REF/CLN: Standardized matplotlib imports

pandas/plotting/_core.py

@@ -1598,7 +1598,7 @@ def area(
 
         See Also
         --------
-        DataFrame.plot : Make plots of DataFrame using matplotlib / pylab.
+        DataFrame.plot : Make plots of DataFrame using matplotlib.
 
         Examples
         --------

pandas/plotting/_matplotlib/__init__.py

@@ -69,7 +69,7 @@ def plot(data, kind, **kwargs):
             kwargs["ax"] = getattr(ax, "left_ax", ax)
     plot_obj = PLOT_CLASSES[kind](data, **kwargs)
     plot_obj.generate()
-    plot_obj.draw()
+    plt.draw_if_interactive()
     return plot_obj.result
 
 

pandas/plotting/_matplotlib/boxplot.py

@@ -7,7 +7,7 @@
 )
 import warnings
 
-from matplotlib.artist import setp
+import matplotlib as mpl
 import numpy as np
 
 from pandas._libs import lib
@@ -274,13 +274,13 @@ def maybe_color_bp(bp, color_tup, **kwds) -> None:
     # GH#30346, when users specifying those arguments explicitly, our defaults
     # for these four kwargs should be overridden; if not, use Pandas settings
     if not kwds.get("boxprops"):
-        setp(bp["boxes"], color=color_tup[0], alpha=1)
+        mpl.artist.setp(bp["boxes"], color=color_tup[0], alpha=1)
     if not kwds.get("whiskerprops"):
-        setp(bp["whiskers"], color=color_tup[1], alpha=1)
+        mpl.artist.setp(bp["whiskers"], color=color_tup[1], alpha=1)
     if not kwds.get("medianprops"):
-        setp(bp["medians"], color=color_tup[2], alpha=1)
+        mpl.artist.setp(bp["medians"], color=color_tup[2], alpha=1)
     if not kwds.get("capprops"):
-        setp(bp["caps"], color=color_tup[3], alpha=1)
+        mpl.artist.setp(bp["caps"], color=color_tup[3], alpha=1)
 
 
 def _grouped_plot_by_column(
@@ -455,7 +455,7 @@ def plot_group(keys, values, ax: Axes, **kwds):
 
         if ax is None:
             rc = {"figure.figsize": figsize} if figsize is not None else {}
-            with plt.rc_context(rc):
+            with mpl.rc_context(rc):
                 ax = plt.gca()
         data = data._get_numeric_data()
         naxes = len(data.columns)

pandas/plotting/_matplotlib/converter.py

@@ -14,13 +14,8 @@
 )
 import warnings
 
+import matplotlib as mpl
 import matplotlib.dates as mdates
-from matplotlib.ticker import (
-    AutoLocator,
-    Formatter,
-    Locator,
-)
-from matplotlib.transforms import nonsingular
 import matplotlib.units as munits
 import numpy as np
 
@@ -174,7 +169,7 @@ def axisinfo(unit, axis) -> munits.AxisInfo | None:
         if unit != "time":
             return None
 
-        majloc = AutoLocator()
+        majloc = mpl.ticker.AutoLocator()  # pyright: ignore[reportAttributeAccessIssue]
         majfmt = TimeFormatter(majloc)
         return munits.AxisInfo(majloc=majloc, majfmt=majfmt, label="time")
 
@@ -184,7 +179,7 @@ def default_units(x, axis) -> str:
 
 
 # time formatter
-class TimeFormatter(Formatter):
+class TimeFormatter(mpl.ticker.Formatter):  # pyright: ignore[reportAttributeAccessIssue]
     def __init__(self, locs) -> None:
         self.locs = locs
 
@@ -917,7 +912,7 @@ def get_finder(freq: BaseOffset):
         raise NotImplementedError(f"Unsupported frequency: {dtype_code}")
 
 
-class TimeSeries_DateLocator(Locator):
+class TimeSeries_DateLocator(mpl.ticker.Locator):  # pyright: ignore[reportAttributeAccessIssue]
     """
     Locates the ticks along an axis controlled by a :class:`Series`.
 
