TYP: plotting

pandas/plotting/_core.py

@@ -37,11 +37,15 @@
 
     from pandas._typing import IndexLabel
 
-    from pandas import DataFrame
+    from pandas import (
+        DataFrame,
+        Series,
+    )
+    from pandas.core.groupby.generic import DataFrameGroupBy
 
 
 def hist_series(
-    self,
+    self: Series,
     by=None,
     ax=None,
     grid: bool = True,
@@ -512,7 +516,7 @@ def boxplot(
 @Substitution(data="", backend=_backend_doc)
 @Appender(_boxplot_doc)
 def boxplot_frame(
-    self,
+    self: DataFrame,
     column=None,
     by=None,
     ax=None,
@@ -542,7 +546,7 @@ def boxplot_frame(
 
 
 def boxplot_frame_groupby(
-    grouped,
+    grouped: DataFrameGroupBy,
     subplots: bool = True,
     column=None,
     fontsize: int | None = None,
@@ -843,11 +847,11 @@ class PlotAccessor(PandasObject):
     _kind_aliases = {"density": "kde"}
     _all_kinds = _common_kinds + _series_kinds + _dataframe_kinds
 
-    def __init__(self, data) -> None:
+    def __init__(self, data: Series | DataFrame) -> None:
         self._parent = data
 
     @staticmethod
-    def _get_call_args(backend_name: str, data, args, kwargs):
+    def _get_call_args(backend_name: str, data: Series | DataFrame, args, kwargs):
         """
         This function makes calls to this accessor `__call__` method compatible
         with the previous `SeriesPlotMethods.__call__` and

pandas/plotting/_matplotlib/boxplot.py

@@ -93,17 +93,18 @@ 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: Axes, y, column_num=None, return_type: str = "axes", **kwds
+        cls, ax: Axes, y: np.ndarray, column_num=None, return_type: str = "axes", **kwds
     ):
+        ys: np.ndarray | list[np.ndarray]
         if y.ndim == 2:
-            y = [remove_na_arraylike(v) for v in y]
+            ys = [remove_na_arraylike(v) for v in y]
             # Boxplot fails with empty arrays, so need to add a NaN
             #   if any cols are empty
             # GH 8181
-            y = [v if v.size > 0 else np.array([np.nan]) for v in y]
+            ys = [v if v.size > 0 else np.array([np.nan]) for v in ys]
         else:
-            y = remove_na_arraylike(y)
-        bp = ax.boxplot(y, **kwds)
+            ys = remove_na_arraylike(y)
+        bp = ax.boxplot(ys, **kwds)
 
         if return_type == "dict":
             return bp, bp
@@ -240,8 +241,7 @@ def _make_plot(self, fig: Figure) -> None:
             self.maybe_color_bp(bp)
             self._return_obj = ret
 
-            labels = [left for left, _ in self._iter_data()]
-            labels = [pprint_thing(left) for left in labels]
+            labels = [pprint_thing(left) for left in self.data.columns]
             if not self.use_index:
                 labels = [pprint_thing(key) for key in range(len(labels))]
             _set_ticklabels(
@@ -251,7 +251,7 @@ def _make_plot(self, fig: Figure) -> None:
     def _make_legend(self) -> None:
         pass
 
-    def _post_plot_logic(self, ax, data) -> None:
+    def _post_plot_logic(self, ax: Axes, data) -> None:
         # GH 45465: make sure that the boxplot doesn't ignore xlabel/ylabel
         if self.xlabel:
             ax.set_xlabel(pprint_thing(self.xlabel))

pandas/plotting/_matplotlib/core.py

@@ -7,6 +7,7 @@
 from collections.abc import (
     Hashable,
     Iterable,
+    Iterator,
     Sequence,
 )
 from typing import (
@@ -431,17 +432,15 @@ def _validate_color_args(self):
                     )
 
     @final
-    def _iter_data(self, data=None, keep_index: bool = False, fillna=None):
-        if data is None:
-            data = self.data
-        if fillna is not None:
-            data = data.fillna(fillna)
-
+    @staticmethod
+    def _iter_data(
+        data: DataFrame | dict[Hashable, Series | DataFrame]
+    ) -> Iterator[tuple[Hashable, np.ndarray]]:
         for col, values in data.items():
-            if keep_index is True:
-                yield col, values
-            else:
-                yield col, values.values
+            # This was originally written to use values.values before EAs
+            #  were implemented; adding np.asarray(...) to keep consistent
+            #  typing.
+            yield col, np.asarray(values.values)
 
     @property
     def nseries(self) -> int:
@@ -480,7 +479,7 @@ def _has_plotted_object(ax: Axes) -> bool:
         return len(ax.lines) != 0 or len(ax.artists) != 0 or len(ax.containers) != 0
 
