select dataframe rows (datetimeindex) by a list of datetime.date

Question

the df looks like this:

DateTime
2017-07-10 03:00:00    288.0
2017-07-10 04:00:00    306.0
2017-08-10 05:00:00    393.0
2017-08-10 06:00:00    522.0
2017-09-10 07:00:00    487.0
2017-09-10 08:00:00    523.0
2017-10-10 09:00:00    585.0

Question how to select row that in a list of dates:

['2017-07-10', '2017-09-10']

to have:

DateTime
2017-07-10 03:00:00    288.0
2017-07-10 04:00:00    306.0
2017-09-10 07:00:00    487.0
2017-09-10 08:00:00    523.0

Thanks

yatu · Answer 1 · 2019-03-29T11:57:52.837

6

Given that the dates in your list contain up to the daily information, you could start by flooring (Series.dt.floor) the DatetimeIndex up to the daily level and indexing with the list of datetime objects using isin:

t = [pd.to_datetime('2017-07-10'), pd.to_datetime('2017-09-10')]
df.index= pd.to_datetime(df.index)

df[df.index.floor('d').isin(t)]

Output

   DateTime
2017-07-10 03:00:00     288.0
2017-07-10 04:00:00     306.0
2017-09-10 07:00:00     487.0
2017-09-10 08:00:00     523.0

edited Mar 29 '19 at 11:57

answered Mar 29 '19 at 11:28

yatu

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for example? we can still use the date accesor right? – anky Mar 29 '19 at 11:39

score 3 · Accepted Answer · answered Mar 29 '19 at 11:28

Assuming the Datetime is index, try with the below:

to_search=['2017-07-10', '2017-09-10']
df[df.index.to_series().dt.date.astype(str).isin(to_search)]

                        1
DateTime                  
2017-07-10 03:00:00  288.0
2017-07-10 04:00:00  306.0
2017-09-10 07:00:00  487.0
2017-09-10 08:00:00  523.0

select dataframe rows (datetimeindex) by a list of datetime.date

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