@@ -998,15 +993,15 @@ def autoscale(self):
         if vmin == vmax:
             vmin -= 1
             vmax += 1
-        return nonsingular(vmin, vmax)
+        return mpl.transforms.nonsingular(vmin, vmax)
 
 
 # -------------------------------------------------------------------------
 # --- Formatter ---
 # -------------------------------------------------------------------------
 
 
-class TimeSeries_DateFormatter(Formatter):
+class TimeSeries_DateFormatter(mpl.ticker.Formatter):  # pyright: ignore[reportAttributeAccessIssue]
     """
     Formats the ticks along an axis controlled by a :class:`PeriodIndex`.
 
@@ -1082,7 +1077,7 @@ def __call__(self, x, pos: int | None = 0) -> str:
             return period.strftime(fmt)
 
 
-class TimeSeries_TimedeltaFormatter(Formatter):
+class TimeSeries_TimedeltaFormatter(mpl.ticker.Formatter):  # pyright: ignore[reportAttributeAccessIssue]
     """
     Formats the ticks along an axis controlled by a :class:`TimedeltaIndex`.
     """

pandas/plotting/_matplotlib/core.py

@@ -107,9 +107,7 @@ def _color_in_style(style: str) -> bool:
     """
     Check if there is a color letter in the style string.
     """
-    from matplotlib.colors import BASE_COLORS
-
-    return not set(BASE_COLORS).isdisjoint(style)
+    return not set(mpl.colors.BASE_COLORS).isdisjoint(style)
 
 
 class MPLPlot(ABC):
@@ -176,8 +174,6 @@ def __init__(
         style=None,
         **kwds,
     ) -> None:
-        import matplotlib.pyplot as plt
-
         # if users assign an empty list or tuple, raise `ValueError`
         # similar to current `df.box` and `df.hist` APIs.
         if by in ([], ()):
@@ -238,7 +234,7 @@ def __init__(
             self.rot = self._default_rot
 
         if grid is None:
-            grid = False if secondary_y else plt.rcParams["axes.grid"]
+            grid = False if secondary_y else mpl.rcParams["axes.grid"]
 
         self.grid = grid
         self.legend = legend
@@ -497,10 +493,6 @@ def _get_nseries(self, data: Series | DataFrame) -> int:
     def nseries(self) -> int:
         return self._get_nseries(self.data)
 
-    @final
-    def draw(self) -> None:
-        self.plt.draw_if_interactive()
-
     @final
     def generate(self) -> None:
         self._compute_plot_data()
@@ -570,6 +562,8 @@ def axes(self) -> Sequence[Axes]:
     @final
     @cache_readonly
     def _axes_and_fig(self) -> tuple[Sequence[Axes], Figure]:
+        import matplotlib.pyplot as plt
+
         if self.subplots:
             naxes = (
                 self.nseries if isinstance(self.subplots, bool) else len(self.subplots)
@@ -584,7 +578,7 @@ def _axes_and_fig(self) -> tuple[Sequence[Axes], Figure]:
                 layout_type=self._layout_type,
             )
         elif self.ax is None:
-            fig = self.plt.figure(figsize=self.figsize)
+            fig = plt.figure(figsize=self.figsize)
             axes = fig.add_subplot(111)
         else:
             fig = self.ax.get_figure()
@@ -918,13 +912,6 @@ def _get_ax_legend(ax: Axes):
             ax = other_ax
         return ax, leg
 
-    @final
-    @cache_readonly
-    def plt(self):
-        import matplotlib.pyplot as plt
-
-        return plt
-
     _need_to_set_index = False
 
