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Revert renaming labels to tick_labels in boxplot_stats() #27916

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Merged
merged 1 commit into from
Mar 15, 2024
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Revert renaming labels to tick_labels in boxplot_stats() #27916

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2 changes: 1 addition & 1 deletion galleries/examples/statistics/bxp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@
labels = list('ABCD')

# compute the boxplot stats
stats = cbook.boxplot_stats(data, tick_labels=labels, bootstrap=10000)
stats = cbook.boxplot_stats(data, labels=labels, bootstrap=10000)

# %%
# After we've computed the stats, we can go through and change anything.
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2 changes: 1 addition & 1 deletion lib/matplotlib/axes/_axes.py
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Expand Up @@ -4001,7 +4001,7 @@ def boxplot(self, x, notch=None, sym=None, vert=None, whis=None,
bootstrap = mpl.rcParams['boxplot.bootstrap']

bxpstats = cbook.boxplot_stats(x, whis=whis, bootstrap=bootstrap,
tick_labels=tick_labels, autorange=autorange)
labels=tick_labels, autorange=autorange)
if notch is None:
notch = mpl.rcParams['boxplot.notch']
if vert is None:
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20 changes: 7 additions & 13 deletions lib/matplotlib/cbook.py
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Expand Up @@ -1126,9 +1126,7 @@ def _broadcast_with_masks(*args, compress=False):
return inputs


@_api.rename_parameter("3.9", "labels", "tick_labels")
def boxplot_stats(X, whis=1.5, bootstrap=None, tick_labels=None,
autorange=False):
def boxplot_stats(X, whis=1.5, bootstrap=None, labels=None, autorange=False):
r"""
Return a list of dictionaries of statistics used to draw a series of box
and whisker plots using `~.Axes.bxp`.
Expand Down Expand Up @@ -1162,14 +1160,10 @@ def boxplot_stats(X, whis=1.5, bootstrap=None, tick_labels=None,
Number of times the confidence intervals around the median
should be bootstrapped (percentile method).

tick_labels : array-like, optional
labels : list of str, optional
Labels for each dataset. Length must be compatible with
dimensions of *X*.

.. versionchanged:: 3.9
Renamed from *labels*, which is deprecated since 3.9
and will be removed in 3.11.

autorange : bool, optional (False)
When `True` and the data are distributed such that the 25th and 75th
percentiles are equal, ``whis`` is set to (0, 100) such that the
Expand Down Expand Up @@ -1245,13 +1239,13 @@ def _compute_conf_interval(data, med, iqr, bootstrap):
X = _reshape_2D(X, "X")

ncols = len(X)
if tick_labels is None:
tick_labels = itertools.repeat(None)
elif len(tick_labels) != ncols:
raise ValueError("Dimensions of tick_labels and X must be compatible")
if labels is None:
labels = itertools.repeat(None)
elif len(labels) != ncols:
raise ValueError("Dimensions of labels and X must be compatible")

input_whis = whis
for ii, (x, label) in enumerate(zip(X, tick_labels)):
for ii, (x, label) in enumerate(zip(X, labels)):

# empty dict
stats = {}
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2 changes: 1 addition & 1 deletion lib/matplotlib/cbook.pyi
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Expand Up @@ -135,7 +135,7 @@ def boxplot_stats(
X: ArrayLike,
whis: float | tuple[float, float] = ...,
bootstrap: int | None = ...,
tick_labels: ArrayLike | None = ...,
labels: ArrayLike | None = ...,
autorange: bool = ...,
) -> list[dict[str, Any]]: ...

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4 changes: 2 additions & 2 deletions lib/matplotlib/tests/test_cbook.py
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Expand Up @@ -147,7 +147,7 @@ def test_results_whiskers_percentiles(self):

def test_results_withlabels(self):
labels = ['Test1', 2, 'Aardvark', 4]
results = cbook.boxplot_stats(self.data, tick_labels=labels)
results = cbook.boxplot_stats(self.data, labels=labels)
for lab, res in zip(labels, results):
assert res['label'] == lab

Expand All @@ -158,7 +158,7 @@ def test_results_withlabels(self):
def test_label_error(self):
labels = [1, 2]
with pytest.raises(ValueError):
cbook.boxplot_stats(self.data, tick_labels=labels)
cbook.boxplot_stats(self.data, labels=labels)

def test_bad_dims(self):
data = np.random.normal(size=(34, 34, 34))
Expand Down