     @final
-    def _maybe_right_yaxis(self, ax: Axes, axes_num: int):
+    def _maybe_right_yaxis(self, ax: Axes, axes_num: int) -> Axes:
         if not self.on_right(axes_num):
             # secondary axes may be passed via ax kw
             return self._get_ax_layer(ax)
@@ -643,11 +642,7 @@ def _compute_plot_data(self):
 
         numeric_data = data.select_dtypes(include=include_type, exclude=exclude_type)
 
-        try:
-            is_empty = numeric_data.columns.empty
-        except AttributeError:
-            is_empty = not len(numeric_data)
-
+        is_empty = numeric_data.shape[-1] == 0
         # no non-numeric frames or series allowed
         if is_empty:
             raise TypeError("no numeric data to plot")
@@ -669,7 +664,7 @@ def _add_table(self) -> None:
         tools.table(ax, data)
 
     @final
-    def _post_plot_logic_common(self, ax, data):
+    def _post_plot_logic_common(self, ax: Axes, data) -> None:
         """Common post process for each axes"""
         if self.orientation == "vertical" or self.orientation is None:
             self._apply_axis_properties(ax.xaxis, rot=self.rot, fontsize=self.fontsize)
@@ -688,7 +683,7 @@ def _post_plot_logic_common(self, ax, data):
             raise ValueError
 
     @abstractmethod
-    def _post_plot_logic(self, ax, data) -> None:
+    def _post_plot_logic(self, ax: Axes, data) -> None:
         """Post process for each axes. Overridden in child classes"""
 
     @final
@@ -1042,7 +1037,7 @@ def _get_colors(
         )
 
     @final
-    def _parse_errorbars(self, label, err):
+    def _parse_errorbars(self, label: str, err):
         """
         Look for error keyword arguments and return the actual errorbar data
         or return the error DataFrame/dict
@@ -1123,7 +1118,10 @@ def match_labels(data, e):
                 err = np.tile(err, (self.nseries, 1))
 
         elif is_number(err):
-            err = np.tile([err], (self.nseries, len(self.data)))
+            err = np.tile(
+                [err],  # pyright: ignore[reportGeneralTypeIssues]
+                (self.nseries, len(self.data)),
+            )
 
         else:
             msg = f"No valid {label} detected"
@@ -1404,14 +1402,14 @@ def _make_plot(self, fig: Figure) -> None:
 
             x = data.index  # dummy, not used
             plotf = self._ts_plot
-            it = self._iter_data(data=data, keep_index=True)
+            it = data.items()
         else:
             x = self._get_xticks(convert_period=True)
             # error: Incompatible types in assignment (expression has type
             # "Callable[[Any, Any, Any, Any, Any, Any, KwArg(Any)], Any]", variable has
             # type "Callable[[Any, Any, Any, Any, KwArg(Any)], Any]")
             plotf = self._plot  # type: ignore[assignment]
-            it = self._iter_data()
+            it = self._iter_data(data=self.data)
 
         stacking_id = self._get_stacking_id()
         is_errorbar = com.any_not_none(*self.errors.values())
@@ -1420,7 +1418,12 @@ def _make_plot(self, fig: Figure) -> None:
         for i, (label, y) in enumerate(it):
             ax = self._get_ax(i)
             kwds = self.kwds.copy()
-            style, kwds = self._apply_style_colors(colors, kwds, i, label)
+            style, kwds = self._apply_style_colors(
+                colors,
+                kwds,
+                i,
+                label,  # pyright: ignore[reportGeneralTypeIssues]
+            )
 
             errors = self._get_errorbars(label=label, index=i)
             kwds = dict(kwds, **errors)
@@ -1432,7 +1435,7 @@ def _make_plot(self, fig: Figure) -> None:
             newlines = plotf(
                 ax,
                 x,
-                y,
+                y,  # pyright: ignore[reportGeneralTypeIssues]
                 style=style,
                 column_num=i,
                 stacking_id=stacking_id,
@@ -1451,7 +1454,14 @@ def _make_plot(self, fig: Figure) -> None:
     # error: Signature of "_plot" incompatible with supertype "MPLPlot"
     @classmethod
     def _plot(  # type: ignore[override]
-        cls, ax: Axes, x, y, style=None, column_num=None, stacking_id=None, **kwds
+        cls,
+        ax: Axes,
+        x,
+        y: np.ndarray,
+        style=None,
+        column_num=None,
+        stacking_id=None,
+        **kwds,
     ):
         # column_num is used to get the target column from plotf in line and
         # area plots
@@ -1478,7 +1488,7 @@ def _ts_plot(self, ax: Axes, x, data: Series, style=None, **kwds):
             decorate_axes(ax.right_ax, freq, kwds)
         ax._plot_data.append((data, self._kind, kwds))
 
-        lines = self._plot(ax, data.index, data.values, style=style, **kwds)
+        lines = self._plot(ax, data.index, np.asarray(data.values), style=style, **kwds)
         # set date formatter, locators and rescale limits
         # error: Argument 3 to "format_dateaxis" has incompatible type "Index";
         # expected "DatetimeIndex | PeriodIndex"
@@ -1506,7 +1516,9 @@ def _initialize_stacker(cls, ax: Axes, stacking_id, n: int) -> None:
 
