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DOC: RT03 fix for various DataFrameGroupBy and SeriesGroupBy methods #57862

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merged 11 commits into from
Apr 1, 2024
Merged

DOC: RT03 fix for various DataFrameGroupBy and SeriesGroupBy methods #57862

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feb79dd
pandas.core.groupby.SeriesGroupBy.apply
quangngd Mar 16, 2024
093bfe0
pandas.core.groupby.GroupBy.apply
quangngd Mar 16, 2024
be885fc
rm check
quangngd Mar 16, 2024
8006d8e
add a bunch
quangngd Mar 16, 2024
ff20a68
fix
quangngd Mar 16, 2024
050375d
fix
quangngd Mar 16, 2024
48e266e
wip
quangngd Mar 17, 2024
cb2264d
update pandas.core.groupby.DataFrameGroupBy.resample
quangngd Mar 18, 2024
fdc9fb4
Merge branch 'main' into 57416-partial
quangngd Mar 20, 2024
00e9a15
rm check from code_checls
quangngd Mar 20, 2024
7da7f7b
minor
quangngd Mar 20, 2024
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26 changes: 3 additions & 23 deletions ci/code_checks.sh
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -682,60 +682,40 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.core.groupby.DataFrameGroupBy.__iter__ RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.agg RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.aggregate RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.apply RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.boxplot PR07,RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.cummax RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.cummin RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.cumprod RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.cumsum RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.filter RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.filter SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.get_group RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.groups SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.hist RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.indices SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.max SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.mean RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.median SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.min SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.nth PR02" \
-i "pandas.core.groupby.DataFrameGroupBy.nunique RT03,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.ohlc SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.plot PR02,SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.prod SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.rank RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.resample RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.skew RT03" \
-i "pandas.core.groupby.DataFrameGroupBy.sum SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.transform RT03" \
-i "pandas.core.groupby.SeriesGroupBy.__iter__ RT03,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.agg RT03" \
-i "pandas.core.groupby.SeriesGroupBy.aggregate RT03" \
-i "pandas.core.groupby.SeriesGroupBy.apply RT03" \
-i "pandas.core.groupby.SeriesGroupBy.cummax RT03" \
-i "pandas.core.groupby.SeriesGroupBy.cummin RT03" \
-i "pandas.core.groupby.SeriesGroupBy.cumprod RT03" \
-i "pandas.core.groupby.SeriesGroupBy.cumsum RT03" \
-i "pandas.core.groupby.SeriesGroupBy.filter PR01,RT03,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.filter PR01,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.get_group RT03,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.groups SA01" \
-i "pandas.core.groupby.SeriesGroupBy.indices SA01" \
-i "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01" \
-i "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01" \
-i "pandas.core.groupby.SeriesGroupBy.max SA01" \
-i "pandas.core.groupby.SeriesGroupBy.mean RT03" \
-i "pandas.core.groupby.SeriesGroupBy.median SA01" \
-i "pandas.core.groupby.SeriesGroupBy.min SA01" \
-i "pandas.core.groupby.SeriesGroupBy.nth PR02" \
-i "pandas.core.groupby.SeriesGroupBy.ohlc SA01" \
-i "pandas.core.groupby.SeriesGroupBy.plot PR02,SA01" \
-i "pandas.core.groupby.SeriesGroupBy.prod SA01" \
-i "pandas.core.groupby.SeriesGroupBy.rank RT03" \
-i "pandas.core.groupby.SeriesGroupBy.resample RT03" \
-i "pandas.core.groupby.SeriesGroupBy.sem SA01" \
-i "pandas.core.groupby.SeriesGroupBy.skew RT03" \
-i "pandas.core.groupby.SeriesGroupBy.sum SA01" \
-i "pandas.core.groupby.SeriesGroupBy.transform RT03" \
-i "pandas.core.resample.Resampler.__iter__ RT03,SA01" \
-i "pandas.core.resample.Resampler.ffill RT03" \
-i "pandas.core.resample.Resampler.get_group RT03,SA01" \
Expand Down
6 changes: 6 additions & 0 deletions pandas/core/groupby/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -240,6 +240,7 @@ def apply(self, func, *args, **kwargs) -> Series:
Returns
-------
Series or DataFrame
A pandas object with the result of applying ``func`` to each group.

