pyspark.pandas.Series.dt.strftime

dt.strftime(date_format: str) → ps.Series

Convert to a string Series using specified date_format.

Return an series of formatted strings specified by date_format, which supports the same string format as the python standard library. Details of the string format can be found in python string format doc.

Parameters

date_formatstr

Date format string (example: “%%Y-%%m-%%d”).

Returns

Series

Series of formatted strings.

See also

to_datetime

Convert the given argument to datetime.

normalize

Return series with times to midnight.

round

Round the series to the specified freq.

floor

Floor the series to the specified freq.

Examples

>>> series = ps.Series(pd.date_range(pd.Timestamp("2018-03-10 09:00"),
...                                  periods=3, freq='s'))
>>> series
0   2018-03-10 09:00:00
1   2018-03-10 09:00:01
2   2018-03-10 09:00:02
dtype: datetime64[ns]

>>> series.dt.strftime('%B %d, %Y, %r')
0    March 10, 2018, 09:00:00 AM
1    March 10, 2018, 09:00:01 AM
2    March 10, 2018, 09:00:02 AM
dtype: object

pyspark.pandas.Series.dt.normalize pyspark.pandas.Series.dt.round