DOC: add Return Value Description to DataFrame.min

ci/code_checks.sh

@@ -73,7 +73,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.DataFrame.max RT03" \
         -i "pandas.DataFrame.mean RT03" \
         -i "pandas.DataFrame.median RT03" \
-        -i "pandas.DataFrame.min RT03" \
         -i "pandas.DataFrame.plot PR02" \
         -i "pandas.Grouper PR02" \
         -i "pandas.MultiIndex.append PR07,SA01" \

pandas/core/frame.py

@@ -11692,14 +11692,71 @@ def min(
     ) -> Series | Any: ...
 
     @deprecate_nonkeyword_arguments(version="3.0", allowed_args=["self"], name="min")
-    @doc(make_doc("min", ndim=2))
     def min(
         self,
         axis: Axis | None = 0,
         skipna: bool = True,
         numeric_only: bool = False,
         **kwargs,
     ) -> Series | Any:
+        """
+        Return the minimum of the values over the requested axis.
+
+        If you want the *index* of the minimum, use ``idxmin``.
+        This is the equivalent of the ``numpy.ndarray`` method ``argmin``.
+
+        Parameters
+        ----------
+        axis : {index (0), columns (1)}
+            Axis for the function to be applied on.
+            For `Series` this parameter is unused and defaults to 0.
+
+            For DataFrames, specifying ``axis=None`` will apply the aggregation
+            across both axes.
+
+            .. versionadded:: 2.0.0
+
+        skipna : bool, default True
+            Exclude NA/null values when computing the result.
+        numeric_only : bool, default False
+            Include only float, int, boolean columns.
+        **kwargs
+            Additional keyword arguments to be passed to the function.
+
+        Returns
+        -------
+        Series or scalar
+            The minimum of the values in the DataFrame.
+
+        See Also
+        --------
+        numpy.min : Equivalent numpy function for arrays.
+        Series.min : Return the minimum.
+        Series.max : Return the maximum.
+        Series.idxmin : Return the index of the minimum.
+        Series.idxmax : Return the index of the maximum.
+        DataFrame.max : Return the maximum over the requested axis.
+        DataFrame.idxmin : Return the index of the minimum over the requested axis.
+        DataFrame.idxmax : Return the index of the maximum over the requested axis.
+
+        Examples
+        --------
+        >>> idx = pd.MultiIndex.from_arrays(
+        ...     [["warm", "warm", "cold", "cold"], ["dog", "falcon", "fish", "spider"]],
+        ...     names=["blooded", "animal"],
+        ... )
+        >>> s = pd.Series([4, 2, 0, 8], name="legs", index=idx)
+        >>> s
+        blooded  animal
+        warm     dog       4
+                 falcon    2
+        cold     fish      0
+                 spider    8
+        Name: legs, dtype: int64
+
+        >>> s.min()
+        0
+        """
         result = super().min(
             axis=axis, skipna=skipna, numeric_only=numeric_only, **kwargs
         )

pandas/core/generic.py

@@ -12532,16 +12532,6 @@ def make_doc(name: str, ndim: int) -> str:
         see_also = _all_see_also
         examples = _all_examples
         kwargs = {"empty_value": "True"}
-    elif name == "min":
-        base_doc = _num_doc
-        desc = (
-            "Return the minimum of the values over the requested axis.\n\n"
-            "If you want the *index* of the minimum, use ``idxmin``. This is "
-            "the equivalent of the ``numpy.ndarray`` method ``argmin``."
-        )
-        see_also = _stat_func_see_also
-        examples = _min_examples
-        kwargs = {"min_count": ""}
     elif name == "max":
         base_doc = _num_doc
         desc = (

pandas/core/series.py

@@ -6524,7 +6524,7 @@ def min(
         Returns
         -------
         scalar or Series (if level specified)
-            The maximum of the values in the Series.
+            The minimum of the values in the Series.
 
         See Also
         --------