See Also
--------
Expand Down Expand Up @@ -600,6 +601,7 @@ def filter(self, func, dropna: bool = True, *args, **kwargs):
Returns
-------
Series
The filtered subset of the original Series.

Notes
-----
Expand Down Expand Up @@ -1078,6 +1080,7 @@ def skew(
Returns
-------
Series
Unbiased skew within groups.

See Also
--------
Expand Down Expand Up @@ -1939,6 +1942,7 @@ def filter(self, func, dropna: bool = True, *args, **kwargs) -> DataFrame:
Returns
-------
DataFrame
The filtered subset of the original DataFrame.

Notes
-----
Expand Down Expand Up @@ -2106,6 +2110,7 @@ def nunique(self, dropna: bool = True) -> DataFrame:
Returns
-------
nunique: DataFrame
Counts of unique elements in each position.

Examples
--------
Expand Down Expand Up @@ -2504,6 +2509,7 @@ def skew(
Returns
-------
DataFrame
Unbiased skew within groups.

See Also
--------
Expand Down
18 changes: 12 additions & 6 deletions pandas/core/groupby/groupby.py
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Original file line number Diff line number Diff line change
Expand Up @@ -333,6 +333,8 @@ class providing the base-class of operations.
Returns
-------
%(klass)s
%(klass)s with the same indexes as the original object filled
with transformed values.

See Also
--------
Expand Down Expand Up @@ -1550,6 +1552,7 @@ def apply(self, func, *args, include_groups: bool = True, **kwargs) -> NDFrameT:
Returns
-------
Series or DataFrame
A pandas object with the result of applying ``func`` to each group.

See Also
--------
Expand Down Expand Up @@ -2244,6 +2247,7 @@ def mean(
Returns
-------
pandas.Series or pandas.DataFrame
Mean of values within each group. Same object type as the caller.
%(see_also)s
Examples
--------
Expand Down Expand Up @@ -3511,11 +3515,8 @@ def resample(self, rule, *args, include_groups: bool = True, **kwargs) -> Resamp

Returns
-------
pandas.api.typing.DatetimeIndexResamplerGroupby,
pandas.api.typing.PeriodIndexResamplerGroupby, or
pandas.api.typing.TimedeltaIndexResamplerGroupby
Return a new groupby object, with type depending on the data
being resampled.
DatetimeIndexResampler, PeriodIndexResampler or TimdeltaResampler
Resampler object for the type of the index.

See Also
--------
Expand Down Expand Up @@ -4590,7 +4591,8 @@ def rank(

Returns
-------
DataFrame with ranking of values within each group
DataFrame
The ranking of values within each group.
%(see_also)s
Examples
--------
Expand Down Expand Up @@ -4662,6 +4664,7 @@ def cumprod(self, *args, **kwargs) -> NDFrameT:
Returns
-------
Series or DataFrame
Cumulative product for each group. Same object type as the caller.
%(see_also)s
Examples
--------
Expand Down Expand Up @@ -4720,6 +4723,7 @@ def cumsum(self, *args, **kwargs) -> NDFrameT:
Returns
-------
Series or DataFrame
Cumulative sum for each group. Same object type as the caller.
%(see_also)s
Examples
--------
Expand Down Expand Up @@ -4782,6 +4786,7 @@ def cummin(
Returns
-------
Series or DataFrame
Cumulative min for each group. Same object type as the caller.
%(see_also)s
Examples
--------
Expand Down Expand Up @@ -4852,6 +4857,7 @@ def cummax(
Returns
-------
Series or DataFrame
Cumulative max for each group. Same object type as the caller.
%(see_also)s
Examples
--------
Expand Down