Merge branch 'main' into pandas.period_range

doc/source/whatsnew/v3.0.0.rst

@@ -544,7 +544,7 @@ Bug fixes
 
 Categorical
 ^^^^^^^^^^^
--
+- Bug in :func:`Series.apply` where ``nan`` was ignored for :class:`CategoricalDtype` (:issue:`59938`)
 -
 
 Datetimelike
@@ -682,6 +682,7 @@ Sparse
 ^^^^^^
 - Bug in :class:`SparseDtype` for equal comparison with na fill value. (:issue:`54770`)
 - Bug in :meth:`DataFrame.sparse.from_spmatrix` which hard coded an invalid ``fill_value`` for certain subtypes. (:issue:`59063`)
+- Bug in :meth:`DataFrame.sparse.to_dense` which ignored subclassing and always returned an instance of :class:`DataFrame` (:issue:`59913`)
 
 ExtensionArray
 ^^^^^^^^^^^^^^

pandas/core/apply.py

@@ -38,10 +38,7 @@
     is_numeric_dtype,
     is_sequence,
 )
-from pandas.core.dtypes.dtypes import (
-    CategoricalDtype,
-    ExtensionDtype,
-)
+from pandas.core.dtypes.dtypes import ExtensionDtype
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCNDFrame,
@@ -1465,14 +1462,7 @@ def curried(x):
 
         else:
             curried = func
-
-        # row-wise access
-        # apply doesn't have a `na_action` keyword and for backward compat reasons
-        # we need to give `na_action="ignore"` for categorical data.
-        # TODO: remove the `na_action="ignore"` when that default has been changed in
-        #  Categorical (GH51645).
-        action = "ignore" if isinstance(obj.dtype, CategoricalDtype) else None
-        mapped = obj._map_values(mapper=curried, na_action=action)
+        mapped = obj._map_values(mapper=curried)
 
         if len(mapped) and isinstance(mapped[0], ABCSeries):
             # GH#43986 Need to do list(mapped) in order to get treated as nested

pandas/core/arrays/sparse/accessor.py

@@ -369,10 +369,10 @@ def to_dense(self) -> DataFrame:
         1  1
         2  0
         """
-        from pandas import DataFrame
-
         data = {k: v.array.to_dense() for k, v in self._parent.items()}
-        return DataFrame(data, index=self._parent.index, columns=self._parent.columns)
+        return self._parent._constructor(
+            data, index=self._parent.index, columns=self._parent.columns
+        )
 
     def to_coo(self) -> spmatrix:
         """

pandas/io/formats/html.py

@@ -195,6 +195,8 @@ def _write_cell(
             esc = {}
 
         rs = pprint_thing(s, escape_chars=esc).strip()
+        # replace spaces betweens strings with non-breaking spaces
+        rs = rs.replace("  ", "  ")
 
         if self.render_links and is_url(rs):
             rs_unescaped = pprint_thing(s, escape_chars={}).strip()

pandas/io/formats/style_render.py

@@ -906,9 +906,9 @@ def concatenated_visible_rows(obj):
                 row_body_headers = [
                     {
                         **col,
-                        "display_value": col["display_value"]
-                        if col["is_visible"]
-                        else "",
+                        "display_value": (
+                            col["display_value"] if col["is_visible"] else ""
+                        ),
                         "cellstyle": self.ctx_index[r, c],
                     }
                     for c, col in enumerate(row[:index_levels])
@@ -2069,18 +2069,18 @@ def maybe_convert_css_to_tuples(style: CSSProperties) -> CSSList:
                                              ('border','1px solid red')]
     """
     if isinstance(style, str):
-        s = style.split(";")
-        try:
-            return [
-                (x.split(":")[0].strip(), x.split(":")[1].strip())
-                for x in s
-                if x.strip() != ""
-            ]
-        except IndexError as err:
+        if style and ":" not in style:
             raise ValueError(
                 "Styles supplied as string must follow CSS rule formats, "
                 f"for example 'attr: val;'. '{style}' was given."
-            ) from err
+            )
+        s = style.split(";")
+        return [
+            (x.split(":")[0].strip(), ":".join(x.split(":")[1:]).strip())
+            for x in s
+            if x.strip() != ""
+        ]
+
     return style
 
