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