pandas.api.types.is_numeric_dtype — pandas 3.0.0.dev0+2100.gf496acffcc documentation (original) (raw)

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

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

Parameters:

arr_or_dtypearray-like or dtype

The array or dtype to check.

Returns:

boolean

Whether or not the array or dtype is of a numeric dtype.

See also

api.types.is_integer_dtype

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

api.types.is_unsigned_integer_dtype

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

api.types.is_signed_integer_dtype

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

Examples

from pandas.api.types import is_numeric_dtype is_numeric_dtype(str) False is_numeric_dtype(int) True is_numeric_dtype(float) True is_numeric_dtype(np.uint64) True is_numeric_dtype(np.datetime64) False is_numeric_dtype(np.timedelta64) False is_numeric_dtype(np.array(["a", "b"])) False is_numeric_dtype(pd.Series([1, 2])) True is_numeric_dtype(pd.Index([1, 2.0])) True is_numeric_dtype(np.array([], dtype=np.timedelta64)) False