merge with upstream

Author: gangula-karthik

doc/source/conf.py

@@ -114,6 +114,8 @@
                 ):
                     exclude_patterns.append(rel_fname)
                 elif single_doc and rel_fname != pattern:
+                    if "\\" in rel_fname:
+                        rel_fname = rel_fname.replace("\\", "/")
                     exclude_patterns.append(rel_fname)
 
 with open(os.path.join(source_path, "index.rst.template"), encoding="utf-8") as f:

doc/source/development/community.rst

@@ -114,7 +114,7 @@ people who are hesitant to bring up their questions or ideas on a large public
 mailing list or GitHub.
 
 If this sounds like the right place for you, you are welcome to join using
-`this link <https://join.slack.com/t/pandas-dev-community/shared_invite/zt-2blg6u9k3-K6_XvMRDZWeH7Id274UeIg>`_!
+`this link <https://join.slack.com/t/pandas-dev-community/shared_invite/zt-3813u5fme-hmp5izpbeFl9G8~smrkE~A>`_!
 Please remember to follow our `Code of Conduct <https://pandas.pydata.org/community/coc.html>`_,
 and be aware that our admins are monitoring for irrelevant messages and will remove folks who use
 our

doc/source/user_guide/enhancingperf.rst

@@ -50,7 +50,7 @@ We have a :class:`DataFrame` to which we want to apply a function row-wise.
        {
            "a": np.random.randn(1000),
            "b": np.random.randn(1000),
-           "N": np.random.randint(100, 1000, (1000)),
+           "N": np.random.randint(100, 1000, (1000), dtype="int64"),
            "x": "x",
        }
    )
@@ -83,7 +83,7 @@ using the `prun ipython magic function <https://ipython.readthedocs.io/en/stable
 .. ipython:: python
 
    # most time consuming 4 calls
-   %prun -l 4 df.apply(lambda x: integrate_f(x["a"], x["b"], x["N"]), axis=1)  # noqa E999
+   %prun -l 4 df.apply(lambda x: integrate_f(x['a'], x['b'], x['N']), axis=1)
 
 By far the majority of time is spend inside either ``integrate_f`` or ``f``,
 hence we'll concentrate our efforts cythonizing these two functions.
@@ -164,7 +164,7 @@ can be improved by passing an ``np.ndarray``.
 
 .. ipython:: python
 
-   %prun -l 4 df.apply(lambda x: integrate_f_typed(x["a"], x["b"], x["N"]), axis=1)
+   %prun -l 4 df.apply(lambda x: integrate_f_typed(x['a'], x['b'], x['N']), axis=1)
 
 .. ipython::
 
@@ -204,7 +204,7 @@ calls are needed to utilize this function.
 
 .. ipython:: python
 
-   %timeit apply_integrate_f(df["a"].to_numpy(), df["b"].to_numpy(), df["N"].to_numpy())
+   %timeit apply_integrate_f(df['a'].to_numpy(), df['b'].to_numpy(), df['N'].to_numpy())
 
 Performance has improved from the prior implementation by almost ten times.
 
@@ -218,7 +218,7 @@ and ``wraparound`` checks can yield more performance.
 
 .. ipython:: python
 
-   %prun -l 4 apply_integrate_f(df["a"].to_numpy(), df["b"].to_numpy(), df["N"].to_numpy())
+   %prun -l 4 apply_integrate_f(df['a'].to_numpy(), df['b'].to_numpy(), df['N'].to_numpy())
 
 .. ipython::
 
@@ -253,7 +253,7 @@ and ``wraparound`` checks can yield more performance.
 
 .. ipython:: python
 
-   %timeit apply_integrate_f_wrap(df["a"].to_numpy(), df["b"].to_numpy(), df["N"].to_numpy())
+   %timeit apply_integrate_f_wrap(df['a'].to_numpy(), df['b'].to_numpy(), df['N'].to_numpy())
 
 However, a loop indexer ``i`` accessing an invalid location in an array would cause a segfault because memory access isn't checked.
 For more about ``boundscheck`` and ``wraparound``, see the Cython docs on

