fix test failures

doc/source/whatsnew/v2.1.0.rst

@@ -104,9 +104,9 @@ Other enhancements
 - Let :meth:`DataFrame.to_feather` accept a non-default :class:`Index` and non-string column names (:issue:`51787`)
 - Performance improvement in :func:`read_csv` (:issue:`52632`) with ``engine="c"``
 - :meth:`Categorical.from_codes` has gotten a ``validate`` parameter (:issue:`50975`)
+- :meth:`DataFrame.hist` and :meth:`Series.hist` use the column names as xlabels and :meth:`DataFrame.hist` supports multiple histograms in a single plot (:issue:`53281`)
 - :meth:`DataFrame.stack` gained the ``sort`` keyword to dictate whether the resulting :class:`MultiIndex` levels are sorted (:issue:`15105`)
 - :meth:`DataFrame.unstack` gained the ``sort`` keyword to dictate whether the resulting :class:`MultiIndex` levels are sorted (:issue:`15105`)
-- :meth:`DataFrame.hist` and :meth: `Series.hist` use the column names as xlabels and :meth:`DataFrame.hist` supports multiple histograms in a single plot (:issue: `53281`)
 - :meth:`DataFrameGroupby.agg` and :meth:`DataFrameGroupby.transform` now support grouping by multiple keys when the index is not a :class:`MultiIndex` for ``engine="numba"`` (:issue:`53486`)
 - :meth:`Series.explode` now supports pyarrow-backed list types (:issue:`53602`)
 - :meth:`Series.str.join` now supports ``ArrowDtype(pa.string())`` (:issue:`53646`)

pandas/plotting/_core.py

@@ -32,6 +32,7 @@
 
     from matplotlib.axes import Axes
     import numpy as np
+    from numpy._typing import NDArray
 
     from pandas._typing import IndexLabel
 
@@ -140,7 +141,7 @@ def hist_frame(
     sharey: bool = False,
     figsize: tuple[int, int] | None = None,
     layout: tuple[int, int] | None = None,
-    bins: int | Sequence[int] = None,
+    bins: int | Sequence[int] | NDArray | None = None,
     backend: str | None = None,
     legend: bool = False,
     **kwargs,

pandas/plotting/_matplotlib/hist.py

@@ -2,10 +2,11 @@
 
 from typing import (
     TYPE_CHECKING,
-    Literal,
+    Literal, Sequence,
 )
 
 import numpy as np
+from numpy._typing import NDArray
 
 from pandas.core.dtypes.common import (
     is_integer,
@@ -328,7 +329,7 @@ def _grouped_hist(
     column=None,
     by=None,
     ax=None,
-    bins: int = 50,
+    bins: int | Sequence[int] | NDArray | None = None,
     figsize: tuple[float, float] | None = None,
     layout=None,
     sharex: bool = False,
@@ -387,7 +388,7 @@ def get_column_data(obj, column_name):
         raw_column = get_column_data(grouped.obj, column_name)
         if bins_copy is None and (numeric_only or is_numeric_dtype(raw_column)):
             # precompute reused bins
-            bins = np.histogram_bin_edges(raw_column, bins="auto")
+            bins_copy = np.histogram_bin_edges(raw_column, bins="auto")
 
         for key, group in grouped:
             column_data = get_column_data(group, column_name)
@@ -398,15 +399,15 @@ def get_column_data(obj, column_name):
                 column_data,
                 alpha=alpha,
                 label=key,
-                bins=bins,
+                bins=bins_copy,
                 edgecolor=edgecolor,
                 linewidth=linewidth,
                 **kwargs,
             )
         if legend:
             ax.legend()
 
-        bins = bins_copy
+        bins_copy = bins
 
     if xrot is None:
         xrot = rot
@@ -446,7 +447,7 @@ def hist_series(
     ylabelsize: int | None = None,
     yrot=None,
     figsize: tuple[float, float] | None = None,
-    bins: int = 10,
+    bins: int | Sequence[int] | NDArray | None = None,
     legend: bool = False,
     **kwds,
 ):
@@ -524,7 +525,7 @@ def hist_frame(
     sharey: bool = False,
     figsize: tuple[float, float] | None = None,
     layout=None,
-    bins: int = 10,
+    bins: int | Sequence[int] | NDArray | None = None,
     legend: bool = False,
     alpha: float = 0.5,
     edgecolor: str = "black",