typ: resolve typing for pandas-stubs>2.3.3

Author: has2k1

plotnine/_utils/__init__.py

@@ -35,7 +35,6 @@
         FloatArray,
         FloatArrayLike,
         HorizontalJustification,
-        IntArray,
         Side,
         VerticalJustification,
     )
@@ -309,7 +308,7 @@ def ninteraction(df: pd.DataFrame, drop: bool = False) -> list[int]:
     def len_unique(x):
         return len(np.unique(x))
 
-    ndistinct: IntArray = ids.apply(len_unique, axis=0).to_numpy()
+    ndistinct = ids.apply(len_unique, axis=0).to_numpy()
 
     combs = np.array(np.hstack([1, np.cumprod(ndistinct[:-1])]))
     mat = np.array(ids)
@@ -743,7 +742,7 @@ def ungroup(data: DataLike) -> DataLike:
     """Return an ungrouped DataFrame, or pass the original data back."""
 
     if isinstance(data, DataFrameGroupBy):
-        return data.obj
+        return data.obj  # pyright: ignore[reportReturnType]
 
     return data
 

plotnine/facets/facet_grid.py

@@ -189,7 +189,7 @@ def compute_layout(self, data: list[pd.DataFrame]) -> pd.DataFrame:
 
         n = len(base)
         panel = ninteraction(base, drop=True)
-        panel = pd.Categorical(panel, categories=range(1, n + 1))
+        panel = pd.Categorical(panel, categories=range(1, n + 1))  # pyright: ignore[reportArgumentType]
 
         if self.rows:
             rows = ninteraction(base[self.rows], drop=True)

plotnine/facets/facet_wrap.py

@@ -115,7 +115,7 @@ def compute_layout(
 
         layout = pd.DataFrame(
             {
-                "PANEL": pd.Categorical(range(1, n + 1)),
+                "PANEL": pd.Categorical(range(1, n + 1)),  # pyright: ignore[reportArgumentType]
                 "ROW": row.astype(int),
                 "COL": col.astype(int),
             }

plotnine/geoms/geom_map.py

@@ -126,18 +126,18 @@ def draw_panel(
         params = self.params
         data.loc[data["color"].isna(), "color"] = "none"
         data.loc[data["fill"].isna(), "fill"] = "none"
-        data["fill"] = to_rgba(data["fill"], data["alpha"])
 
         geom_type = data.geometry.iloc[0].geom_type
         if geom_type in ("Polygon", "MultiPolygon"):
             from matplotlib.collections import PatchCollection
 
             linewidth = data["size"] * SIZE_FACTOR
+            fill = to_rgba(data["fill"], data["alpha"])
             patches = [PolygonPatch(g) for g in data["geometry"]]
             coll = PatchCollection(
                 patches,
                 edgecolor=data["color"],
-                facecolor=data["fill"],
+                facecolor=fill,
                 linestyle=data["linetype"],
                 linewidth=linewidth,
                 zorder=params["zorder"],
@@ -152,7 +152,6 @@ def draw_panel(
             data["y"] = arr[:, 1]
             for _, gdata in data.groupby("group"):
                 gdata.reset_index(inplace=True, drop=True)
-                gdata.is_copy = None
                 geom_point.draw_group(gdata, panel_params, coord, ax, params)
         elif geom_type == "MultiPoint":
             # Where n is the length of the dataframe (no. of multipoints),
@@ -173,7 +172,7 @@ def draw_panel(
             from matplotlib.collections import LineCollection
 
             linewidth = data["size"] * SIZE_FACTOR
-            data["color"] = to_rgba(data["color"], data["alpha"])
+            color = to_rgba(data["color"], data["alpha"])
             segments = []
             for g in data["geometry"]:
                 if g.geom_type == "LineString":
@@ -183,7 +182,7 @@ def draw_panel(
 
             coll = LineCollection(
                 segments,
-                edgecolor=data["color"],
+                edgecolor=color,
                 linewidth=linewidth,
                 linestyle=data["linetype"],
                 zorder=params["zorder"],

plotnine/geoms/geom_path.py

@@ -302,7 +302,7 @@ def draw(
         last = self.ends in ("last", "both")
 
         data = data.sort_values("group", kind="mergesort")
-        data["color"] = to_rgba(data["color"], data["alpha"])
+        data["color"] = to_rgba(data["color"], data["alpha"])  # pyright: ignore[reportCallIssue,reportArgumentType]
 
         if self.type == "open":
             data["facecolor"] = "none"

plotnine/geoms/geom_text.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
-import typing
 from contextlib import suppress
+from typing import TYPE_CHECKING, cast
 from warnings import warn
 
 import numpy as np
@@ -12,7 +12,7 @@
 from ..positions import position_nudge
 from .geom import geom
 
