diff --git a/ci/code_checks.sh b/ci/code_checks.sh index cabc25b5e0ba5..5802aa8418058 100755 --- a/ci/code_checks.sh +++ b/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" \ @@ -287,7 +284,6 @@ 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,SA01" \ -i "pandas.Series.dt.components SA01" \ diff --git a/pandas/core/frame.py b/pandas/core/frame.py index 0185ca8241617..50dc514e7181f 100644 --- a/pandas/core/frame.py +++ b/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]}) diff --git a/pandas/core/generic.py b/pandas/core/generic.py index dbe2006642484..a7f155ec93524 100644 --- a/pandas/core/generic.py +++ b/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]})