BUG: Handle overlapping line and scatter on the same plot

doc/source/whatsnew/v3.0.0.rst

@@ -762,6 +762,7 @@ 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 scatter plot from being aligned (:issue:`61005`)
 - Bug in :meth:`Series.plot` with ``kind="pie"`` with :class:`ArrowDtype` (:issue:`59192`)
 
 Groupby/resample/rolling

pandas/plotting/_matplotlib/core.py

@@ -54,6 +54,7 @@
 )
 from pandas.core.dtypes.missing import isna
 
+from pandas import Series
 import pandas.core.common as com
 from pandas.util.version import Version
 
@@ -64,10 +65,9 @@
 from pandas.plotting._matplotlib.misc import unpack_single_str_list
 from pandas.plotting._matplotlib.style import get_standard_colors
 from pandas.plotting._matplotlib.timeseries import (
- decorate_axes,
  format_dateaxis,
  maybe_convert_index,
- maybe_resample,
+ prepare_ts_data,
  use_dynamic_x,
 )
 from pandas.plotting._matplotlib.tools import (
@@ -95,7 +95,6 @@
  from pandas import (
  DataFrame,
  Index,
- Series,
  )
 
 
@@ -288,6 +287,21 @@ def __init__(
 
  self.data = self._ensure_frame(self.data)
 
+ from pandas.plotting import plot_params
+
+ self.x_compat = plot_params["x_compat"]
+ if "x_compat" in self.kwds:
+ self.x_compat = bool(self.kwds.pop("x_compat"))
+
+ @final
+ def _is_ts_plot(self) -> bool:
+ # this is slightly deceptive
+ return not self.x_compat and self.use_index and self._use_dynamic_x()
+
+ @final
+ def _use_dynamic_x(self) -> bool:
+ return use_dynamic_x(self._get_ax(0), self.data.index)
+
  @final
  @staticmethod
  def _validate_sharex(sharex: bool | None, ax, by) -> bool:
@@ -1324,10 +1338,18 @@ def __init__(
  c = self.data.columns[c]
  self.c = c
 
+ @register_pandas_matplotlib_converters
  def _make_plot(self, fig: Figure) -> None:
  x, y, c, data = self.x, self.y, self.c, self.data
  ax = self.axes[0]
 
+ x_data = data[x]
+ s = Series(index=x_data)
+ if use_dynamic_x(ax, s.index):
+ s = maybe_convert_index(ax, s)
+ freq, s = prepare_ts_data(s, ax, self.kwds)
+ x_data = s.index
+
  c_is_column = is_hashable(c) and c in self.data.columns
 
  color_by_categorical = c_is_column and isinstance(
@@ -1344,7 +1366,7 @@ def _make_plot(self, fig: Figure) -> None:
  else:
  label = None
 
- # if a list of non color strings is passed in as c, color points
+ # if a list of non-color strings is passed in as c, color points
  # by uniqueness of the strings, such same strings get same color
  create_colors = not self._are_valid_colors(c_values)
  if create_colors:
@@ -1360,7 +1382,7 @@ def _make_plot(self, fig: Figure) -> None:
  )
 
  scatter = ax.scatter(
- data[x].values,
+ x_data.values,
  data[y].values,
  c=c_values,
  label=label,
@@ -1520,23 +1542,9 @@ def _kind(self) -> Literal["line", "area", "hist", "kde", "box"]:
  return "line"
 
  def __init__(self, data, **kwargs) -> None:
- from pandas.plotting import plot_params
-
  MPLPlot.__init__(self, data, **kwargs)
  if self.stacked:
  self.data = self.data.fillna(value=0)
- self.x_compat = plot_params["x_compat"]
- if "x_compat" in self.kwds:
- self.x_compat = bool(self.kwds.pop("x_compat"))
-
- @final
- def _is_ts_plot(self) -> bool:
- # this is slightly deceptive
- return not self.x_compat and self.use_index and self._use_dynamic_x()
-
- @final
- def _use_dynamic_x(self) -> bool:
- return use_dynamic_x(self._get_ax(0), self.data)
 
  def _make_plot(self, fig: Figure) -> None:
  if self._is_ts_plot():
@@ -1626,15 +1634,8 @@ def _ts_plot(self, ax: Axes, x, data: Series, style=None, **kwds):
  # accept x to be consistent with normal plot func,
  # x is not passed to tsplot as it uses data.index as x coordinate
  # column_num must be in kwds for stacking purpose
- freq, data = maybe_resample(data, ax, kwds)
+ freq, data = prepare_ts_data(data, ax, kwds)
 
