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[BUG] TimeGapSplit mutates the data

See original GitHub issue

TimeGapSplit mutates the pandas.DataFrame it operates on if the date column is not a datetime type. For example:

from pandas.api.types import (

date_range = pd.date_range(start='1/1/2018', end='1/30/2018')
dates = [date.strftime('%m-%d-%Y') for date in date_range]

df = (
        data=np.random.randint(0, 30, size=(30, 4)),

assert is_object_dtype(df['date'])

cv = TimeGapSplit(

assert is_datetime64_any_dtype(df['date'])

Is this desirable behavior?

Possible remedies are:

  • Only accept the datetime type
  • Accept str type, but make a copy and leave the pandas.DataFrame as is.

Happy to hear your thoughts @kayhoogland @stephanecollot @koaning

Issue Analytics

  • State:closed
  • Created 4 years ago
  • Comments:11 (8 by maintainers)

github_iconTop GitHub Comments

koaningcommented, Sep 19, 2019

copy feels like a safer option for now. it allows for flexibility in the future.

stephanecollotcommented, Oct 28, 2019

@koaning can you close?

Read more comments on GitHub >

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