CLN: plotting code

pandas/plotting/_matplotlib/converter.py

@@ -224,22 +224,29 @@ def __call__(self, x, pos: int | None = 0) -> str:
 
 class PeriodConverter(mdates.DateConverter):
     @staticmethod
-    def convert(values, units, axis):
+    def convert(values, unit, axis: Axis):
+        # Reached via e.g. `ax.set_xlim`
+
+        # In tests as of 2025-09-24, unit is always None except for 3 tests
+        #  that directly call this with unit="";
+        #  axis is always specifically a matplotlib.axis.XAxis
+
         if not hasattr(axis, "freq"):
             raise TypeError("Axis must have `freq` set to convert to Periods")
-        return PeriodConverter.convert_from_freq(values, axis.freq)
+        freq = to_offset(axis.freq, is_period=True)
+        return PeriodConverter.convert_from_freq(values, freq)
 
     @staticmethod
-    def convert_from_freq(values, freq):
+    def convert_from_freq(values, freq: BaseOffset):
         if is_nested_list_like(values):
             values = [PeriodConverter._convert_1d(v, freq) for v in values]
         else:
             values = PeriodConverter._convert_1d(values, freq)
         return values
 
     @staticmethod
-    def _convert_1d(values, freq):
-        valid_types = (str, datetime, Period, pydt.date, pydt.time, np.datetime64)
+    def _convert_1d(values, freq: BaseOffset):
+        valid_types = (str, datetime, Period, pydt.date, np.datetime64)
         with warnings.catch_warnings():
             warnings.filterwarnings(
                 "ignore", "Period with BDay freq is deprecated", category=FutureWarning
@@ -252,30 +259,26 @@ def _convert_1d(values, freq):
                 or is_integer(values)
                 or is_float(values)
             ):
-                return get_datevalue(values, freq)
+                return _get_datevalue(values, freq)
             elif isinstance(values, PeriodIndex):
                 return values.asfreq(freq).asi8
             elif isinstance(values, Index):
-                return values.map(lambda x: get_datevalue(x, freq))
+                return values.map(lambda x: _get_datevalue(x, freq))
             elif lib.infer_dtype(values, skipna=False) == "period":
                 # https://github.com/pandas-dev/pandas/issues/24304
                 # convert ndarray[period] -> PeriodIndex
                 return PeriodIndex(values, freq=freq).asi8
-            elif isinstance(values, (list, tuple, np.ndarray, Index)):
-                return [get_datevalue(x, freq) for x in values]
+            elif isinstance(values, (list, tuple, np.ndarray)):
+                return [_get_datevalue(x, freq) for x in values]
         return values
 
 
-def get_datevalue(date, freq):
+def _get_datevalue(date, freq: BaseOffset):
     if isinstance(date, Period):
         return date.asfreq(freq).ordinal
-    elif isinstance(date, (str, datetime, pydt.date, pydt.time, np.datetime64)):
+    elif isinstance(date, (str, datetime, pydt.date, np.datetime64)):
         return Period(date, freq).ordinal
-    elif (
-        is_integer(date)
-        or is_float(date)
-        or (isinstance(date, (np.ndarray, Index)) and (date.size == 1))
-    ):
+    elif is_integer(date) or is_float(date):
         return date
     elif date is None:
         return None
@@ -285,7 +288,13 @@ def get_datevalue(date, freq):
 # Datetime Conversion
 class DatetimeConverter(mdates.DateConverter):
     @staticmethod
-    def convert(values, unit, axis):
+    def convert(values, unit, axis: Axis):
+        # Reached via e.g. `ax.set_xlim`
+
+        # In tests as of 2025-09-24, unit is always None except for 3 tests
+        #  that directly call this with unit="";
+        #  axis is always specifically a matplotlib.axis.XAxis
+
         # values might be a 1-d array, or a list-like of arrays.
         if is_nested_list_like(values):
             values = [DatetimeConverter._convert_1d(v, unit, axis) for v in values]

pandas/plotting/_matplotlib/timeseries.py

@@ -6,12 +6,9 @@
 from typing import (
     TYPE_CHECKING,
     Any,
-    cast,
 )
 import warnings
 
-import numpy as np
-
 from pandas._libs.tslibs import (
     BaseOffset,
     Period,
@@ -265,27 +262,15 @@ def _get_index_freq(index: Index) -> BaseOffset | None:
     freq = getattr(index, "freq", None)
     if freq is None:
         freq = getattr(index, "inferred_freq", None)
-        if freq == "B":
-            # error: "Index" has no attribute "dayofweek"
-            weekdays = np.unique(index.dayofweek)  # type: ignore[attr-defined]
-            if (5 in weekdays) or (6 in weekdays):
-                freq = None
-
-    freq = to_offset(freq)
+        freq = to_offset(freq)
     return freq
 
 
 def maybe_convert_index(ax: Axes, data: NDFrameT) -> NDFrameT:
     # tsplot converts automatically, but don't want to convert index
     # over and over for DataFrames
     if isinstance(data.index, (ABCDatetimeIndex, ABCPeriodIndex)):
-        freq: str | BaseOffset | None = data.index.freq
-
-        if freq is None:
-            # We only get here for DatetimeIndex
-            data.index = cast("DatetimeIndex", data.index)
-            freq = data.index.inferred_freq
-            freq = to_offset(freq)
+        freq = _get_index_freq(data.index)
 
         if freq is None:
             freq = _get_ax_freq(ax)
@@ -315,7 +300,7 @@ def maybe_convert_index(ax: Axes, data: NDFrameT) -> NDFrameT:
 # Patch methods for subplot.
 
 
-def _format_coord(freq, t, y) -> str:
+def _format_coord(freq: BaseOffset, t, y) -> str:
     time_period = Period(ordinal=int(t), freq=freq)
     return f"t = {time_period}  y = {y:8f}"
 

pandas/tests/plotting/test_datetimelike.py

@@ -165,12 +165,13 @@ def test_high_freq(self, freq):
         _check_plot_works(ser.plot, ax=ax)
 
     def test_get_datevalue(self):
-        assert conv.get_datevalue(None, "D") is None
-        assert conv.get_datevalue(1987, "Y") == 1987
+        assert conv._get_datevalue(None, "D") is None
+        assert conv._get_datevalue(1987, "Y") == 1987
         assert (
-            conv.get_datevalue(Period(1987, "Y"), "M") == Period("1987-12", "M").ordinal
+            conv._get_datevalue(Period(1987, "Y"), "M")
+            == Period("1987-12", "M").ordinal
         )
-        assert conv.get_datevalue("1/1/1987", "D") == Period("1987-1-1", "D").ordinal
+        assert conv._get_datevalue("1/1/1987", "D") == Period("1987-1-1", "D").ordinal
 
     @pytest.mark.parametrize(
         "freq, expected_string",