- # Set ax with freq info
- decorate_axes(ax, freq)
- # digging deeper
- if hasattr(ax, "left_ax"):
- decorate_axes(ax.left_ax, freq)
- if hasattr(ax, "right_ax"):
- decorate_axes(ax.right_ax, freq)
  # TODO #54485
  ax._plot_data.append((data, self._kind, kwds)) # type: ignore[attr-defined]
 

pandas/plotting/_matplotlib/timeseries.py

@@ -48,7 +48,6 @@
  from pandas._typing import NDFrameT
 
  from pandas import (
- DataFrame,
  DatetimeIndex,
  Index,
  PeriodIndex,
@@ -231,8 +230,8 @@ def _get_freq(ax: Axes, series: Series):
  return freq, ax_freq
 
 
-def use_dynamic_x(ax: Axes, data: DataFrame | Series) -> bool:
- freq = _get_index_freq(data.index)
+def use_dynamic_x(ax: Axes, index: Index) -> bool:
+ freq = _get_index_freq(index)
  ax_freq = _get_ax_freq(ax)
 
  if freq is None: # convert irregular if axes has freq info
@@ -250,16 +249,15 @@ def use_dynamic_x(ax: Axes, data: DataFrame | Series) -> bool:
  return False
 
  # FIXME: hack this for 0.10.1, creating more technical debt...sigh
- if isinstance(data.index, ABCDatetimeIndex):
+ if isinstance(index, ABCDatetimeIndex):
  # error: "BaseOffset" has no attribute "_period_dtype_code"
  freq_str = OFFSET_TO_PERIOD_FREQSTR.get(freq_str, freq_str)
  base = to_offset(freq_str, is_period=True)._period_dtype_code # type: ignore[attr-defined]
- x = data.index
  if base <= FreqGroup.FR_DAY.value:
- return x[:1].is_normalized
- period = Period(x[0], freq_str)
+ return index[:1].is_normalized
+ period = Period(index[0], freq_str)
  assert isinstance(period, Period)
- return period.to_timestamp().tz_localize(x.tz) == x[0]
+ return period.to_timestamp().tz_localize(index.tz) == index[0]
  return True
 
 
@@ -366,3 +364,17 @@ def format_dateaxis(
  raise TypeError("index type not supported")
 
  plt.draw_if_interactive()
+
+
+def prepare_ts_data(data, ax, kwds):
+ freq, data = maybe_resample(data, ax, kwds)
+
+ # Set ax with freq info
+ decorate_axes(ax, freq)
+ # digging deeper
+ if hasattr(ax, "left_ax"):
+ decorate_axes(ax.left_ax, freq)
+ if hasattr(ax, "right_ax"):
+ decorate_axes(ax.right_ax, freq)
+
+ return freq, data

pandas/tests/plotting/frame/test_frame.py

@@ -840,14 +840,26 @@ def test_plot_scatter_shape(self):
  axes = df.plot(x="x", y="y", kind="scatter", subplots=True)
  _check_axes_shape(axes, axes_num=1, layout=(1, 1))
 
- def test_raise_error_on_datetime_time_data(self):
- # GH 8113, datetime.time type is not supported by matplotlib in scatter
+ def test_scatter_on_datetime_time_data(self):
+ # datetime.time type is now supported in scatter, since a converter
+ # is implemented in ScatterPlot
  df = DataFrame(np.random.default_rng(2).standard_normal(10), columns=["a"])
  df["dtime"] = date_range(start="2014-01-01", freq="h", periods=10).time
- msg = "must be a string or a (real )?number, not 'datetime.time'"
-
- with pytest.raises(TypeError, match=msg):
- df.plot(kind="scatter", x="dtime", y="a")
+ df.plot(kind="scatter", x="dtime", y="a")
+
+ def test_scatter_line_xticks(self):
+ # GH#61005
+ datetime_list = [datetime(year=2025, month=1, day=1, hour=n) for n in range(3)]
+ df = DataFrame(columns=["datetime", "y"])
+ for i, n in enumerate(datetime_list):
+ df.loc[len(df)] = [n, i]
+ fig, ax = plt.subplots(2, sharex=True)
+ df.plot.scatter(x="datetime", y="y", ax=ax[0])
+ scatter_xticks = ax[0].get_xticks()
+ df.plot(x="datetime", y="y", ax=ax[1])
+ line_xticks = ax[1].get_xticks()
+ assert scatter_xticks[0] == line_xticks[0]
+ assert scatter_xticks[-1] == line_xticks[-1]
 
  @pytest.mark.parametrize("x, y", [("dates", "vals"), (0, 1)])
  def test_scatterplot_datetime_data(self, x, y):