pandas.api.types.is_unsigned_integer_dtype — pandas 3.0.0.dev0+2099.g3832e85779 documentation (original) (raw)

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

Check whether the provided array or dtype is of an unsigned integer dtype.

The nullable Integer dtypes (e.g. pandas.UInt64Dtype) 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 unsigned integer dtype.

See also

api.types.is_signed_integer_dtype

Check whether the provided array or dtype is of an signed integer dtype.

api.types.is_integer_dtype

Check whether the provided array or dtype is of an integer dtype.

api.types.is_numeric_dtype

Check whether the provided array or dtype is of a numeric dtype.

Examples

from pandas.api.types import is_unsigned_integer_dtype is_unsigned_integer_dtype(str) False is_unsigned_integer_dtype(int) # signed False is_unsigned_integer_dtype(float) False is_unsigned_integer_dtype(np.uint64) True is_unsigned_integer_dtype("uint8") True is_unsigned_integer_dtype("UInt8") True is_unsigned_integer_dtype(pd.UInt8Dtype) True is_unsigned_integer_dtype(np.array(["a", "b"])) False is_unsigned_integer_dtype(pd.Series([1, 2])) # signed False is_unsigned_integer_dtype(pd.Index([1, 2.0])) # float False is_unsigned_integer_dtype(np.array([1, 2], dtype=np.uint32)) True