DOC: Fix SA01 Docstring Errors for DataFrame (#58364)

* DataFrame.__iter__ fix SA01 * add See Also for DataFrame.column * DataFrame.droplevel SA01 fixed * remove pandas.Series.droplevel from code_checks.sh

Author: gboeker

ci/code_checks.sh

@@ -80,10 +80,7 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
  -i "pandas.CategoricalIndex.codes SA01" \
  -i "pandas.CategoricalIndex.ordered SA01" \
  -i "pandas.DataFrame.__dataframe__ SA01" \
- -i "pandas.DataFrame.__iter__ SA01" \
  -i "pandas.DataFrame.at_time PR01" \
- -i "pandas.DataFrame.columns SA01" \
- -i "pandas.DataFrame.droplevel SA01" \
  -i "pandas.DataFrame.hist RT03" \
  -i "pandas.DataFrame.infer_objects RT03" \
  -i "pandas.DataFrame.kurt RT03,SA01" \
@@ -277,7 +274,6 @@ if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
  -i "pandas.Series.cat.reorder_categories PR01,PR02" \
  -i "pandas.Series.cat.set_categories PR01,PR02" \
  -i "pandas.Series.div PR07" \
- -i "pandas.Series.droplevel SA01" \
  -i "pandas.Series.dt.as_unit PR01,PR02" \
  -i "pandas.Series.dt.ceil PR01,PR02" \
  -i "pandas.Series.dt.components SA01" \

pandas/core/frame.py

@@ -12893,6 +12893,10 @@ def isin_(x):
  """
  The column labels of the DataFrame.
 
+ See Also
+ --------
+ DataFrame.index: The index (row labels) of the DataFrame.
+
  Examples
  --------
  >>> df = pd.DataFrame({'A': [1, 2], 'B': [3, 4]})

pandas/core/generic.py

@@ -783,6 +783,12 @@ def droplevel(self, level: IndexLabel, axis: Axis = 0) -> Self:
  {klass}
  {klass} with requested index / column level(s) removed.
 
+ See Also
+ --------
+ DataFrame.replace : Replace values given in `to_replace` with `value`.
+ DataFrame.pivot : Return reshaped DataFrame organized by given
+ index / column values.
+
  Examples
  --------
  >>> df = (
@@ -1862,6 +1868,11 @@ def __iter__(self) -> Iterator:
  iterator
  Info axis as iterator.
 
+ See Also
+ --------
+ DataFrame.items : Iterate over (column name, Series) pairs.
+ DataFrame.itertuples : Iterate over DataFrame rows as namedtuples.
+
  Examples
  --------
  >>> df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]})