pandas.api.types.is_signed_integer_dtype¶
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pandas.api.types.
is_signed_integer_dtype
(arr_or_dtype)[source]¶ Check whether the provided array or dtype is of a signed integer dtype.
Unlike in in_any_int_dtype, timedelta64 instances will return False.
Changed in version 0.24.0: The nullable Integer dtypes (e.g. pandas.Int64Dtype) are also considered as integer by this function.
Parameters: - arr_or_dtype : array-like
The array or dtype to check.
Returns: - boolean : Whether or not the array or dtype is of a signed integer dtype
and not an instance of timedelta64.
Examples
>>> is_signed_integer_dtype(str) False >>> is_signed_integer_dtype(int) True >>> is_signed_integer_dtype(float) False >>> is_signed_integer_dtype(np.uint64) # unsigned False >>> is_signed_integer_dtype('int8') True >>> is_signed_integer_dtype('Int8') True >>> is_signed_dtype(pd.Int8Dtype) True >>> is_signed_integer_dtype(np.datetime64) False >>> is_signed_integer_dtype(np.timedelta64) False >>> is_signed_integer_dtype(np.array(['a', 'b'])) False >>> is_signed_integer_dtype(pd.Series([1, 2])) True >>> is_signed_integer_dtype(np.array([], dtype=np.timedelta64)) False >>> is_signed_integer_dtype(pd.Index([1, 2.])) # float False >>> is_signed_integer_dtype(np.array([1, 2], dtype=np.uint32)) # unsigned False