Merge branch 'main' into fix/grouby_agg_dict_input_dup_columns

ci/code_checks.sh

@@ -100,26 +100,19 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.DataFrame.var PR01,RT03,SA01" \
         -i "pandas.DatetimeIndex.indexer_at_time PR01,RT03" \
         -i "pandas.DatetimeIndex.snap PR01,RT03" \
-        -i "pandas.DatetimeIndex.std PR01,RT03" \
         -i "pandas.DatetimeIndex.to_period RT03" \
         -i "pandas.DatetimeIndex.to_pydatetime RT03,SA01" \
-        -i "pandas.DatetimeTZDtype SA01" \
         -i "pandas.Grouper PR02" \
         -i "pandas.Index PR07" \
         -i "pandas.Index.append PR07,RT03,SA01" \
-        -i "pandas.Index.copy PR07,SA01" \
         -i "pandas.Index.difference PR07,RT03,SA01" \
         -i "pandas.Index.drop PR07,SA01" \
-        -i "pandas.Index.droplevel RT03,SA01" \
-        -i "pandas.Index.dropna RT03,SA01" \
         -i "pandas.Index.duplicated RT03" \
         -i "pandas.Index.get_indexer PR07,SA01" \
         -i "pandas.Index.get_indexer_for PR01,SA01" \
         -i "pandas.Index.get_indexer_non_unique PR07,SA01" \
         -i "pandas.Index.get_loc PR07,RT03,SA01" \
-        -i "pandas.Index.get_slice_bound PR07" \
         -i "pandas.Index.identical PR01,SA01" \
-        -i "pandas.Index.inferred_type SA01" \
         -i "pandas.Index.insert PR07,RT03,SA01" \
         -i "pandas.Index.intersection PR07,RT03,SA01" \
         -i "pandas.Index.join PR07,RT03,SA01" \
@@ -129,7 +122,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.Index.ravel PR01,RT03" \
         -i "pandas.Index.reindex PR07" \
         -i "pandas.Index.slice_indexer PR07,RT03,SA01" \
-        -i "pandas.Index.slice_locs RT03" \
         -i "pandas.Index.str PR01,SA01" \
         -i "pandas.Index.symmetric_difference PR07,RT03,SA01" \
         -i "pandas.Index.take PR01,PR07" \
@@ -161,7 +153,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
         -i "pandas.MultiIndex.append PR07,SA01" \
         -i "pandas.MultiIndex.copy PR07,RT03,SA01" \
         -i "pandas.MultiIndex.drop PR07,RT03,SA01" \
-        -i "pandas.MultiIndex.droplevel RT03,SA01" \
         -i "pandas.MultiIndex.dtypes SA01" \
         -i "pandas.MultiIndex.get_indexer PR07,SA01" \
         -i "pandas.MultiIndex.get_level_values SA01" \

pandas/core/arrays/datetimes.py

@@ -2248,16 +2248,33 @@ def std(
         axis : int, optional
             Axis for the function to be applied on. For :class:`pandas.Series`
             this parameter is unused and defaults to ``None``.
+        dtype : dtype, optional, default None
+            Type to use in computing the standard deviation. For arrays of
+            integer type the default is float64, for arrays of float types
+            it is the same as the array type.
+        out : ndarray, optional, default None
+            Alternative output array in which to place the result. It must have
+            the same shape as the expected output but the type (of the
+            calculated values) will be cast if necessary.
         ddof : int, default 1
             Degrees of Freedom. The divisor used in calculations is `N - ddof`,
             where `N` represents the number of elements.
+        keepdims : bool, optional
+            If this is set to True, the axes which are reduced are left in the
+            result as dimensions with size one. With this option, the result
+            will broadcast correctly against the input array. If the default
+            value is passed, then keepdims will not be passed through to the
+            std method of sub-classes of ndarray, however any non-default value
+            will be. If the sub-class method does not implement keepdims any
+            exceptions will be raised.
         skipna : bool, default True
             Exclude NA/null values. If an entire row/column is ``NA``, the result
             will be ``NA``.
 
         Returns
         -------
         Timedelta
+            Standard deviation over requested axis.
 
         See Also
         --------

pandas/core/dtypes/dtypes.py

@@ -717,6 +717,11 @@ class DatetimeTZDtype(PandasExtensionDtype):
     ZoneInfoNotFoundError
         When the requested timezone cannot be found.
 
+    See Also
+    --------
+    numpy.datetime64 : Numpy data type for datetime.
+    datetime.datetime : Python datetime object.
+
     Examples
     --------
     >>> from zoneinfo import ZoneInfo

pandas/core/indexes/base.py

@@ -1262,12 +1262,19 @@ def copy(
         name : Label, optional
             Set name for new object.
         deep : bool, default False
+            If True attempts to make a deep copy of the Index.
+                Else makes a shallow copy.
 
         Returns
         -------
         Index
             Index refer to new object which is a copy of this object.
 
+        See Also
+        --------
+        Index.delete: Make new Index with passed location(-s) deleted.
+        Index.drop: Make new Index with passed list of labels deleted.
+
         Notes
         -----
         In most cases, there should be no functional difference from using
@@ -2093,6 +2100,12 @@ def droplevel(self, level: IndexLabel = 0):
         Returns
         -------
         Index or MultiIndex
+            Returns an Index or MultiIndex object, depending on the resulting index
+            after removing the requested level(s).
+
+        See Also
+        --------
+        Index.dropna : Return Index without NA/NaN values.
 
         Examples
         --------
@@ -2360,6 +2373,10 @@ def inferred_type(self) -> str_t:
         """
         Return a string of the type inferred from the values.
 
+        See Also
+        --------
+        Index.dtype : Return the dtype object of the underlying data.
+
         Examples
         --------
         >>> idx = pd.Index([1, 2, 3])
@@ -2615,6 +2632,12 @@ def dropna(self, how: AnyAll = "any") -> Self:
         Returns
         -------
         Index
+            Returns an Index object after removing NA/NaN values.
+
+        See Also
+        --------
+        Index.fillna : Fill NA/NaN values with the specified value.
+        Index.isna : Detect missing values.
 
         Examples
         --------
@@ -6382,7 +6405,10 @@ def get_slice_bound(self, label, side: Literal["left", "right"]) -> int:
         Parameters
         ----------
         label : object
+            The label for which to calculate the slice bound.
         side : {'left', 'right'}
+            if 'left' return leftmost position of given label.
+            if 'right' return one-past-the-rightmost position of given label.
 
         Returns
         -------
@@ -6471,6 +6497,8 @@ def slice_locs(self, start=None, end=None, step=None) -> tuple[int, int]:
         Returns
         -------
         tuple[int, int]
+            Returns a tuple of two integers representing the slice locations for the
+            input labels within the index.
 
         See Also
         --------