BUG: Handle overlapping line and bar on the same plot (#61173)

* Handle line and box on the same plot

* Handle line and box on the same plot

* Refactor PeriodConverter to separate frequency handling.

Introduce `convert_from_freq` method and streamline the conversion process by passing `freq` directly instead of using `axis.freq`. This improves modularity and ensures clearer separation of concerns for frequency handling in Period conversion.

* Refactor time series plotting logic in Matplotlib backend.

Simplified `tick_pos` calculation by reusing helper methods and added a decorator to register pandas Matplotlib converters in the `_plot` method. This improves clarity and ensures proper integration with the pandas Matplotlib ecosystem.

* Add test for bar and line plot superposition with same x values

This test ensures that bar and line plots with identical x values are correctly superposed on the same axes. It verifies that the x-tick positions remain consistent across plot types.

* Fix alignment issue in Series.plot with line and bar.

Resolved a bug that prevented a line and bar from aligning on the same plot in `Series.plot`. This addresses issue #61161 and improves plot consistency when combining these chart types.

* Refactor time series handling in matplotlib plotting.

Move `x_compat` logic and time series helper methods from `LinePlot` to `MPLPlot` for better reusability and maintainability. This simplifies the `LinePlot` class and centralizes common functionality.

* Update doc/source/whatsnew/v3.0.0.rst

* Apply suggestions from code review

* Fix bar and line plot alignment and x-axis visibility in tests

Ensure bar and line plots share consistent x-axis tick labels and verify that x-axis limits are adjusted to make all plotted elements visible in `test_bar_line_plot` test. These changes improve the robustness of visual alignment and boundary checks.

* Ensure bar_xticks length matches index in test_series.py

Add an assertion to verify the length of `bar_xticks` aligns with the length of the index. This improves the test's robustness by ensuring the data and ticks remain consistent.

Author: MartinBraquet

doc/source/whatsnew/v3.0.0.rst

@@ -769,6 +769,7 @@ Plotting
 - Bug in :meth:`DataFrame.plot.bar` with ``stacked=True`` where labels on stacked bars with zero-height segments were incorrectly positioned at the base instead of the label position of the previous segment (:issue:`59429`)
 - Bug in :meth:`DataFrame.plot.line` raising ``ValueError`` when set both color and a ``dict`` style (:issue:`59461`)
 - Bug in :meth:`DataFrame.plot` that causes a shift to the right when the frequency multiplier is greater than one. (:issue:`57587`)
+- Bug in :meth:`Series.plot` preventing a line and bar from being aligned on the same plot (:issue:`61161`)
 - Bug in :meth:`Series.plot` preventing a line and scatter plot from being aligned (:issue:`61005`)
 - Bug in :meth:`Series.plot` with ``kind="pie"`` with :class:`ArrowDtype` (:issue:`59192`)
 

pandas/plotting/_matplotlib/converter.py

@@ -225,16 +225,20 @@ def __call__(self, x, pos: int | None = 0) -> str:
 class PeriodConverter(mdates.DateConverter):
     @staticmethod
     def convert(values, units, axis):
+        if not hasattr(axis, "freq"):
+            raise TypeError("Axis must have `freq` set to convert to Periods")
+        return PeriodConverter.convert_from_freq(values, axis.freq)
+
+    @staticmethod
+    def convert_from_freq(values, freq):
         if is_nested_list_like(values):
-            values = [PeriodConverter._convert_1d(v, units, axis) for v in values]
+            values = [PeriodConverter._convert_1d(v, freq) for v in values]
         else:
-            values = PeriodConverter._convert_1d(values, units, axis)
+            values = PeriodConverter._convert_1d(values, freq)
         return values
 
     @staticmethod
-    def _convert_1d(values, units, axis):
-        if not hasattr(axis, "freq"):
-            raise TypeError("Axis must have `freq` set to convert to Periods")
+    def _convert_1d(values, freq):
         valid_types = (str, datetime, Period, pydt.date, pydt.time, np.datetime64)
         with warnings.catch_warnings():
             warnings.filterwarnings(
@@ -248,17 +252,17 @@ def _convert_1d(values, units, axis):
                 or is_integer(values)
                 or is_float(values)
             ):
-                return get_datevalue(values, axis.freq)
+                return get_datevalue(values, freq)
             elif isinstance(values, PeriodIndex):
-                return values.asfreq(axis.freq).asi8
+                return values.asfreq(freq).asi8
             elif isinstance(values, Index):
-                return values.map(lambda x: get_datevalue(x, axis.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=axis.freq).asi8
+                return PeriodIndex(values, freq=freq).asi8
             elif isinstance(values, (list, tuple, np.ndarray, Index)):
-                return [get_datevalue(x, axis.freq) for x in values]
+                return [get_datevalue(x, freq) for x in values]
         return values
 
 

pandas/plotting/_matplotlib/core.py

@@ -59,7 +59,10 @@
 
 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.converter import (
+    PeriodConverter,
+    register_pandas_matplotlib_converters,
+)
 from pandas.plotting._matplotlib.groupby import reconstruct_data_with_by
 from pandas.plotting._matplotlib.misc import unpack_single_str_list
 from pandas.plotting._matplotlib.style import get_standard_colors
@@ -1858,7 +1861,6 @@ def __init__(
         self.bar_width = width
         self._align = align
         self._position = position
-        self.tick_pos = np.arange(len(data))
 
         if is_list_like(bottom):
             bottom = np.array(bottom)
@@ -1871,6 +1873,16 @@ def __init__(
 
         MPLPlot.__init__(self, data, **kwargs)
 
+        if self._is_ts_plot():
+            self.tick_pos = np.array(
+                PeriodConverter.convert_from_freq(
+                    self._get_xticks(),
+                    data.index.freq,
+                )
+            )
+        else:
+            self.tick_pos = np.arange(len(data))
+
     @cache_readonly
     def ax_pos(self) -> np.ndarray:
         return self.tick_pos - self.tickoffset
@@ -1900,6 +1912,7 @@ def lim_offset(self):
 
     # error: Signature of "_plot" incompatible with supertype "MPLPlot"
     @classmethod
+    @register_pandas_matplotlib_converters
     def _plot(  # type: ignore[override]
         cls,
         ax: Axes,

pandas/tests/plotting/test_series.py

@@ -971,3 +971,27 @@ def test_secondary_y_subplot_axis_labels(self):
         s1.plot(ax=ax2)
         assert len(ax.xaxis.get_minor_ticks()) == 0
         assert len(ax.get_xticklabels()) > 0
+
+    def test_bar_line_plot(self):
+        """
+        Test that bar and line plots with the same x values are superposed
+        and that the x limits are set such that the plots are visible.
+        """
+        # GH61161
+        index = period_range("2023", periods=3, freq="Y")
+        years = set(index.year.astype(str))
+        s = Series([1, 2, 3], index=index)
+        ax = plt.subplot()
+        s.plot(kind="bar", ax=ax)
+        bar_xticks = [
+            label for label in ax.get_xticklabels() if label.get_text() in years
+        ]
+        s.plot(kind="line", ax=ax, color="r")
+        line_xticks = [
+            label for label in ax.get_xticklabels() if label.get_text() in years
+        ]
+        assert len(bar_xticks) == len(index)
+        assert bar_xticks == line_xticks
+        x_limits = ax.get_xlim()
+        assert x_limits[0] <= bar_xticks[0].get_position()[0]
+        assert x_limits[1] >= bar_xticks[-1].get_position()[0]