BUG: Fixed issue with bar plots not stacking correctly when 'stacked' and 'subplots' are used together

doc/source/whatsnew/v3.0.0.rst

@@ -795,6 +795,7 @@ Period
 Plotting
 ^^^^^^^^
 - Bug in :meth:`.DataFrameGroupBy.boxplot` failed when there were multiple groupings (:issue:`14701`)
+- Bug in :meth:`DataFrame.plot.bar` when ``subplots`` and ``stacked=True`` are used in conjunction which causes incorrect stacking. (:issue:`61018`)
 - Bug in :meth:`DataFrame.plot.bar` with ``stacked=True`` where labels on stacked bars with zero-height segments were incorrectly positioned at the base instead of the label position of the previous segment (:issue:`59429`)
 - Bug in :meth:`DataFrame.plot.line` raising ``ValueError`` when set both color and a ``dict`` style (:issue:`59461`)
 - Bug in :meth:`DataFrame.plot` that causes a shift to the right when the frequency multiplier is greater than one. (:issue:`57587`)

pandas/plotting/_matplotlib/core.py

@@ -1928,6 +1928,27 @@ def _make_plot(self, fig: Figure) -> None:
         K = self.nseries
 
         data = self.data.fillna(0)
+
+        _stacked_subplots_ind: dict[int, int] = {}
+        _stacked_subplots_offsets = []
+
+        self.subplots: list[Any]
+        if self.subplots:
+            subplots_flag = 1
+        else:
+            subplots_flag = 0
+
+        if subplots_flag & self.stacked:
+            sub_range = range(len(self.subplots))
+            ss_temp = {
+                x: self.subplots[x] for x in sub_range if len(self.subplots[x]) > 1
+            }
+            for k, v in ss_temp.items():
+                for x in v:
+                    _stacked_subplots_ind.setdefault(int(x), k)
+
+                _stacked_subplots_offsets.append([0, 0])
+
         for i, (label, y) in enumerate(self._iter_data(data=data)):
             ax = self._get_ax(i)
             kwds = self.kwds.copy()
@@ -1953,7 +1974,28 @@ def _make_plot(self, fig: Figure) -> None:
             start = start + self._start_base
 
             kwds["align"] = self._align
-            if self.subplots:
+
+            if i in _stacked_subplots_ind:
+                offset_index = _stacked_subplots_ind[i]
+                pos_prior, neg_prior = _stacked_subplots_offsets[offset_index]  # type:ignore[assignment]
+                mask = y >= 0
+                start = np.where(mask, pos_prior, neg_prior) + self._start_base
+                w = self.bar_width / 2
+                rect = self._plot(
+                    ax,
+                    self.ax_pos + w,
+                    y,
+                    self.bar_width,
+                    start=start,
+                    label=label,
+                    log=self.log,
+                    **kwds,
+                )
+                pos_new = pos_prior + np.where(mask, y, 0)
+                neg_new = neg_prior + np.where(mask, 0, y)
+                _stacked_subplots_offsets[offset_index] = [pos_new, neg_new]
+
+            elif self.subplots:
                 w = self.bar_width / 2
                 rect = self._plot(
                     ax,