 

pandas/tests/apply/test_frame_apply.py

@@ -741,8 +741,9 @@ def test_apply_category_equalness(val):
 
     result = df.a.apply(lambda x: x == val)
     expected = Series(
-        [np.nan if pd.isnull(x) else x == val for x in df_values], name="a"
+        [False if pd.isnull(x) else x == val for x in df_values], name="a"
     )
+    # False since behavior of NaN for categorical dtype has been changed (GH 59966)
     tm.assert_series_equal(result, expected)
 
 

pandas/tests/apply/test_series_apply.py

@@ -236,10 +236,10 @@ def test_apply_categorical_with_nan_values(series, by_row):
         with pytest.raises(AttributeError, match=msg):
             s.apply(lambda x: x.split("-")[0], by_row=by_row)
         return
-
-    result = s.apply(lambda x: x.split("-")[0], by_row=by_row)
+    # NaN for cat dtype fixed in (GH 59966)
+    result = s.apply(lambda x: x.split("-")[0] if pd.notna(x) else False, by_row=by_row)
     result = result.astype(object)
-    expected = Series(["1", "1", np.nan], dtype="category")
+    expected = Series(["1", "1", False], dtype="category")
     expected = expected.astype(object)
     tm.assert_series_equal(result, expected)
 

pandas/tests/arrays/sparse/test_accessor.py

@@ -252,3 +252,7 @@ def test_with_column_named_sparse(self):
         # https://github.com/pandas-dev/pandas/issues/30758
         df = pd.DataFrame({"sparse": pd.arrays.SparseArray([1, 2])})
         assert isinstance(df.sparse, pd.core.arrays.sparse.accessor.SparseFrameAccessor)
+
+    def test_subclassing(self):
+        df = tm.SubclassedDataFrame({"sparse": pd.arrays.SparseArray([1, 2])})
+        assert isinstance(df.sparse.to_dense(), tm.SubclassedDataFrame)

pandas/tests/io/formats/style/test_style.py

@@ -886,8 +886,19 @@ def test_maybe_convert_css_to_tuples(self):
         expected = []
         assert maybe_convert_css_to_tuples("") == expected
 
+        # issue #59623
+        expected = [("a", "b"), ("c", "url('data:123')")]
+        assert maybe_convert_css_to_tuples("a:b;c: url('data:123');") == expected
+
+        # if no value, return attr and empty string
+        expected = [("a", ""), ("c", "")]
+        assert maybe_convert_css_to_tuples("a:;c: ") == expected
+
     def test_maybe_convert_css_to_tuples_err(self):
-        msg = "Styles supplied as string must follow CSS rule formats"
+        msg = (
+            "Styles supplied as string must follow CSS rule formats, "
+            "for example 'attr: val;'. 'err' was given."
+        )
         with pytest.raises(ValueError, match=msg):
             maybe_convert_css_to_tuples("err")
 

pandas/tests/io/formats/test_format.py

@@ -375,12 +375,29 @@ def test_repr_min_rows(self):
             (None, "{:.3f}", "None"),
             ("", "{:.2f}", ""),
             (112345.6789, "{:6.3f}", "112345.679"),
+            ("foo      foo", None, "foo      foo"),
+            (" foo", None, "foo"),
+            (
+                "foo foo       foo",
+                None,
+                "foo foo       foo",
+            ),  # odd no.of spaces
+            (
+                "foo foo    foo",
+                None,
+                "foo foo    foo",
+            ),  # even no.of spaces
         ],
     )
     def test_repr_float_formatting_html_output(
         self, data, format_option, expected_values
     ):
-        with option_context("display.float_format", format_option.format):
+        if format_option is not None:
+            with option_context("display.float_format", format_option.format):
+                df = DataFrame({"A": [data]})
+                html_output = df._repr_html_()
+                assert expected_values in html_output
+        else:
             df = DataFrame({"A": [data]})
             html_output = df._repr_html_()
             assert expected_values in html_output