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Raise a clear error when grouped_bar gets singular label/color (#30739) #32006

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Raise a clear error when grouped_bar gets singular label/color (#30739) #32006

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14 changes: 14 additions & 0 deletions lib/matplotlib/axes/_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3288,6 +3288,20 @@ def grouped_bar(self, heights, *, positions=None, group_spacing=1.5, bar_spacing
boxplot(values, positions=..., tick_labels=...)

"""
# grouped_bar() controls the label and color of each dataset's bars via the
# dedicated *labels* and *colors* parameters, and passes them positionally to
# bar(). A 'label' or 'color' in kwargs would therefore be passed to bar()
# twice, raising an opaque "multiple values for keyword argument" TypeError.
# Reject them early with an actionable message pointing to the plural
# parameters (see #30739).
for kwarg, alternative in [("color", "colors"), ("label", "labels")]:
if kwarg in kwargs:
raise TypeError(
f"grouped_bar() got an unexpected keyword argument '{kwarg}'. "
f"grouped_bar() sets the {kwarg} of each dataset's bars "
f"internally; use '{alternative}' to control the per-dataset "
f"{kwarg}s.")

if cbook._is_pandas_dataframe(heights):
if labels is None:
labels = heights.columns.tolist()
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14 changes: 14 additions & 0 deletions lib/matplotlib/tests/test_axes.py
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Expand Up @@ -2315,6 +2315,20 @@ def test_grouped_bar_hatch_sequence():
assert rect.get_hatch() == hatch


@pytest.mark.parametrize("kwarg, alternative", [("label", "labels"),
("color", "colors")])
def test_grouped_bar_reject_singular_label_color(kwarg, alternative):
# grouped_bar() passes the per-dataset label/color to bar() itself, so a
# 'label' or 'color' in kwargs would be passed twice and raise an opaque
# "multiple values for keyword argument" TypeError. It should instead fail
# early with a message pointing to the plural parameter. See #30739.
fig, ax = plt.subplots()
heights = [np.array([1, 2]), np.array([2, 3])]
with pytest.raises(TypeError, match=f"unexpected keyword argument '{kwarg}'.*"
f"use '{alternative}'"):
ax.grouped_bar(heights, **{kwarg: "dataset"})


def test_boxplot_dates_pandas(pd):
# smoke test for boxplot and dates in pandas
data = np.random.rand(5, 2)
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