doc/source/whatsnew/v2.3.1.rst

@@ -26,7 +26,7 @@ Fixed regressions
 
 Bug fixes
 ~~~~~~~~~
--
+- Fixed bug in :meth:`DataFrame.explode` and :meth:`Series.explode` where methods would fail with ``dtype="str"`` (:issue:`61623`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_231.other:

pandas/core/arrays/arrow/array.py

@@ -1935,9 +1935,9 @@ def _explode(self):
         """
         # child class explode method supports only list types; return
         # default implementation for non list types.
-        if not (
-            pa.types.is_list(self.dtype.pyarrow_dtype)
-            or pa.types.is_large_list(self.dtype.pyarrow_dtype)
+        if not hasattr(self.dtype, "pyarrow_dtype") or (
+            not pa.types.is_list(self.dtype.pyarrow_dtype)
+            and not pa.types.is_large_list(self.dtype.pyarrow_dtype)
         ):
             return super()._explode()
         values = self

pandas/io/formats/excel.py

@@ -303,13 +303,13 @@ def _border_style(
         #       'slantDashDot'
         #       'thick'
         #       'thin'
-        if width is None and style is None and color is None:
-            # Return None will remove "border" from style dictionary
-            return None
-
         if width is None and style is None:
-            # Return "none" will keep "border" in style dictionary
-            return "none"
+            if color is None:
+                # Return None will remove "border" from style dictionary
+                return None
+            else:
+                # Return "none" will keep "border" in style dictionary
+                return "none"
 
         if style in ("none", "hidden"):
             return "none"
@@ -411,11 +411,6 @@ def _get_decoration(self, props: Mapping[str, str]) -> Sequence[str]:
         else:
             return ()
 
-    def _get_underline(self, decoration: Sequence[str]) -> str | None:
-        if "underline" in decoration:
-            return "single"
-        return None
-
     def _get_shadow(self, props: Mapping[str, str]) -> bool | None:
         if "text-shadow" in props:
             return bool(re.search("^[^#(]*[1-9]", props["text-shadow"]))

pandas/tests/frame/methods/test_explode.py

@@ -297,3 +297,11 @@ def test_multi_columns_nan_empty():
         index=[0, 0, 1, 2, 3, 3],
     )
     tm.assert_frame_equal(result, expected)
+
+
+def test_str_dtype():
+    # https://github.com/pandas-dev/pandas/pull/61623
+    df = pd.DataFrame({"a": ["x", "y"]}, dtype="str")
+    result = df.explode(column="a")
+    assert result is not df
+    tm.assert_frame_equal(result, df)

pandas/tests/io/formats/test_to_excel.py

@@ -156,6 +156,14 @@
             "border-top-style: solid; border-top-width: 4pt",
             {"border": {"top": {"style": "thick"}}},
         ),
+        (
+            "border-top-style: solid; border-top-width: none",
+            {"border": {"top": {"style": "none"}}},
+        ),
+        (
+            "border-top-style: solid; border-top-width: 0.000001pt",
+            {"border": {"top": {"style": "none"}}},
+        ),
         (
             "border-top-style: dotted",
             {"border": {"top": {"style": "mediumDashDotDot"}}},
@@ -194,6 +202,10 @@
             "border-top-color: blue",
             {"border": {"top": {"color": "0000FF", "style": "none"}}},
         ),
+        (
+            "border-top-style: slantDashDot; border-top-color: blue",
+            {"border": {"top": {"style": "slantDashDot", "color": "0000FF"}}},
+        ),
         # ALIGNMENT
         # - horizontal
         ("text-align: center", {"alignment": {"horizontal": "center"}}),
@@ -249,6 +261,20 @@ def test_css_to_excel_multiple():
     } == actual
 
 
+@pytest.mark.parametrize(
+    "css",
+    [
+        "border-top-style: unhandled-border-style",
+        "border-style: another-unhandled-style",
+    ],
+)
+def test_css_to_excel_unhandled_border_style_warns(css):
+    """Test that unhandled border styles raise a CSSWarning."""
+    convert = CSSToExcelConverter()
+    with tm.assert_produces_warning(CSSWarning, match="Unhandled border style format"):
+        convert(css)
+
+
 @pytest.mark.parametrize(
     "css,inherited,expected",
     [
@@ -330,6 +356,23 @@ def test_css_to_excel_bad_colors(input_color):
         assert expected == convert(css)
 
 
+@pytest.mark.parametrize("input_color", ["#", "#1234567"])
+def test_css_to_excel_invalid_color_raises(input_color):
+    """Test that invalid colors raise a ValueError."""
+    css = (
+        f"border-top-color: {input_color}; "
+        f"border-right-color: {input_color}; "
+        f"border-bottom-color: {input_color}; "
+        f"border-left-color: {input_color}; "
+        f"background-color: {input_color}; "
+        f"color: {input_color}"
+    )
+
+    convert = CSSToExcelConverter()
+    with pytest.raises(ValueError, match=f"Unexpected color {input_color}"):
+        convert(css)
+
+
 def tests_css_named_colors_valid():
     upper_hexs = set(map(str.upper, string.hexdigits))
     for color in CSSToExcelConverter.NAMED_COLORS.values():

pandas/tests/series/methods/test_explode.py

@@ -175,3 +175,11 @@ def test_explode_pyarrow_non_list_type(ignore_index):
     result = ser.explode(ignore_index=ignore_index)
     expected = pd.Series([1, 2, 3], dtype="int64[pyarrow]", index=[0, 1, 2])
     tm.assert_series_equal(result, expected)
+
+
+def test_str_dtype():
+    # https://github.com/pandas-dev/pandas/pull/61623
+    ser = pd.Series(["x", "y"], dtype="str")
+    result = ser.explode()
+    assert result is not ser
+    tm.assert_series_equal(result, ser)