Revert renaming labels to tick_labels in boxplot_stats()

timhoffm · timhoffm · commit d8cf8f3353a8 · 2024-03-13T22:36:00.000+01:00
This is up for debate: I'm only +0.2 here. The renaming was done in #27901, which renamed the parameter `labels` to `tick_labels` for `boxplot()` and `bxp()`. One can take two views here: - If `boxplot_stats()` is specifically for the input of `bxp()`, one can justify the renaming as being consistent with the `bxp()` signature. Note however, that the returned dict still contains the key "label" for back-compatibility. So that brings us an inconsistency between the parameter name and the returned dict key. - One can alternatively view `boxplot_stats()` as a generic function to define box parameters. Here, we'd only have a general `label` for the boy and no information that this should be used as tick label. If we could make a clean transition and also rename the dict key, I would tend to go with the first view. But the inevitable inconsistency of the fist view let's me sway towards the second view, so that with the revert, we've effectively not touched `boxplot_stats()`.
diff --git a/lib/matplotlib/cbook.py b/lib/matplotlib/cbook.py
@@ -1126,8 +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,
+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
@@ -1162,14 +1161,10 @@ 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
@@ -1245,13 +1240,13 @@ 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 = {}
