NOTICE
The upcoming release of Featuretools 1.0.0 contains several breaking changes. Users are encouraged to test this version prior to release by installing from GitHub:
pip install https://github.com/alteryx/featuretools/archive/woodwork-integration.zip
For details on migrating to the new version, refer to Transitioning to Featuretools Version 1.0. Please report any issues in the Featuretools GitHub repo or by messaging in Alteryx Open Source Slack.
featuretools.
make_temporal_cutoffs
Makes a set of equally spaced cutoff times prior to a set of input cutoffs and instance ids.
If window_size and num_windows are provided, then num_windows of size window_size will be created prior to each cutoff time
If window_size and a start list is provided, then a variable number of windows will be created prior to each cutoff time, with the corresponding start time as the first cutoff.
If num_windows and a start list is provided, then num_windows of variable size will be created prior to each cutoff time, with the corresponding start time as the first cutoff
instance_ids (list, np.ndarray, or pd.Series) – list of instance ids. This function will make a new datetime series of multiple cutoff times for each value in this array.
cutoffs (list, np.ndarray, or pd.Series) – list of datetime objects associated with each instance id. Each one of these will be the last time in the new datetime series for each instance id
window_size (pd.Timedelta, optional) – amount of time between each datetime in each new cutoff series
num_windows (int, optional) – number of windows in each new cutoff series
start (list, optional) – list of start times for each instance id