STYLE: Fix redefined-outer-name linting issue

pandas/plotting/_matplotlib/converter.py

@@ -17,16 +17,14 @@
 )
 
 from dateutil.relativedelta import relativedelta
-from matplotlib import (
-    dates,
-    units,
-)
+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
 
 from pandas._libs import lib
@@ -126,25 +124,25 @@ def register() -> None:
     pairs = get_pairs()
     for type_, cls in pairs:
         # Cache previous converter if present
-        if type_ in units.registry and not isinstance(units.registry[type_], cls):
-            previous = units.registry[type_]
+        if type_ in munits.registry and not isinstance(munits.registry[type_], cls):
+            previous = munits.registry[type_]
             _mpl_units[type_] = previous
         # Replace with pandas converter
-        units.registry[type_] = cls()
+        munits.registry[type_] = cls()
 
 
 def deregister() -> None:
     # Renamed in pandas.plotting.__init__
     for type_, cls in get_pairs():
         # We use type to catch our classes directly, no inheritance
-        if type(units.registry.get(type_)) is cls:
-            units.registry.pop(type_)
+        if type(munits.registry.get(type_)) is cls:
+            munits.registry.pop(type_)
 
     # restore the old keys
     for unit, formatter in _mpl_units.items():
         if type(formatter) not in {DatetimeConverter, PeriodConverter, TimeConverter}:
             # make it idempotent by excluding ours.
-            units.registry[unit] = formatter
+            munits.registry[unit] = formatter
 
 
 def _to_ordinalf(tm: pydt.time) -> float:
@@ -161,7 +159,7 @@ def time2num(d):
     return d
 
 
-class TimeConverter(units.ConversionInterface):
+class TimeConverter(munits.ConversionInterface):
     @staticmethod
     def convert(value, unit, axis):
         valid_types = (str, pydt.time)
@@ -174,13 +172,13 @@ def convert(value, unit, axis):
         return value
 
     @staticmethod
-    def axisinfo(unit, axis) -> units.AxisInfo | None:
+    def axisinfo(unit, axis) -> munits.AxisInfo | None:
         if unit != "time":
             return None
 
         majloc = AutoLocator()
         majfmt = TimeFormatter(majloc)
-        return units.AxisInfo(majloc=majloc, majfmt=majfmt, label="time")
+        return munits.AxisInfo(majloc=majloc, majfmt=majfmt, label="time")
 
     @staticmethod
     def default_units(x, axis) -> str:
@@ -231,7 +229,7 @@ def __call__(self, x, pos: int = 0) -> str:
 # Period Conversion
 
 
-class PeriodConverter(dates.DateConverter):
+class PeriodConverter(mdates.DateConverter):
     @staticmethod
     def convert(values, units, axis):
         if is_nested_list_like(values):
@@ -277,7 +275,7 @@ def get_datevalue(date, freq):
 
 
 # Datetime Conversion
-class DatetimeConverter(dates.DateConverter):
+class DatetimeConverter(mdates.DateConverter):
     @staticmethod
     def convert(values, unit, axis):
         # values might be a 1-d array, or a list-like of arrays.
@@ -291,12 +289,12 @@ def convert(values, unit, axis):
     def _convert_1d(values, unit, axis):
         def try_parse(values):
             try:
-                return dates.date2num(tools.to_datetime(values))
+                return mdates.date2num(tools.to_datetime(values))
             except Exception:
                 return values
 
         if isinstance(values, (datetime, pydt.date, np.datetime64, pydt.time)):
-            return dates.date2num(values)
+            return mdates.date2num(values)
         elif is_integer(values) or is_float(values):
             return values
         elif isinstance(values, str):
@@ -319,12 +317,12 @@ def try_parse(values):
             except Exception:
                 pass
 
-            values = dates.date2num(values)
+            values = mdates.date2num(values)
 
         return values
 
     @staticmethod
-    def axisinfo(unit: tzinfo | None, axis) -> units.AxisInfo:
+    def axisinfo(unit: tzinfo | None, axis) -> munits.AxisInfo:
         """
         Return the :class:`~matplotlib.units.AxisInfo` for *unit*.
 
@@ -338,17 +336,17 @@ def axisinfo(unit: tzinfo | None, axis) -> units.AxisInfo:
         datemin = pydt.date(2000, 1, 1)
         datemax = pydt.date(2010, 1, 1)
 
-        return units.AxisInfo(
+        return munits.AxisInfo(
             majloc=majloc, majfmt=majfmt, label="", default_limits=(datemin, datemax)
         )
 
 
-class PandasAutoDateFormatter(dates.AutoDateFormatter):
+class PandasAutoDateFormatter(mdates.AutoDateFormatter):
     def __init__(self, locator, tz=None, defaultfmt: str = "%Y-%m-%d") -> None:
-        dates.AutoDateFormatter.__init__(self, locator, tz, defaultfmt)
+        mdates.AutoDateFormatter.__init__(self, locator, tz, defaultfmt)
 
 
-class PandasAutoDateLocator(dates.AutoDateLocator):
+class PandasAutoDateLocator(mdates.AutoDateLocator):
     def get_locator(self, dmin, dmax):
         """Pick the best locator based on a distance."""
         delta = relativedelta(dmax, dmin)
@@ -366,26 +364,26 @@ def get_locator(self, dmin, dmax):
             locator.axis.set_data_interval(*self.axis.get_data_interval())
             return locator
 
-        return dates.AutoDateLocator.get_locator(self, dmin, dmax)
+        return mdates.AutoDateLocator.get_locator(self, dmin, dmax)
 
     def _get_unit(self):
         return MilliSecondLocator.get_unit_generic(self._freq)
 