-if typing.TYPE_CHECKING:
+if TYPE_CHECKING:
     from typing import Any, Sequence
 
     import pandas as pd
@@ -244,7 +244,7 @@ def draw_group(
             axis=1,
             inplace=True,
         )
-        plot_data["color"] = color
+        plot_data["color"] = color  # pyright: ignore[reportCallIssue,reportArgumentType]
         plot_data["zorder"] = zorder
         plot_data["rasterized"] = params["raster"]
         plot_data["clip_on"] = True
@@ -255,7 +255,7 @@ def draw_group(
             fill = to_rgba(data.pop("fill"), data["alpha"])
             if isinstance(fill, tuple):
                 fill = [list(fill)] * len(data["x"])
-            plot_data["facecolor"] = fill
+            plot_data["facecolor"] = fill  # pyright: ignore[reportCallIssue,reportArgumentType]
 
             tokens = [params["boxstyle"], f"pad={params['label_padding']}"]
             if params["boxstyle"] in {"round", "round4"}:
@@ -272,7 +272,7 @@ def draw_group(
 
         # For labels add a bbox
         for i in range(len(data)):
-            kw: dict[str, Any] = plot_data.iloc[i].to_dict()
+            kw = cast("dict[str, Any]", plot_data.iloc[i].to_dict())
             if draw_label:
                 kw["bbox"] = bbox
                 kw["bbox"]["edgecolor"] = params["boxcolor"] or kw["color"]

plotnine/stats/smoothers.py

@@ -13,6 +13,8 @@
 if TYPE_CHECKING:
     import statsmodels.api as sm
 
+    from plotnine.typing import FloatArray
+
 
 def predictdf(data, xseq, params) -> pd.DataFrame:
     """
@@ -454,12 +456,14 @@ def gpr(data, xseq, params):
     if params["se"]:
         y, stderr = regressor.predict(Xseq, return_std=True)
         data["y"] = y
-        data["se"] = stderr
+        data["se"] = cast("FloatArray", stderr)
         data["ymin"], data["ymax"] = tdist_ci(
             y, n - 1, stderr, params["level"]
         )
     else:
-        data["y"] = regressor.predict(Xseq, return_std=True)
+        data["y"] = cast(
+            "FloatArray", regressor.predict(Xseq, return_std=False)
+        )
 
     return data
 

plotnine/stats/stat_qq.py

@@ -11,9 +11,9 @@
 from .stat import stat
 
 if TYPE_CHECKING:
-    from typing import Any, Sequence
+    from typing import Any
 
-    from plotnine.typing import FloatArray
+    from plotnine.typing import FloatArray, FloatArrayLike
 
 
 # Note: distribution should be a name from scipy.stat.distribution
@@ -93,7 +93,7 @@ def theoretical_qq(
     distribution: str,
     alpha: float,
     beta: float,
-    quantiles: Sequence[float] | None,
+    quantiles: FloatArrayLike | None,
     distribution_params: dict[str, Any],
 ) -> FloatArray:
     """

plotnine/stats/stat_summary.py

@@ -1,3 +1,5 @@
+from typing import cast
+
 import numpy as np
 import pandas as pd
 
@@ -314,8 +316,8 @@ def compute_panel(self, data, scales):
         summaries = []
         for (group, x), df in data.groupby(["group", "x"]):
             summary = func(df)
-            summary["x"] = x
-            summary["group"] = group
+            summary["x"] = x  # pyright: ignore[reportCallIssue,reportArgumentType]
+            summary["group"] = cast("int", group)
             summary["n"] = len(df)
             unique = uniquecols(df)
             if "y" in unique: