class_docstr: Accessor object for datetimelike properties of the Series values.
  
  Examples
  --------
  >>> seconds_series = pd.Series(pd.date_range("2000-01-01", periods=3, freq="s"))
  >>> seconds_series
  0   2000-01-01 00:00:00
  1   2000-01-01 00:00:01
  2   2000-01-01 00:00:02
  dtype: datetime64[ns]
  >>> seconds_series.dt.second
  0    0
  1    1
  2    2
  dtype: int32
  
  >>> hours_series = pd.Series(pd.date_range("2000-01-01", periods=3, freq="h"))
  >>> hours_series
  0   2000-01-01 00:00:00
  1   2000-01-01 01:00:00
  2   2000-01-01 02:00:00
  dtype: datetime64[ns]
  >>> hours_series.dt.hour
  0    0
  1    1
  2    2
  dtype: int32
  
  >>> quarters_series = pd.Series(pd.date_range("2000-01-01", periods=3, freq="q"))
  >>> quarters_series
  0   2000-03-31
  1   2000-06-30
  2   2000-09-30
  dtype: datetime64[ns]
  >>> quarters_series.dt.quarter
  0    1
  1    2
  2    3
  dtype: int32
  
  Returns a Series indexed like the original Series.
  Raises TypeError if the Series does not contain datetimelike values.
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code: def freq(self):
      return self._get_values().inferred_freq
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, cast
  import numpy
  from pandas.core.dtypes.common import is_categorical_dtype, is_datetime64_dtype, is_datetime64tz_dtype, is_integer_dtype, is_list_like, is_period_dtype, is_timedelta64_dtype
  from pandas.core.dtypes.generic import ABCSeries
  from pandas.core.accessor import PandasDelegate, delegate_names
  from pandas.core.arrays import DatetimeArray, PeriodArray, TimedeltaArray
  from pandas.core.arrays.arrow.array import ArrowExtensionArray
  from pandas.core.arrays.arrow.dtype import ArrowDtype
  from pandas.core.base import NoNewAttributesMixin, PandasObject
  from pandas.core.indexes.datetimes import DatetimeIndex
  from pandas.core.indexes.timedeltas import TimedeltaIndex
label_desc: Use image node_id 2 for calling the DatetimeProperties obj's underlying member method code with example usage: obj.freq() and returns: self