days 00:00:00'), Timedelta('41 days 00:00:00')] - You can specify the number of periods to shift the values - >>> diff_dt_periods = DiffDatetime(periods = 1) >>> diff_dt_periods(dt_values).tolist() [NaT, NaT, Timedelta('121 days 00:00:00'), Timedelta('140 days 00:00:00'), Timedelta('74 days 00:00:00')] - Methods - __init__([periods])- flatten_nested_input_types(input_types)- Flattens nested column schema inputs into a single list. - generate_name(base_feature_names)- generate_names(base_feature_names)- get_args_string()- get_arguments()- get_description(input_column_descriptions[, ...])- get_filepath(filename)- get_function()- Attributes - base_of- base_of_exclude- commutative- compatibility- Additional compatible libraries - default_value- Default value this feature returns if no data found. - description_template- input_types- woodwork.ColumnSchema types of inputs - max_stack_depth- name- Name of the primitive - number_output_features- Number of columns in feature matrix associated with this feature - return_type- ColumnSchema type of return - series_library- stack_on- stack_on_exclude- stack_on_self- uses_calc_time- uses_full_dataframe