Expanding DatetimeIndex to rows in Python pandas

Question

I have a pandas dataframe with 3 columns DateIndex, Country, and Awareness

I need to convert the DateIndex to individual date entries per row.

Input:

Country Awareness DateIndex

USA 50% DatetimeIndex(['2017-05-01', '2017-05-02', '20... UK 75% DatetimeIndex(['2018-05-01', '2018-05-02', '20... Output: Country Awareness Date USA 50% 2017-05-01 USA 50% 2017-05-02 . . UK 75% 2018-05-01
UK 75% 2018-05-02

jezrael · Accepted Answer · 2019-09-09T08:41:33.390

1

Solution for pandas 0.25+ with DataFrame.explode:

df = pd.DataFrame({'Country':['USA','UK'],
                   'Awareness':['50%','75%'],
                   'Datetime':[pd.date_range('2017-05-01','2017-05-03'),
                               pd.date_range('2017-05-01','2017-05-04')]})
df = df.explode('Datetime')
print (df)
  Country Awareness   Datetime
0     USA       50% 2017-05-01
0     USA       50% 2017-05-02
0     USA       50% 2017-05-03
1      UK       75% 2017-05-01
1      UK       75% 2017-05-02
1      UK       75% 2017-05-03
1      UK       75% 2017-05-04

edited Sep 09 '19 at 08:41

answered Sep 09 '19 at 08:28

jezrael

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Datetime is of type: pandas.DatetimeIndex . I am now getting AttributeError: 'Series' object has no attribute 'explode' – user2419259 Sep 09 '19 at 08:44
1

@user2419259 - Because lower version of pandas like `0.25+`, is possible upgrade? – jezrael Sep 09 '19 at 08:45

Expanding DatetimeIndex to rows in Python pandas

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