REF: make plotting less stateful (4)

pandas/plotting/_matplotlib/boxplot.py

@@ -10,6 +10,7 @@
 from matplotlib.artist import setp
 import numpy as np
 
+from pandas.util._decorators import cache_readonly
 from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import is_dict_like
@@ -132,15 +133,29 @@ def _validate_color_args(self):
         else:
             self.color = None
 
+    @cache_readonly
+    def _color_attrs(self):
         # get standard colors for default
-        colors = get_standard_colors(num_colors=3, colormap=self.colormap, color=None)
         # use 2 colors by default, for box/whisker and median
         # flier colors isn't needed here
         # because it can be specified by ``sym`` kw
-        self._boxes_c = colors[0]
-        self._whiskers_c = colors[0]
-        self._medians_c = colors[2]
-        self._caps_c = colors[0]
+        return get_standard_colors(num_colors=3, colormap=self.colormap, color=None)
+
+    @cache_readonly
+    def _boxes_c(self):
+        return self._color_attrs[0]
+
+    @cache_readonly
+    def _whiskers_c(self):
+        return self._color_attrs[0]
+
+    @cache_readonly
+    def _medians_c(self):
+        return self._color_attrs[2]
+
+    @cache_readonly
+    def _caps_c(self):
+        return self._color_attrs[0]
 
     def _get_colors(
         self,

pandas/plotting/_matplotlib/core.py

@@ -90,6 +90,8 @@
         npt,
     )
 
+    from pandas import Series
+
 
 def _color_in_style(style: str) -> bool:
     """
@@ -471,7 +473,8 @@ def generate(self) -> None:
             self._post_plot_logic(ax, self.data)
 
     @final
-    def _has_plotted_object(self, ax: Axes) -> bool:
+    @staticmethod
+    def _has_plotted_object(ax: Axes) -> bool:
         """check whether ax has data"""
         return len(ax.lines) != 0 or len(ax.artists) != 0 or len(ax.containers) != 0
 
@@ -576,7 +579,8 @@ def result(self):
                 return self.axes[0]
 
     @final
-    def _convert_to_ndarray(self, data):
+    @staticmethod
+    def _convert_to_ndarray(data):
         # GH31357: categorical columns are processed separately
         if isinstance(data.dtype, CategoricalDtype):
             return data
@@ -767,6 +771,7 @@ def _apply_axis_properties(
                 if fontsize is not None:
                     label.set_fontsize(fontsize)
 
+    @final
     @property
     def legend_title(self) -> str | None:
         if not isinstance(self.data.columns, ABCMultiIndex):
@@ -836,7 +841,8 @@ def _make_legend(self) -> None:
                     ax.legend(loc="best")
 
     @final
-    def _get_ax_legend(self, ax: Axes):
+    @staticmethod
+    def _get_ax_legend(ax: Axes):
         """
         Take in axes and return ax and legend under different scenarios
         """
@@ -1454,7 +1460,7 @@ def _plot(  # type: ignore[override]
         return lines
 
     @final
-    def _ts_plot(self, ax: Axes, x, data, style=None, **kwds):
+    def _ts_plot(self, ax: Axes, x, data: Series, style=None, **kwds):
         # accept x to be consistent with normal plot func,
         # x is not passed to tsplot as it uses data.index as x coordinate
         # column_num must be in kwds for stacking purpose
@@ -1471,11 +1477,13 @@ def _ts_plot(self, ax: Axes, x, data, style=None, **kwds):
 
         lines = self._plot(ax, data.index, data.values, style=style, **kwds)
         # set date formatter, locators and rescale limits
-        format_dateaxis(ax, ax.freq, data.index)
+        # error: Argument 3 to "format_dateaxis" has incompatible type "Index";
+        # expected "DatetimeIndex | PeriodIndex"
+        format_dateaxis(ax, ax.freq, data.index)  # type: ignore[arg-type]
         return lines
 
     @final
-    def _get_stacking_id(self):
+    def _get_stacking_id(self) -> int | None:
         if self.stacked:
             return id(self.data)
         else:

pandas/plotting/_matplotlib/hist.py

@@ -56,12 +56,16 @@ def __init__(
         data,
         bins: int | np.ndarray | list[np.ndarray] = 10,
         bottom: int | np.ndarray = 0,
+        *,
+        range=None,
         **kwargs,
     ) -> None:
         if is_list_like(bottom):
             bottom = np.array(bottom)
         self.bottom = bottom
 
+        self._bin_range = range
+
         self.xlabel = kwargs.get("xlabel")
         self.ylabel = kwargs.get("ylabel")
         # Do not call LinePlot.__init__ which may fill nan
@@ -85,7 +89,7 @@ def _calculate_bins(self, data: DataFrame, bins) -> np.ndarray:
         values = np.ravel(nd_values)
         values = values[~isna(values)]
 
-        hist, bins = np.histogram(values, bins=bins, range=self.kwds.get("range", None))
+        hist, bins = np.histogram(values, bins=bins, range=self._bin_range)
         return bins
 
     # error: Signature of "_plot" incompatible with supertype "LinePlot"
@@ -209,24 +213,23 @@ def __init__(self, data, bw_method=None, ind=None, **kwargs) -> None:
         self.bw_method = bw_method
         self.ind = ind
 
-    def _get_ind(self, y):
-        if self.ind is None:
+    @staticmethod
+    def _get_ind(y, ind):
+        if ind is None:
             # np.nanmax() and np.nanmin() ignores the missing values
             sample_range = np.nanmax(y) - np.nanmin(y)
             ind = np.linspace(
                 np.nanmin(y) - 0.5 * sample_range,
                 np.nanmax(y) + 0.5 * sample_range,
                 1000,
             )
-        elif is_integer(self.ind):
+        elif is_integer(ind):
             sample_range = np.nanmax(y) - np.nanmin(y)
             ind = np.linspace(
                 np.nanmin(y) - 0.5 * sample_range,
                 np.nanmax(y) + 0.5 * sample_range,
-                self.ind,
+                ind,
             )
-        else:
-            ind = self.ind
         return ind
 
     @classmethod
@@ -252,7 +255,7 @@ def _plot(
 
     def _make_plot_keywords(self, kwds, y):
         kwds["bw_method"] = self.bw_method
-        kwds["ind"] = self._get_ind(y)
+        kwds["ind"] = self._get_ind(y, ind=self.ind)
         return kwds
 
     def _post_plot_logic(self, ax, data) -> None:

pandas/plotting/_matplotlib/timeseries.py

@@ -48,6 +48,7 @@
         DataFrame,
         DatetimeIndex,
         Index,
+        PeriodIndex,
         Series,
     )
 
@@ -300,16 +301,17 @@ def maybe_convert_index(ax: Axes, data):
     return data
 
 
-# Patch methods for subplot. Only format_dateaxis is currently used.
-# Do we need the rest for convenience?
+# Patch methods for subplot.
 
 
 def _format_coord(freq, t, y) -> str:
     time_period = Period(ordinal=int(t), freq=freq)
     return f"t = {time_period}  y = {y:8f}"
 
 
-def format_dateaxis(subplot, freq, index) -> None:
+def format_dateaxis(
+    subplot, freq: BaseOffset, index: DatetimeIndex | PeriodIndex
+) -> None:
     """
     Pretty-formats the date axis (x-axis).