TYP: annotate plotting._matplotlib.misc

pandas/plotting/_matplotlib/misc.py

@@ -1,18 +1,27 @@
 import random
+from typing import TYPE_CHECKING, Dict, List, Optional, Set
 
 import matplotlib.lines as mlines
 import matplotlib.patches as patches
 import numpy as np
 
+from pandas._typing import Label
+
 from pandas.core.dtypes.missing import notna
 
 from pandas.io.formats.printing import pprint_thing
 from pandas.plotting._matplotlib.style import _get_standard_colors
 from pandas.plotting._matplotlib.tools import _set_ticks_props, _subplots
 
+if TYPE_CHECKING:
+    from matplotlib.axes import Axes
+    from matplotlib.figure import Figure
+
+    from pandas import DataFrame, Series
+
 
 def scatter_matrix(
-    frame,
+    frame: "DataFrame",
     alpha=0.5,
     figsize=None,
     ax=None,
@@ -114,7 +123,14 @@ def _get_marker_compat(marker):
     return marker
 
 
-def radviz(frame, class_column, ax=None, color=None, colormap=None, **kwds):
+def radviz(
+    frame: "DataFrame",
+    class_column,
+    ax: Optional["Axes"] = None,
+    color=None,
+    colormap=None,
+    **kwds,
+) -> "Axes":
     import matplotlib.pyplot as plt
 
     def normalize(series):
@@ -130,7 +146,7 @@ def normalize(series):
     if ax is None:
         ax = plt.gca(xlim=[-1, 1], ylim=[-1, 1])
 
-    to_plot = {}
+    to_plot: Dict[Label, List[List]] = {}
     colors = _get_standard_colors(
         num_colors=len(classes), colormap=colormap, color_type="random", color=color
     )
@@ -197,8 +213,14 @@ def normalize(series):
 
 
 def andrews_curves(
-    frame, class_column, ax=None, samples=200, color=None, colormap=None, **kwds
-):
+    frame: "DataFrame",
+    class_column,
+    ax: Optional["Axes"] = None,
+    samples: int = 200,
+    color=None,
+    colormap=None,
+    **kwds,
+) -> "Axes":
     import matplotlib.pyplot as plt
 
     def function(amplitudes):
@@ -231,7 +253,7 @@ def f(t):
     classes = frame[class_column].drop_duplicates()
     df = frame.drop(class_column, axis=1)
     t = np.linspace(-np.pi, np.pi, samples)
-    used_legends = set()
+    used_legends: Set[str] = set()
 
     color_values = _get_standard_colors(
         num_colors=len(classes), colormap=colormap, color_type="random", color=color
@@ -256,7 +278,13 @@ def f(t):
     return ax
 
 
-def bootstrap_plot(series, fig=None, size=50, samples=500, **kwds):
+def bootstrap_plot(
+    series: "Series",
+    fig: Optional["Figure"] = None,
+    size: int = 50,
+    samples: int = 500,
+    **kwds,
+) -> "Figure":
 
     import matplotlib.pyplot as plt
 
@@ -306,19 +334,19 @@ def bootstrap_plot(series, fig=None, size=50, samples=500, **kwds):
 
 
 def parallel_coordinates(
-    frame,
+    frame: "DataFrame",
     class_column,
     cols=None,
-    ax=None,
+    ax: Optional["Axes"] = None,
     color=None,
     use_columns=False,
     xticks=None,
     colormap=None,
-    axvlines=True,
+    axvlines: bool = True,
     axvlines_kwds=None,
-    sort_labels=False,
+    sort_labels: bool = False,
     **kwds,
-):
+) -> "Axes":
     import matplotlib.pyplot as plt
 
     if axvlines_kwds is None:
@@ -333,7 +361,7 @@ def parallel_coordinates(
     else:
         df = frame[cols]
 
-    used_legends = set()
+    used_legends: Set[str] = set()
 
     ncols = len(df.columns)
 
@@ -385,7 +413,9 @@ def parallel_coordinates(
     return ax
 
 
-def lag_plot(series, lag=1, ax=None, **kwds):
+def lag_plot(
+    series: "Series", lag: int = 1, ax: Optional["Axes"] = None, **kwds
+) -> "Axes":
     # workaround because `c='b'` is hardcoded in matplotlib's scatter method
     import matplotlib.pyplot as plt
 
@@ -402,7 +432,9 @@ def lag_plot(series, lag=1, ax=None, **kwds):
     return ax
 
 
-def autocorrelation_plot(series, ax=None, **kwds):
+def autocorrelation_plot(
+    series: "Series", ax: Optional["Axes"] = None, **kwds
+) -> "Axes":
     import matplotlib.pyplot as plt
 
     n = len(series)

pandas/plotting/_matplotlib/style.py

@@ -11,7 +11,7 @@
 
 
 def _get_standard_colors(
-    num_colors=None, colormap=None, color_type="default", color=None
+    num_colors=None, colormap=None, color_type: str = "default", color=None
 ):
     import matplotlib.pyplot as plt