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# pandas.Series.dt.strftime

Series.dt.strftime(*args, **kwargs)

  Convert to Index using specified date_format.

  Return an Index 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.

  Formats supported by the C strftime API but not by the python string format doc (such as “%R”, “%r”) are not officially supported and should be preferably replaced with their supported equivalents (such as “%H:%M”, “%I:%M:%S %p”).

  Note that PeriodIndex support additional directives, detailed in Period.strftime.

  Parameters:
    date_formatstr

      Date format string (e.g. “%Y-%m-%d”).

  Returns:
    ndarray[object]

      NumPy ndarray of formatted strings.

  See also

  `to_datetime`

    Convert the given argument to datetime.

  `DatetimeIndex.normalize`

    Return DatetimeIndex with times to midnight.

  `DatetimeIndex.round`

    Round the DatetimeIndex to the specified freq.

  `DatetimeIndex.floor`

    Floor the DatetimeIndex to the specified freq.

  `Timestamp.strftime`

    Format a single Timestamp.

  `Period.strftime`

    Format a single Period.

  Examples

      >>> rng = pd.date_range(pd.Timestamp("2018-03-10 09:00"),
      ...                     periods=3, freq='s')
      >>> rng.strftime('%B %d, %Y, %r')
      Index(['March 10, 2018, 09:00:00 AM', 'March 10, 2018, 09:00:01 AM',
             'March 10, 2018, 09:00:02 AM'],
            dtype='object')