diff --git a/doc/source/whatsnew/v2.1.0.rst b/doc/source/whatsnew/v2.1.0.rst index 46f564f716b0a..cfce12c2930d7 100644 --- a/doc/source/whatsnew/v2.1.0.rst +++ b/doc/source/whatsnew/v2.1.0.rst @@ -350,8 +350,8 @@ Missing MultiIndex ^^^^^^^^^^ +- Bug in :meth:`DataFrame.__getitem__` not preserving dtypes for :class:`MultiIndex` partial keys (:issue:`51895`) - Bug in :meth:`MultiIndex.set_levels` not preserving dtypes for :class:`Categorical` (:issue:`52125`) -- I/O ^^^ diff --git a/pandas/core/frame.py b/pandas/core/frame.py index 34e8c969d1b75..e04555ca30008 100644 --- a/pandas/core/frame.py +++ b/pandas/core/frame.py @@ -3831,18 +3831,8 @@ def _getitem_multilevel(self, key): if isinstance(loc, (slice, np.ndarray)): new_columns = self.columns[loc] result_columns = maybe_droplevels(new_columns, key) - if self._is_mixed_type: - result = self.reindex(columns=new_columns) - result.columns = result_columns - else: - new_values = self._values[:, loc] - result = self._constructor( - new_values, index=self.index, columns=result_columns, copy=False - ) - if using_copy_on_write() and isinstance(loc, slice): - result._mgr.add_references(self._mgr) # type: ignore[arg-type] - - result = result.__finalize__(self) + result = self.iloc[:, loc] + result.columns = result_columns # If there is only one column being returned, and its name is # either an empty string, or a tuple with an empty string as its diff --git a/pandas/tests/indexing/multiindex/test_multiindex.py b/pandas/tests/indexing/multiindex/test_multiindex.py index d7285f0069c71..955c4acfd4c97 100644 --- a/pandas/tests/indexing/multiindex/test_multiindex.py +++ b/pandas/tests/indexing/multiindex/test_multiindex.py @@ -6,12 +6,14 @@ import pandas as pd from pandas import ( + CategoricalDtype, DataFrame, Index, MultiIndex, Series, ) import pandas._testing as tm +from pandas.core.arrays.boolean import BooleanDtype class TestMultiIndexBasic: @@ -207,6 +209,24 @@ def test_multiindex_with_na_missing_key(self): with pytest.raises(KeyError, match="missing_key"): df[[("missing_key",)]] + def test_multiindex_dtype_preservation(self): + # GH51261 + columns = MultiIndex.from_tuples([("A", "B")], names=["lvl1", "lvl2"]) + df = DataFrame(["value"], columns=columns).astype("category") + df_no_multiindex = df["A"] + assert isinstance(df_no_multiindex["B"].dtype, CategoricalDtype) + + # geopandas 1763 analogue + df = DataFrame( + [[1, 0], [0, 1]], + columns=[ + ["foo", "foo"], + ["location", "location"], + ["x", "y"], + ], + ).assign(bools=Series([True, False], dtype="boolean")) + assert isinstance(df["bools"].dtype, BooleanDtype) + def test_multiindex_from_tuples_with_nan(self): # GH#23578 result = MultiIndex.from_tuples([("a", "b", "c"), np.nan, ("d", "", "")])