     @final
     @classmethod
-    def _get_stacked_values(cls, ax: Axes, stacking_id, values, label):
+    def _get_stacked_values(
+        cls, ax: Axes, stacking_id: int | None, values: np.ndarray, label
+    ) -> np.ndarray:
         if stacking_id is None:
             return values
         if not hasattr(ax, "_stacker_pos_prior"):
@@ -1526,7 +1538,7 @@ def _get_stacked_values(cls, ax: Axes, stacking_id, values, label):
 
     @final
     @classmethod
-    def _update_stacker(cls, ax: Axes, stacking_id, values) -> None:
+    def _update_stacker(cls, ax: Axes, stacking_id: int | None, values) -> None:
         if stacking_id is None:
             return
         if (values >= 0).all():
@@ -1604,7 +1616,7 @@ def _plot(  # type: ignore[override]
         cls,
         ax: Axes,
         x,
-        y,
+        y: np.ndarray,
         style=None,
         column_num=None,
         stacking_id=None,
@@ -1730,7 +1742,7 @@ def _plot(  # type: ignore[override]
         cls,
         ax: Axes,
         x,
-        y,
+        y: np.ndarray,
         w,
         start: int | npt.NDArray[np.intp] = 0,
         log: bool = False,
@@ -1749,7 +1761,8 @@ def _make_plot(self, fig: Figure) -> None:
         pos_prior = neg_prior = np.zeros(len(self.data))
         K = self.nseries
 
-        for i, (label, y) in enumerate(self._iter_data(fillna=0)):
+        data = self.data.fillna(0)
+        for i, (label, y) in enumerate(self._iter_data(data=data)):
             ax = self._get_ax(i)
             kwds = self.kwds.copy()
             if self._is_series:
@@ -1828,7 +1841,14 @@ def _post_plot_logic(self, ax: Axes, data) -> None:
 
         self._decorate_ticks(ax, self._get_index_name(), str_index, s_edge, e_edge)
 
-    def _decorate_ticks(self, ax: Axes, name, ticklabels, start_edge, end_edge) -> None:
+    def _decorate_ticks(
+        self,
+        ax: Axes,
+        name: str | None,
+        ticklabels: list[str],
+        start_edge: float,
+        end_edge: float,
+    ) -> None:
         ax.set_xlim((start_edge, end_edge))
 
         if self.xticks is not None:
@@ -1862,7 +1882,7 @@ def _plot(  # type: ignore[override]
         cls,
         ax: Axes,
         x,
-        y,
+        y: np.ndarray,
         w,
         start: int | npt.NDArray[np.intp] = 0,
         log: bool = False,
@@ -1873,7 +1893,14 @@ def _plot(  # type: ignore[override]
     def _get_custom_index_name(self):
         return self.ylabel
 
-    def _decorate_ticks(self, ax: Axes, name, ticklabels, start_edge, end_edge) -> None:
+    def _decorate_ticks(
+        self,
+        ax: Axes,
+        name: str | None,
+        ticklabels: list[str],
+        start_edge: float,
+        end_edge: float,
+    ) -> None:
         # horizontal bars
         ax.set_ylim((start_edge, end_edge))
         ax.set_yticks(self.tick_pos)
@@ -1907,7 +1934,7 @@ def _make_plot(self, fig: Figure) -> None:
         colors = self._get_colors(num_colors=len(self.data), color_kwds="colors")
         self.kwds.setdefault("colors", colors)
 
-        for i, (label, y) in enumerate(self._iter_data()):
+        for i, (label, y) in enumerate(self._iter_data(data=self.data)):
             ax = self._get_ax(i)
             if label is not None:
                 label = pprint_thing(label)

pandas/plotting/_matplotlib/groupby.py

@@ -16,12 +16,14 @@
 from pandas.plotting._matplotlib.misc import unpack_single_str_list
 
 if TYPE_CHECKING:
+    from collections.abc import Hashable
+
     from pandas._typing import IndexLabel
 
 
 def create_iter_data_given_by(
     data: DataFrame, kind: str = "hist"
-) -> dict[str, DataFrame | Series]:
+) -> dict[Hashable, DataFrame | Series]:
     """
     Create data for iteration given `by` is assigned or not, and it is only
     used in both hist and boxplot.
@@ -126,9 +128,7 @@ def reconstruct_data_with_by(
     return data
 
 
-def reformat_hist_y_given_by(
-    y: Series | np.ndarray, by: IndexLabel | None
-) -> Series | np.ndarray:
+def reformat_hist_y_given_by(y: np.ndarray, by: IndexLabel | None) -> np.ndarray:
     """Internal function to reformat y given `by` is applied or not for hist plot.
 
     If by is None, input y is 1-d with NaN removed; and if by is not None, groupby