TYP: plotting, make weights kwd explicit

pandas/plotting/_matplotlib/boxplot.py

@@ -93,7 +93,7 @@ def __init__(self, data, return_type: str = "axes", **kwargs) -> None:
     # error: Signature of "_plot" incompatible with supertype "MPLPlot"
     @classmethod
     def _plot(  # type: ignore[override]
-        cls, ax, y, column_num=None, return_type: str = "axes", **kwds
+        cls, ax: Axes, y, column_num=None, return_type: str = "axes", **kwds
     ):
         if y.ndim == 2:
             y = [remove_na_arraylike(v) for v in y]

pandas/plotting/_matplotlib/core.py

@@ -11,6 +11,7 @@
 )
 from typing import (
     TYPE_CHECKING,
+    Any,
     Literal,
     final,
 )
@@ -998,7 +999,9 @@ def on_right(self, i: int):
             return self.data.columns[i] in self.secondary_y
 
     @final
-    def _apply_style_colors(self, colors, kwds, col_num, label: str):
+    def _apply_style_colors(
+        self, colors, kwds: dict[str, Any], col_num: int, label: str
+    ):
         """
         Manage style and color based on column number and its label.
         Returns tuple of appropriate style and kwds which "color" may be added.

pandas/plotting/_matplotlib/hist.py

@@ -2,7 +2,9 @@
 
 from typing import (
     TYPE_CHECKING,
+    Any,
     Literal,
+    final,
 )
 
 import numpy as np
@@ -58,13 +60,15 @@ def __init__(
         bottom: int | np.ndarray = 0,
         *,
         range=None,
+        weights=None,
         **kwargs,
     ) -> None:
         if is_list_like(bottom):
             bottom = np.array(bottom)
         self.bottom = bottom
 
         self._bin_range = range
+        self.weights = weights
 
         self.xlabel = kwargs.get("xlabel")
         self.ylabel = kwargs.get("ylabel")
@@ -96,7 +100,7 @@ def _calculate_bins(self, data: DataFrame, bins) -> np.ndarray:
     @classmethod
     def _plot(  # type: ignore[override]
         cls,
-        ax,
+        ax: Axes,
         y,
         style=None,
         bottom: int | np.ndarray = 0,
@@ -140,7 +144,7 @@ def _make_plot(self, fig: Figure) -> None:
             if style is not None:
                 kwds["style"] = style
 
-            kwds = self._make_plot_keywords(kwds, y)
+            self._make_plot_keywords(kwds, y)
 
             # the bins is multi-dimension array now and each plot need only 1-d and
             # when by is applied, label should be columns that are grouped
@@ -149,21 +153,8 @@ def _make_plot(self, fig: Figure) -> None:
                 kwds["label"] = self.columns
                 kwds.pop("color")
 
-            # We allow weights to be a multi-dimensional array, e.g. a (10, 2) array,
-            # and each sub-array (10,) will be called in each iteration. If users only
-            # provide 1D array, we assume the same weights is used for all iterations
-            weights = kwds.get("weights", None)
-            if weights is not None:
-                if np.ndim(weights) != 1 and np.shape(weights)[-1] != 1:
-                    try:
-                        weights = weights[:, i]
-                    except IndexError as err:
-                        raise ValueError(
-                            "weights must have the same shape as data, "
-                            "or be a single column"
-                        ) from err
-                weights = weights[~isna(y)]
-                kwds["weights"] = weights
+            if self.weights is not None:
+                kwds["weights"] = self._get_column_weights(self.weights, i, y)
 
             y = reformat_hist_y_given_by(y, self.by)
 
@@ -175,12 +166,29 @@ def _make_plot(self, fig: Figure) -> None:
 
             self._append_legend_handles_labels(artists[0], label)
 
-    def _make_plot_keywords(self, kwds, y):
+    def _make_plot_keywords(self, kwds: dict[str, Any], y) -> None:
         """merge BoxPlot/KdePlot properties to passed kwds"""
         # y is required for KdePlot
         kwds["bottom"] = self.bottom
         kwds["bins"] = self.bins
-        return kwds
+
+    @final
+    @staticmethod
+    def _get_column_weights(weights, i: int, y):
+        # We allow weights to be a multi-dimensional array, e.g. a (10, 2) array,
+        # and each sub-array (10,) will be called in each iteration. If users only
+        # provide 1D array, we assume the same weights is used for all iterations
+        if weights is not None:
+            if np.ndim(weights) != 1 and np.shape(weights)[-1] != 1:
+                try:
+                    weights = weights[:, i]
+                except IndexError as err:
+                    raise ValueError(
+                        "weights must have the same shape as data, "
+                        "or be a single column"
+                    ) from err
+            weights = weights[~isna(y)]
+        return weights
 
     def _post_plot_logic(self, ax: Axes, data) -> None:
         if self.orientation == "horizontal":
@@ -207,11 +215,14 @@ def _kind(self) -> Literal["kde"]:
     def orientation(self) -> Literal["vertical"]:
         return "vertical"
 
-    def __init__(self, data, bw_method=None, ind=None, **kwargs) -> None:
+    def __init__(
+        self, data, bw_method=None, ind=None, *, weights=None, **kwargs
+    ) -> None:
         # Do not call LinePlot.__init__ which may fill nan
         MPLPlot.__init__(self, data, **kwargs)  # pylint: disable=non-parent-init-called
         self.bw_method = bw_method
         self.ind = ind
+        self.weights = weights
 
     @staticmethod
     def _get_ind(y, ind):
@@ -233,9 +244,10 @@ def _get_ind(y, ind):
         return ind
 
     @classmethod
-    def _plot(
+    # error: Signature of "_plot" incompatible with supertype "MPLPlot"
+    def _plot(  #  type: ignore[override]
         cls,
-        ax,
+        ax: Axes,
         y,
         style=None,
         bw_method=None,
@@ -253,10 +265,9 @@ def _plot(
         lines = MPLPlot._plot(ax, ind, y, style=style, **kwds)
         return lines
 
-    def _make_plot_keywords(self, kwds, y):
+    def _make_plot_keywords(self, kwds: dict[str, Any], y) -> None:
         kwds["bw_method"] = self.bw_method
         kwds["ind"] = self._get_ind(y, ind=self.ind)
-        return kwds
 
     def _post_plot_logic(self, ax, data) -> None:
         ax.set_ylabel("Density")