DOC: Clarify data inputs for boxplot() and violinplot()

timhoffm · timhoffm · commit 5a245bab0d1d · 2026-01-07T10:13:36.000+01:00
diff --git a/lib/matplotlib/axes/_axes.py b/lib/matplotlib/axes/_axes.py
@@ -4325,10 +4325,12 @@ def boxplot(self, x, notch=None, sym=None, vert=None,
 
         Parameters
         ----------
-        x : Array or a sequence of vectors.
-            The input data.  If a 2D array, a boxplot is drawn for each column
-            in *x*.  If a sequence of 1D arrays, a boxplot is drawn for each
-            array in *x*.
+        x : 1D array or sequence of 1D arrays or 2D array
+            The input data. Possible values:
+
+            - 1D array: A single box is drawn.
+            - sequence of 1D arrays: A box is drawn for each array in the sequence.
+            - 2D array: A box is drawn for each column in the array.
 
         notch : bool, default: :rc:`boxplot.notch`
             Whether to draw a notched boxplot (`True`), or a rectangular
@@ -8862,8 +8864,12 @@ def violinplot(self, dataset, positions=None, vert=None,
 
         Parameters
         ----------
-        dataset : Array or a sequence of vectors.
-            The input data.
+        dataset : 1D array or sequence of 1D arrays or 2D array
+            The input data. Possible values:
+
+            - 1D array: A single violin is drawn.
+            - sequence of 1D arrays: A violin is drawn for each array in the sequence.
+            - 2D array: A violin is drawn for each column in the array.
 
         positions : array-like, default: [1, 2, ..., n]
             The positions of the violins; i.e. coordinates on the x-axis for
diff --git a/lib/matplotlib/cbook.py b/lib/matplotlib/cbook.py
@@ -1463,9 +1463,13 @@ def violin_stats(X, method=("GaussianKDE", "scott"), points=100, quantiles=None)
 
     Parameters
     ----------
-    X : array-like
+    X : 1D array or sequence of 1D arrays or 2D array
         Sample data that will be used to produce the gaussian kernel density
-        estimates. Must have 2 or fewer dimensions.
+        estimates. Possible values:
+
+        - 1D array: Statistics are computed for that array.
+        - sequence of 1D arrays: Statistics are computed for each array in the sequence.
+        - 2D array: Statistics are computed for each column in the array.
 
     method : (name, bw_method) or callable,
         The method used to calculate the kernel density estimate for each