     @final
@@ -1219,9 +1206,9 @@ def _get_errorbars(
     @final
     def _get_subplots(self, fig: Figure) -> list[Axes]:
         if Version(mpl.__version__) < Version("3.8"):
-            from matplotlib.axes import Subplot as Klass
+            Klass = mpl.axes.Subplot
         else:
-            from matplotlib.axes import Axes as Klass
+            Klass = mpl.axes.Axes
 
         return [
             ax
@@ -1386,7 +1373,7 @@ def _get_c_values(self, color, color_by_categorical: bool, c_is_column: bool):
         if c is not None and color is not None:
             raise TypeError("Specify exactly one of `c` and `color`")
         if c is None and color is None:
-            c_values = self.plt.rcParams["patch.facecolor"]
+            c_values = mpl.rcParams["patch.facecolor"]
         elif color is not None:
             c_values = color
         elif color_by_categorical:
@@ -1411,12 +1398,10 @@ def _get_norm_and_cmap(self, c_values, color_by_categorical: bool):
             cmap = None
 
         if color_by_categorical and cmap is not None:
-            from matplotlib import colors
-
             n_cats = len(self.data[c].cat.categories)
-            cmap = colors.ListedColormap([cmap(i) for i in range(cmap.N)])
+            cmap = mpl.colors.ListedColormap([cmap(i) for i in range(cmap.N)])
             bounds = np.linspace(0, n_cats, n_cats + 1)
-            norm = colors.BoundaryNorm(bounds, cmap.N)
+            norm = mpl.colors.BoundaryNorm(bounds, cmap.N)
             # TODO: warn that we are ignoring self.norm if user specified it?
             #  Doesn't happen in any tests 2023-11-09
         else:
@@ -1676,8 +1661,6 @@ def _update_stacker(cls, ax: Axes, stacking_id: int | None, values) -> None:
             ax._stacker_neg_prior[stacking_id] += values  # type: ignore[attr-defined]
 
     def _post_plot_logic(self, ax: Axes, data) -> None:
-        from matplotlib.ticker import FixedLocator
-
         def get_label(i):
             if is_float(i) and i.is_integer():
                 i = int(i)
@@ -1691,7 +1674,7 @@ def get_label(i):
             xticklabels = [get_label(x) for x in xticks]
             # error: Argument 1 to "FixedLocator" has incompatible type "ndarray[Any,
             # Any]"; expected "Sequence[float]"
-            ax.xaxis.set_major_locator(FixedLocator(xticks))  # type: ignore[arg-type]
+            ax.xaxis.set_major_locator(mpl.ticker.FixedLocator(xticks))  # type: ignore[arg-type]
             ax.set_xticklabels(xticklabels)
 
         # If the index is an irregular time series, then by default

pandas/plotting/_matplotlib/misc.py

@@ -3,8 +3,7 @@
 import random
 from typing import TYPE_CHECKING
 
-from matplotlib import patches
-import matplotlib.lines as mlines
+import matplotlib as mpl
 import numpy as np
 
 from pandas.core.dtypes.missing import notna
@@ -129,7 +128,7 @@ def scatter_matrix(
 
 
 def _get_marker_compat(marker):
-    if marker not in mlines.lineMarkers:
+    if marker not in mpl.lines.lineMarkers:
         return "o"
     return marker
 
@@ -190,10 +189,10 @@ def normalize(series):
         )
     ax.legend()
 
-    ax.add_patch(patches.Circle((0.0, 0.0), radius=1.0, facecolor="none"))
+    ax.add_patch(mpl.patches.Circle((0.0, 0.0), radius=1.0, facecolor="none"))
 
     for xy, name in zip(s, df.columns):
-        ax.add_patch(patches.Circle(xy, radius=0.025, facecolor="gray"))
+        ax.add_patch(mpl.patches.Circle(xy, radius=0.025, facecolor="gray"))
 
         if xy[0] < 0.0 and xy[1] < 0.0:
             ax.text(

pandas/plotting/_matplotlib/style.py

@@ -260,9 +260,7 @@ def _get_colors_from_color_type(color_type: str, num_colors: int) -> list[Color]
 
 def _get_default_colors(num_colors: int) -> list[Color]:
     """Get `num_colors` of default colors from matplotlib rc params."""
-    import matplotlib.pyplot as plt
-
-    colors = [c["color"] for c in plt.rcParams["axes.prop_cycle"]]
+    colors = [c["color"] for c in mpl.rcParams["axes.prop_cycle"]]
     return colors[0:num_colors]
 
