pandas.api.types.is_integer_dtype#
- pandas.api.types.is_integer_dtype(arr_or_dtype)[source]#
Check whether the provided array or dtype is of an integer dtype.
Unlike in is_any_int_dtype, timedelta64 instances will return False.
The nullable Integer dtypes (e.g. pandas.Int64Dtype) are also considered as integer by this function.
- Parameters
- arr_or_dtypearray-like or dtype
The array or dtype to check.
- Returns
- boolean
Whether or not the array or dtype is of an integer dtype and not an instance of timedelta64.
Examples
>>> is_integer_dtype(str) False >>> is_integer_dtype(int) True >>> is_integer_dtype(float) False >>> is_integer_dtype(np.uint64) True >>> is_integer_dtype('int8') True >>> is_integer_dtype('Int8') True >>> is_integer_dtype(pd.Int8Dtype) True >>> is_integer_dtype(np.datetime64) False >>> is_integer_dtype(np.timedelta64) False >>> is_integer_dtype(np.array(['a', 'b'])) False >>> is_integer_dtype(pd.Series([1, 2])) True >>> is_integer_dtype(np.array([], dtype=np.timedelta64)) False >>> is_integer_dtype(pd.Index([1, 2.])) # float False