pandas/tests/plotting/test_misc.py

@@ -681,3 +681,129 @@ def test_bar_plt_xaxis_intervalrange(self):
             (a.get_text() == b.get_text())
             for a, b in zip(s.plot.bar().get_xticklabels(), expected)
         )
+
+
+@pytest.fixture(scope="class")
+def BSS_data():
+    return np.random.default_rng(3).integers(0, 100, 5)
+
+
+@pytest.fixture(scope="class")
+def BSS_df(BSS_data) -> DataFrame:
+    BSS_df = DataFrame(
+        {"A": BSS_data, "B": BSS_data[::-1], "C": BSS_data[0], "D": BSS_data[-1]}
+    )
+    return BSS_df
+
+
+def _BSS_xyheight_from_ax_helper(BSS_data, ax, subplot_division):
+    subplot_data_df_list = []
+
+    # get xy and height of squares representing data, separated by subplots
+    for i in range(len(subplot_division)):
+        subplot_data = np.array(
+            [
+                (x.get_x(), x.get_y(), x.get_height())
+                for x in ax[i].findobj(plt.Rectangle)
+                if x.get_height() in BSS_data
+            ]
+        )
+        subplot_data_df_list.append(
+            DataFrame(data=subplot_data, columns=["x_coord", "y_coord", "height"])
+        )
+
+    return subplot_data_df_list
+
+
+def _BSS_subplot_checker(BSS_data, BSS_df, subplot_data_df, subplot_columns):
+    subplot_sliced_by_source = [
+        subplot_data_df.iloc[len(BSS_data) * i : len(BSS_data) * (i + 1)].reset_index()
+        for i in range(len(subplot_columns))
+    ]
+    expected_total_height = BSS_df.loc[:, subplot_columns].sum(axis=1)
+
+    for i in range(len(subplot_columns)):
+        sliced_df = subplot_sliced_by_source[i]
+        if i == 0:
+            # Checks that the bar chart starts y=0
+            assert (sliced_df["y_coord"] == 0).all
+            height_iter = sliced_df["y_coord"].add(sliced_df["height"])
+        else:
+            height_iter = height_iter + sliced_df["height"]
+
+        if i + 1 == len(subplot_columns):
+            # Checks final height matches what is expected
+            tm.assert_series_equal(
+                height_iter, expected_total_height, check_names=False, check_dtype=False
+            )
+
+        else:
+            # Checks each preceding bar ends where the next one starts
+            next_start_coord = subplot_sliced_by_source[i + 1]["y_coord"]
+            tm.assert_series_equal(
+                height_iter, next_start_coord, check_names=False, check_dtype=False
+            )
+
+
+class TestBarSubplotStacked:
+    # GH Issue 61018
+    @pytest.mark.parametrize("columns_used", [["A", "B"], ["C", "D"], ["D", "A"]])
+    def test_bar_1_subplot_1_double_stacked(self, BSS_data, BSS_df, columns_used):
+        BSS_df_trimmed = BSS_df[columns_used]
+        subplot_division = [columns_used]
+        ax = BSS_df_trimmed.plot(subplots=subplot_division, kind="bar", stacked=True)
+        subplot_data_df_list = _BSS_xyheight_from_ax_helper(
+            BSS_data, ax, subplot_division
+        )
+        for i in range(len(subplot_data_df_list)):
+            _BSS_subplot_checker(
+                BSS_data, BSS_df_trimmed, subplot_data_df_list[i], subplot_division[i]
+            )
+
+    @pytest.mark.parametrize(
+        "columns_used", [["A", "B", "C"], ["A", "C", "B"], ["D", "A", "C"]]
+    )
+    def test_bar_2_subplot_1_double_stacked(self, BSS_data, BSS_df, columns_used):
+        BSS_df_trimmed = BSS_df[columns_used]
+        subplot_division = [(columns_used[0], columns_used[1]), (columns_used[2],)]
+        ax = BSS_df_trimmed.plot(subplots=subplot_division, kind="bar", stacked=True)
+        subplot_data_df_list = _BSS_xyheight_from_ax_helper(
+            BSS_data, ax, subplot_division
+        )
+        for i in range(len(subplot_data_df_list)):
+            _BSS_subplot_checker(
+                BSS_data, BSS_df_trimmed, subplot_data_df_list[i], subplot_division[i]
+            )
+
+    @pytest.mark.parametrize(
+        "subplot_division",
+        [
+            [("A", "B"), ("C", "D")],
+            [("A", "D"), ("C", "B")],
+            [("B", "C"), ("D", "A")],
+            [("B", "D"), ("C", "A")],
+        ],
+    )
+    def test_bar_2_subplot_2_double_stacked(self, BSS_data, BSS_df, subplot_division):
+        ax = BSS_df.plot(subplots=subplot_division, kind="bar", stacked=True)
+        subplot_data_df_list = _BSS_xyheight_from_ax_helper(
+            BSS_data, ax, subplot_division
+        )
+        for i in range(len(subplot_data_df_list)):
+            _BSS_subplot_checker(
+                BSS_data, BSS_df, subplot_data_df_list[i], subplot_division[i]
+            )
+
+    @pytest.mark.parametrize(
+        "subplot_division",
+        [[("A", "B", "C")], [("A", "D", "B")], [("C", "A", "D")], [("D", "C", "A")]],
+    )
+    def test_bar_2_subplots_1_triple_stacked(self, BSS_data, BSS_df, subplot_division):
+        ax = BSS_df.plot(subplots=subplot_division, kind="bar", stacked=True)
+        subplot_data_df_list = _BSS_xyheight_from_ax_helper(
+            BSS_data, ax, subplot_division
+        )
+        for i in range(len(subplot_data_df_list)):
+            _BSS_subplot_checker(
+                BSS_data, BSS_df, subplot_data_df_list[i], subplot_division[i]
+            )