REF: dont use np.abs in NDFrame.__abs__ (pandas-dev#43847)

Author: jbrockmendel

pandas/core/generic.py

@@ -1589,6 +1589,77 @@ def bool(self):
 
         self.__nonzero__()
 
+    @final
+    def abs(self: NDFrameT) -> NDFrameT:
+        """
+        Return a Series/DataFrame with absolute numeric value of each element.
+
+        This function only applies to elements that are all numeric.
+
+        Returns
+        -------
+        abs
+            Series/DataFrame containing the absolute value of each element.
+
+        See Also
+        --------
+        numpy.absolute : Calculate the absolute value element-wise.
+
+        Notes
+        -----
+        For ``complex`` inputs, ``1.2 + 1j``, the absolute value is
+        :math:`\\sqrt{ a^2 + b^2 }`.
+
+        Examples
+        --------
+        Absolute numeric values in a Series.
+
+        >>> s = pd.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 Series with complex numbers.
+
+        >>> s = pd.Series([1.2 + 1j])
+        >>> s.abs()
+        0    1.56205
+        dtype: float64
+
+        Absolute numeric values in a Series with a Timedelta element.
+
+        >>> s = pd.Series([pd.Timedelta('1 days')])
+        >>> s.abs()
+        0   1 days
+        dtype: timedelta64[ns]
+
+        Select rows with data closest to certain value using argsort (from
+        `StackOverflow <https://stackoverflow.com/a/17758115>`__).
+
+        >>> df = pd.DataFrame({
+        ...     'a': [4, 5, 6, 7],
+        ...     'b': [10, 20, 30, 40],
+        ...     'c': [100, 50, -30, -50]
+        ... })
+        >>> df
+             a    b    c
+        0    4   10  100
+        1    5   20   50
+        2    6   30  -30
+        3    7   40  -50
+        >>> df.loc[(df.c - 43).abs().argsort()]
+             a    b    c
+        1    5   20   50
+        0    4   10  100
+        2    6   30  -30
+        3    7   40  -50
+        """
+        res_mgr = self._mgr.apply(np.abs)
+        return self._constructor(res_mgr).__finalize__(self, name="abs")
+
     @final
     def __abs__(self: NDFrameT) -> NDFrameT:
         return self.abs()
@@ -9838,78 +9909,6 @@ def _tz_localize(ax, tz, ambiguous, nonexistent):
     # ----------------------------------------------------------------------
     # Numeric Methods
 
-    @final
-    def abs(self: NDFrameT) -> NDFrameT:
-        """
-        Return a Series/DataFrame with absolute numeric value of each element.
-
-        This function only applies to elements that are all numeric.
-
-        Returns
-        -------
-        abs
-            Series/DataFrame containing the absolute value of each element.
-
-        See Also
-        --------
-        numpy.absolute : Calculate the absolute value element-wise.
-
-        Notes
-        -----
-        For ``complex`` inputs, ``1.2 + 1j``, the absolute value is
-        :math:`\\sqrt{ a^2 + b^2 }`.
-
-        Examples
-        --------
-        Absolute numeric values in a Series.
-
-        >>> s = pd.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 Series with complex numbers.
-
-        >>> s = pd.Series([1.2 + 1j])
-        >>> s.abs()
-        0    1.56205
-        dtype: float64
-
-        Absolute numeric values in a Series with a Timedelta element.
-
-        >>> s = pd.Series([pd.Timedelta('1 days')])
-        >>> s.abs()
-        0   1 days
-        dtype: timedelta64[ns]
-
-        Select rows with data closest to certain value using argsort (from
-        `StackOverflow <https://stackoverflow.com/a/17758115>`__).
-
-        >>> df = pd.DataFrame({
-        ...     'a': [4, 5, 6, 7],
-        ...     'b': [10, 20, 30, 40],
-        ...     'c': [100, 50, -30, -50]
-        ... })
-        >>> df
-             a    b    c
-        0    4   10  100
-        1    5   20   50
-        2    6   30  -30
-        3    7   40  -50
-        >>> df.loc[(df.c - 43).abs().argsort()]
-             a    b    c
-        1    5   20   50
-        0    4   10  100
-        2    6   30  -30
-        3    7   40  -50
-        """
-        # error: Incompatible return value type (got "ndarray[Any, dtype[Any]]",
-        # expected "NDFrameT")
-        return np.abs(self)  # type: ignore[return-value]
-
     @final
     def describe(
         self: NDFrameT,