pyspark.pandas.DatetimeIndex.ceil¶

DatetimeIndex.ceil(freq: Union[str, pandas._libs.tslibs.offsets.DateOffset], *args: Any, **kwargs: Any) → pyspark.pandas.indexes.datetimes.DatetimeIndex[source]¶

Perform ceil operation on the data to the specified freq.

Parameters

freqstr or Offset: The frequency level to ceil the index to. Must be a fixed frequency like ‘S’ (second) not ‘ME’ (month end).

Returns

DatetimeIndex

Raises

ValueError if the freq cannot be converted.

Examples

>>> rng = ps.date_range('1/1/2018 11:59:00', periods=3, freq='min')
>>> rng.ceil('H')  
DatetimeIndex(['2018-01-01 12:00:00', '2018-01-01 12:00:00',
               '2018-01-01 13:00:00'],
              dtype='datetime64[ns]', freq=None)

pyspark.pandas.DatetimeIndex.floor pyspark.pandas.DatetimeIndex.month_name