 

pandas/plotting/_matplotlib/timeseries.py

@@ -333,7 +333,7 @@ def format_dateaxis(
     default, changing the limits of the x axis will intelligently change
     the positions of the ticks.
     """
-    from matplotlib import pylab
+    import matplotlib.pyplot as plt
 
     # handle index specific formatting
     # Note: DatetimeIndex does not use this
@@ -365,4 +365,4 @@ def format_dateaxis(
     else:
         raise TypeError("index type not supported")
 
-    pylab.draw_if_interactive()
+    plt.draw_if_interactive()

pandas/plotting/_matplotlib/tools.py

@@ -5,8 +5,7 @@
 from typing import TYPE_CHECKING
 import warnings
 
-from matplotlib import ticker
-import matplotlib.table
+import matplotlib as mpl
 import numpy as np
 
 from pandas.util._exceptions import find_stack_level
@@ -77,7 +76,7 @@ def table(
 
     # error: Argument "cellText" to "table" has incompatible type "ndarray[Any,
     # Any]"; expected "Sequence[Sequence[str]] | None"
-    return matplotlib.table.table(
+    return mpl.table.table(
         ax,
         cellText=cellText,  # type: ignore[arg-type]
         rowLabels=rowLabels,
@@ -327,10 +326,10 @@ def _remove_labels_from_axis(axis: Axis) -> None:
 
     # set_visible will not be effective if
     # minor axis has NullLocator and NullFormatter (default)
-    if isinstance(axis.get_minor_locator(), ticker.NullLocator):
-        axis.set_minor_locator(ticker.AutoLocator())
-    if isinstance(axis.get_minor_formatter(), ticker.NullFormatter):
-        axis.set_minor_formatter(ticker.FormatStrFormatter(""))
+    if isinstance(axis.get_minor_locator(), mpl.ticker.NullLocator):
+        axis.set_minor_locator(mpl.ticker.AutoLocator())
+    if isinstance(axis.get_minor_formatter(), mpl.ticker.NullFormatter):
+        axis.set_minor_formatter(mpl.ticker.FormatStrFormatter(""))
     for t in axis.get_minorticklabels():
         t.set_visible(False)
 
@@ -455,17 +454,15 @@ def set_ticks_props(
     ylabelsize: int | None = None,
     yrot=None,
 ):
-    import matplotlib.pyplot as plt
-
     for ax in flatten_axes(axes):
         if xlabelsize is not None:
-            plt.setp(ax.get_xticklabels(), fontsize=xlabelsize)
+            mpl.artist.setp(ax.get_xticklabels(), fontsize=xlabelsize)
         if xrot is not None:
-            plt.setp(ax.get_xticklabels(), rotation=xrot)
+            mpl.artist.setp(ax.get_xticklabels(), rotation=xrot)
         if ylabelsize is not None:
-            plt.setp(ax.get_yticklabels(), fontsize=ylabelsize)
+            mpl.artist.setp(ax.get_yticklabels(), fontsize=ylabelsize)
         if yrot is not None:
-            plt.setp(ax.get_yticklabels(), rotation=yrot)
+            mpl.artist.setp(ax.get_yticklabels(), rotation=yrot)
     return axes
 
 

pandas/tests/io/formats/style/test_matplotlib.py

@@ -7,11 +7,9 @@
     Series,
 )
 
-pytest.importorskip("matplotlib")
+mpl = pytest.importorskip("matplotlib")
 pytest.importorskip("jinja2")
 
-import matplotlib as mpl
-
 from pandas.io.formats.style import Styler
 
 pytestmark = pytest.mark.usefixtures("mpl_cleanup")