def abs(self: FrameLike) -> FrameLike:
    "\n        Return a Series/DataFrame with absolute numeric value of each element.\n\n        Returns\n        -------\n        abs : Series/DataFrame containing the absolute value of each element.\n\n        Examples\n        --------\n\n        Absolute numeric values in a Series.\n\n        >>> s = ps.Series([-1.10, 2, -3.33, 4])\n        >>> s.abs()\n        0    1.10\n        1    2.00\n        2    3.33\n        3    4.00\n        dtype: float64\n\n        Absolute numeric values in a DataFrame.\n\n        >>> df = ps.DataFrame({\n        ...     'a': [4, 5, 6, 7],\n        ...     'b': [10, 20, 30, 40],\n        ...     'c': [100, 50, -30, -50]\n        ...   },\n        ...   columns=['a', 'b', 'c'])\n        >>> df.abs()\n           a   b    c\n        0  4  10  100\n        1  5  20   50\n        2  6  30   30\n        3  7  40   50\n        "

    def abs(psser: 'Series') -> Union[('Series', Column)]:
        if isinstance(psser.spark.data_type, BooleanType):
            return psser
        elif isinstance(psser.spark.data_type, NumericType):
            return psser._with_new_scol(F.abs(psser.spark.column), field=psser._internal.data_fields[0])
        else:
            raise TypeError('bad operand type for abs(): {} ({})'.format(spark_type_to_pandas_dtype(psser.spark.data_type), psser.spark.data_type.simpleString()))
    return self._apply_series_op(abs)
Return a Series/DataFrame with absolute numeric value of each element.

Returns
-------
abs : Series/DataFrame containing the absolute value of each element.

Examples
--------

Absolute numeric values in a Series.

>>> s = ps.Series([-1.10, 2, -3.33, 4])
>>> s.abs()
0    1.10
1    2.00
2    3.33
3    4.00
dtype: float64

Absolute numeric values in a DataFrame.

>>> df = ps.DataFrame({
...     'a': [4, 5, 6, 7],
...     'b': [10, 20, 30, 40],
...     'c': [100, 50, -30, -50]
...   },
...   columns=['a', 'b', 'c'])
>>> df.abs()
   a   b    c
0  4  10  100
1  5  20   50
2  6  30   30
3  7  40   50
def abs(self: FrameLike) -> FrameLike:
    "\n        Return a Series/DataFrame with absolute numeric value of each element.\n\n        Returns\n        -------\n        abs : Series/DataFrame containing the absolute value of each element.\n\n        Examples\n        --------\n\n        Absolute numeric values in a Series.\n\n        >>> s = ps.Series([-1.10, 2, -3.33, 4])\n        >>> s.abs()\n        0    1.10\n        1    2.00\n        2    3.33\n        3    4.00\n        dtype: float64\n\n        Absolute numeric values in a DataFrame.\n\n        >>> df = ps.DataFrame({\n        ...     'a': [4, 5, 6, 7],\n        ...     'b': [10, 20, 30, 40],\n        ...     'c': [100, 50, -30, -50]\n        ...   },\n        ...   columns=['a', 'b', 'c'])\n        >>> df.abs()\n           a   b    c\n        0  4  10  100\n        1  5  20   50\n        2  6  30   30\n        3  7  40   50\n        "

    def abs(psser: 'Series') -> Union[('Series', Column)]:
        if isinstance(psser.spark.data_type, BooleanType):
            return psser
        elif isinstance(psser.spark.data_type, NumericType):
            return psser._with_new_scol(F.abs(psser.spark.column), field=psser._internal.data_fields[0])
        else:
            raise TypeError('bad operand type for abs(): {} ({})'.format(spark_type_to_pandas_dtype(psser.spark.data_type), psser.spark.data_type.simpleString()))
    return self._apply_series_op(abs)