DOC: fix SA01 for pandas.core.resample.Resampler.ohlc (#60036)

Author: tuhinsharma121

ci/code_checks.sh

@@ -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" \
@@ -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" \
@@ -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" \

pandas/core/groupby/groupby.py

@@ -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
         --------