pandas.api.types.is_datetime64_ns_dtype#

pandas.api.types.is_datetime64_ns_dtype(arr_or_dtype)[source]#

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

Parameters:

arr_or_dtypearray-like or dtype: The array or dtype to check.

Returns:

bool: Whether or not the array or dtype is of the datetime64[ns] dtype.

See also

api.types.is_datetime64_dtype: Check whether an array-like or dtype is of the datetime64 dtype.
api.types.is_datetime64_any_dtype: Check whether the provided array or dtype is of the datetime64 dtype.

Examples

>>> from pandas.api.types import is_datetime64_ns_dtype
>>> from pandas.core.dtypes.dtypes import DatetimeTZDtype
>>> is_datetime64_ns_dtype(str)
False
>>> is_datetime64_ns_dtype(int)
False
>>> is_datetime64_ns_dtype(np.datetime64)  # no unit
False
>>> is_datetime64_ns_dtype(DatetimeTZDtype("ns", "US/Eastern"))
True
>>> is_datetime64_ns_dtype(np.array(["a", "b"]))
False
>>> is_datetime64_ns_dtype(np.array([1, 2]))
False
>>> is_datetime64_ns_dtype(np.array([], dtype="datetime64"))  # no unit
False
>>> is_datetime64_ns_dtype(np.array([], dtype="datetime64[ps]"))  # wrong unit
False
>>> is_datetime64_ns_dtype(pd.DatetimeIndex([1, 2, 3], dtype="datetime64[ns]"))
True