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Merge branch 'main' into fix/grouby_agg_dict_input_dup_columns
2 parents f6c6408 + a1fc8e8 commit 75f593e

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-9
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4 files changed

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ci/code_checks.sh

-9
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@@ -100,26 +100,19 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.DataFrame.var PR01,RT03,SA01" \
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-i "pandas.DatetimeIndex.indexer_at_time PR01,RT03" \
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-i "pandas.DatetimeIndex.snap PR01,RT03" \
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-i "pandas.DatetimeIndex.std PR01,RT03" \
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-i "pandas.DatetimeIndex.to_period RT03" \
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-i "pandas.DatetimeIndex.to_pydatetime RT03,SA01" \
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-i "pandas.DatetimeTZDtype SA01" \
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-i "pandas.Grouper PR02" \
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-i "pandas.Index PR07" \
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-i "pandas.Index.append PR07,RT03,SA01" \
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-i "pandas.Index.copy PR07,SA01" \
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-i "pandas.Index.difference PR07,RT03,SA01" \
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-i "pandas.Index.drop PR07,SA01" \
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-i "pandas.Index.droplevel RT03,SA01" \
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-i "pandas.Index.dropna RT03,SA01" \
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-i "pandas.Index.duplicated RT03" \
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-i "pandas.Index.get_indexer PR07,SA01" \
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-i "pandas.Index.get_indexer_for PR01,SA01" \
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-i "pandas.Index.get_indexer_non_unique PR07,SA01" \
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-i "pandas.Index.get_loc PR07,RT03,SA01" \
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-i "pandas.Index.get_slice_bound PR07" \
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-i "pandas.Index.identical PR01,SA01" \
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-i "pandas.Index.inferred_type SA01" \
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-i "pandas.Index.insert PR07,RT03,SA01" \
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-i "pandas.Index.intersection PR07,RT03,SA01" \
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-i "pandas.Index.join PR07,RT03,SA01" \
@@ -129,7 +122,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.Index.ravel PR01,RT03" \
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-i "pandas.Index.reindex PR07" \
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-i "pandas.Index.slice_indexer PR07,RT03,SA01" \
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-i "pandas.Index.slice_locs RT03" \
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-i "pandas.Index.str PR01,SA01" \
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-i "pandas.Index.symmetric_difference PR07,RT03,SA01" \
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-i "pandas.Index.take PR01,PR07" \
@@ -161,7 +153,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
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-i "pandas.MultiIndex.append PR07,SA01" \
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-i "pandas.MultiIndex.copy PR07,RT03,SA01" \
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-i "pandas.MultiIndex.drop PR07,RT03,SA01" \
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-i "pandas.MultiIndex.droplevel RT03,SA01" \
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-i "pandas.MultiIndex.dtypes SA01" \
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-i "pandas.MultiIndex.get_indexer PR07,SA01" \
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-i "pandas.MultiIndex.get_level_values SA01" \

pandas/core/arrays/datetimes.py

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

pandas/core/dtypes/dtypes.py

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

pandas/core/indexes/base.py

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@@ -1262,12 +1262,19 @@ def copy(
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name : Label, optional
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Set name for new object.
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deep : bool, default False
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If True attempts to make a deep copy of the Index.
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Else makes a shallow copy.
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Returns
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-------
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Index
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Index refer to new object which is a copy of this object.
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See Also
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--------
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Index.delete: Make new Index with passed location(-s) deleted.
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Index.drop: Make new Index with passed list of labels deleted.
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Notes
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-----
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In most cases, there should be no functional difference from using
@@ -2093,6 +2100,12 @@ def droplevel(self, level: IndexLabel = 0):
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Returns
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-------
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Index or MultiIndex
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Returns an Index or MultiIndex object, depending on the resulting index
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after removing the requested level(s).
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See Also
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--------
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Index.dropna : Return Index without NA/NaN values.
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Examples
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--------
@@ -2360,6 +2373,10 @@ def inferred_type(self) -> str_t:
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"""
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Return a string of the type inferred from the values.
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See Also
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--------
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Index.dtype : Return the dtype object of the underlying data.
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Examples
23642381
--------
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>>> idx = pd.Index([1, 2, 3])
@@ -2615,6 +2632,12 @@ def dropna(self, how: AnyAll = "any") -> Self:
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Returns
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-------
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Index
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Returns an Index object after removing NA/NaN values.
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See Also
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--------
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Index.fillna : Fill NA/NaN values with the specified value.
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Index.isna : Detect missing values.
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Examples
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--------
@@ -6382,7 +6405,10 @@ def get_slice_bound(self, label, side: Literal["left", "right"]) -> int:
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Parameters
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----------
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label : object
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The label for which to calculate the slice bound.
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side : {'left', 'right'}
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if 'left' return leftmost position of given label.
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if 'right' return one-past-the-rightmost position of given label.
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Returns
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-------
@@ -6471,6 +6497,8 @@ def slice_locs(self, start=None, end=None, step=None) -> tuple[int, int]:
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Returns
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-------
64736499
tuple[int, int]
6500+
Returns a tuple of two integers representing the slice locations for the
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input labels within the index.
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See Also
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--------

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