 
-class MilliSecondLocator(dates.DateLocator):
+class MilliSecondLocator(mdates.DateLocator):
 
     UNIT = 1.0 / (24 * 3600 * 1000)
 
     def __init__(self, tz) -> None:
-        dates.DateLocator.__init__(self, tz)
+        mdates.DateLocator.__init__(self, tz)
         self._interval = 1.0
 
     def _get_unit(self):
         return self.get_unit_generic(-1)
 
     @staticmethod
     def get_unit_generic(freq):
-        unit = dates.RRuleLocator.get_unit_generic(freq)
+        unit = mdates.RRuleLocator.get_unit_generic(freq)
         if unit < 0:
             return MilliSecondLocator.UNIT
         return unit
@@ -398,7 +396,7 @@ def __call__(self):
             return []
 
         # We need to cap at the endpoints of valid datetime
-        nmax, nmin = dates.date2num((dmax, dmin))
+        nmax, nmin = mdates.date2num((dmax, dmin))
 
         num = (nmax - nmin) * 86400 * 1000
         max_millis_ticks = 6
@@ -427,12 +425,12 @@ def __call__(self):
 
         try:
             if len(all_dates) > 0:
-                locs = self.raise_if_exceeds(dates.date2num(all_dates))
+                locs = self.raise_if_exceeds(mdates.date2num(all_dates))
                 return locs
         except Exception:  # pragma: no cover
             pass
 
-        lims = dates.date2num([dmin, dmax])
+        lims = mdates.date2num([dmin, dmax])
         return lims
 
     def _get_interval(self):
@@ -445,8 +443,8 @@ def autoscale(self):
         # We need to cap at the endpoints of valid datetime
         dmin, dmax = self.datalim_to_dt()
 
-        vmin = dates.date2num(dmin)
-        vmax = dates.date2num(dmax)
+        vmin = mdates.date2num(dmin)
+        vmax = mdates.date2num(dmax)
 
         return self.nonsingular(vmin, vmax)
 

pandas/plotting/_matplotlib/core.py

@@ -55,6 +55,7 @@
 from pandas.core.frame import DataFrame
 
 from pandas.io.formats.printing import pprint_thing
+from pandas.plotting._matplotlib import tools
 from pandas.plotting._matplotlib.converter import register_pandas_matplotlib_converters
 from pandas.plotting._matplotlib.groupby import reconstruct_data_with_by
 from pandas.plotting._matplotlib.misc import unpack_single_str_list
@@ -73,7 +74,6 @@
     get_all_lines,
     get_xlim,
     handle_shared_axes,
-    table,
 )
 
 if TYPE_CHECKING:
@@ -644,7 +644,7 @@ def _add_table(self) -> None:
         else:
             data = self.table
         ax = self._get_ax(0)
-        table(ax, data)
+        tools.table(ax, data)
 
     def _post_plot_logic_common(self, ax, data):
         """Common post process for each axes"""

pandas/plotting/_matplotlib/tools.py

@@ -75,10 +75,9 @@ def table(
 
     cellText = data.values
 
-    table = matplotlib.table.table(
+    return matplotlib.table.table(
         ax, cellText=cellText, rowLabels=rowLabels, colLabels=colLabels, **kwargs
     )
-    return table
 
 
 def _get_layout(

pandas/tests/plotting/test_converter.py

@@ -215,7 +215,7 @@ def test_conversion_float(self, dtc):
         rtol = 0.5 * 10**-9
 
         rs = dtc.convert(Timestamp("2012-1-1 01:02:03", tz="UTC"), None, None)
-        xp = converter.dates.date2num(Timestamp("2012-1-1 01:02:03", tz="UTC"))
+        xp = converter.mdates.date2num(Timestamp("2012-1-1 01:02:03", tz="UTC"))
         tm.assert_almost_equal(rs, xp, rtol=rtol)
 
         rs = dtc.convert(
@@ -230,18 +230,18 @@ def test_conversion_outofbounds_datetime(self, dtc):
         # 2579
         values = [date(1677, 1, 1), date(1677, 1, 2)]
         rs = dtc.convert(values, None, None)
-        xp = converter.dates.date2num(values)
+        xp = converter.mdates.date2num(values)
         tm.assert_numpy_array_equal(rs, xp)
         rs = dtc.convert(values[0], None, None)
-        xp = converter.dates.date2num(values[0])
+        xp = converter.mdates.date2num(values[0])
         assert rs == xp
 
         values = [datetime(1677, 1, 1, 12), datetime(1677, 1, 2, 12)]
         rs = dtc.convert(values, None, None)
-        xp = converter.dates.date2num(values)
+        xp = converter.mdates.date2num(values)
         tm.assert_numpy_array_equal(rs, xp)
         rs = dtc.convert(values[0], None, None)
-        xp = converter.dates.date2num(values[0])
+        xp = converter.mdates.date2num(values[0])
         assert rs == xp
 
     @pytest.mark.parametrize(
@@ -264,7 +264,7 @@ def test_dateindex_conversion(self, freq, dtc):
         rtol = 10**-9
         dateindex = tm.makeDateIndex(k=10, freq=freq)
         rs = dtc.convert(dateindex, None, None)
-        xp = converter.dates.date2num(dateindex._mpl_repr())
+        xp = converter.mdates.date2num(dateindex._mpl_repr())
         tm.assert_almost_equal(rs, xp, rtol=rtol)
 
     @pytest.mark.parametrize("offset", [Second(), Milli(), Micro(50)])