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# pandas.api.types.is_datetime64_any_dtype

pandas.api.types.is_datetime64_any_dtype(arr_or_dtype)

  Check whether the provided array or dtype is of the datetime64 dtype.

  Unlike `api.types.is_datetime64_dtype()`, this function also considers timezone-aware dtypes such as `DatetimeTZDtype` to be datetime64 dtypes.

  Parameters:
    arr_or_dtype array-like or dtype

      The array or dtype to check.

  Returns:
    bool

      Whether or not the array or dtype is of the datetime64 dtype.

  See also

  `api.types.is_datetime64_dtype`

    Check whether an array-like or dtype is of the datetime64 dtype.

  `api.is_datetime64_ns_dtype`

    Check whether the provided array or dtype is of the datetime64[ns] dtype.

  `api.is_datetime64tz_dtype`

    Check whether an array-like or dtype is of a DatetimeTZDtype dtype.

  Examples

      >>> from pandas.api.types import is_datetime64_any_dtype
      >>> from pandas.api.types import DatetimeTZDtype
      >>> is_datetime64_any_dtype(str)
      False
      >>> is_datetime64_any_dtype(int)
      False
      >>> is_datetime64_any_dtype(np.datetime64)  # can be tz-naive
      True
      >>> is_datetime64_any_dtype(DatetimeTZDtype("ns", "US/Eastern"))
      True
      >>> is_datetime64_any_dtype(np.array(["a", "b"]))
      False
      >>> is_datetime64_any_dtype(np.array([1, 2]))
      False
      >>> is_datetime64_any_dtype(np.array([], dtype="datetime64[ns]"))
      True
      >>> is_datetime64_any_dtype(pd.DatetimeIndex([1, 2, 3], dtype="datetime64[ns]"))
      True