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DOC: fix SA01 for pandas.core.resample.Resampler.ohlc (#60036)
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tuhinsharma121 authored Oct 21, 2024
1 parent 2a10e04 commit 68d9dca
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3 changes: 0 additions & 3 deletions ci/code_checks.sh
Original file line number Diff line number Diff line change
Expand Up @@ -104,7 +104,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.core.groupby.DataFrameGroupBy.indices SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.nth PR02" \
-i "pandas.core.groupby.DataFrameGroupBy.nunique SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.ohlc SA01" \
-i "pandas.core.groupby.DataFrameGroupBy.plot PR02" \
-i "pandas.core.groupby.DataFrameGroupBy.sem SA01" \
-i "pandas.core.groupby.SeriesGroupBy.__iter__ RT03,SA01" \
Expand All @@ -114,7 +113,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.core.groupby.SeriesGroupBy.is_monotonic_decreasing SA01" \
-i "pandas.core.groupby.SeriesGroupBy.is_monotonic_increasing SA01" \
-i "pandas.core.groupby.SeriesGroupBy.nth PR02" \
-i "pandas.core.groupby.SeriesGroupBy.ohlc SA01" \
-i "pandas.core.groupby.SeriesGroupBy.plot PR02" \
-i "pandas.core.groupby.SeriesGroupBy.sem SA01" \
-i "pandas.core.resample.Resampler.__iter__ RT03,SA01" \
Expand All @@ -124,7 +122,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
-i "pandas.core.resample.Resampler.max PR01,RT03,SA01" \
-i "pandas.core.resample.Resampler.mean SA01" \
-i "pandas.core.resample.Resampler.min PR01,RT03,SA01" \
-i "pandas.core.resample.Resampler.ohlc SA01" \
-i "pandas.core.resample.Resampler.prod SA01" \
-i "pandas.core.resample.Resampler.quantile PR01,PR07" \
-i "pandas.core.resample.Resampler.sem SA01" \
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6 changes: 6 additions & 0 deletions pandas/core/groupby/groupby.py
Original file line number Diff line number Diff line change
Expand Up @@ -3224,6 +3224,12 @@ def ohlc(self) -> DataFrame:
DataFrame
Open, high, low and close values within each group.
See Also
--------
DataFrame.agg : Aggregate using one or more operations over the specified axis.
DataFrame.resample : Resample time-series data.
DataFrame.groupby : Group DataFrame using a mapper or by a Series of columns.
Examples
--------
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