pandas.api.types.is_integer_dtype — pandas 2.3.0 documentation (original) (raw)

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

from pandas.api.types import is_integer_dtype 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