Series.at_time(self, time, asof=False, axis=None)
[source]
Select values at particular time of day (e.g. 9:30AM).
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See also
between_time
first
last
DatetimeIndex.indexer_at_time
>>> i = pd.date_range('2018-04-09', periods=4, freq='12H') >>> ts = pd.DataFrame({'A': [1, 2, 3, 4]}, index=i) >>> ts A 2018-04-09 00:00:00 1 2018-04-09 12:00:00 2 2018-04-10 00:00:00 3 2018-04-10 12:00:00 4
>>> ts.at_time('12:00') A 2018-04-09 12:00:00 2 2018-04-10 12:00:00 4
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https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.Series.at_time.html