DEPR: plotting deprecations (#30003)

doc/source/whatsnew/v1.0.0.rst

@@ -509,6 +509,10 @@ or ``matplotlib.Axes.plot``. See :ref:`plotting.formatters` for more.
 
 **Other removals**
 
+- Removed the previously deprecated :func:`pandas.plotting._matplotlib.tsplot`, use :meth:`Series.plot` instead (:issue:`19980`)
+- :func:`pandas.tseries.converter.register` has been moved to :func:`pandas.plotting.register_matplotlib_converters` (:issue:`18307`)
+- :meth:`Series.plot` no longer accepts positional arguments, pass keyword arguments instead (:issue:`30003`)
+- :meth:`DataFrame.hist` and :meth:`Series.hist` no longer allows ``figsize="default"``, specify figure size by passinig a tuple instead (:issue:`30003`)
 - Floordiv of integer-dtyped array by :class:`Timedelta` now raises ``TypeError`` (:issue:`21036`)
 - :func:`pandas.api.types.infer_dtype` argument ``skipna`` defaults to ``True`` instead of ``False`` (:issue:`24050`)
 - Removed the previously deprecated :meth:`Index.summary` (:issue:`18217`)

pandas/plotting/_core.py

@@ -1,5 +1,4 @@
 import importlib
-import warnings
 
 from pandas._config import get_option
 
@@ -752,7 +751,7 @@ def _get_call_args(backend_name, data, args, kwargs):
                 f"Use `Series.plot({keyword_args})` instead of "
                 f"`Series.plot({positional_args})`."
             )
-            warnings.warn(msg, FutureWarning, stacklevel=3)
+            raise TypeError(msg)
 
         pos_args = {name: value for value, (name, _) in zip(args, arg_def)}
         if backend_name == "pandas.plotting._matplotlib":

pandas/plotting/_matplotlib/__init__.py

@@ -24,7 +24,6 @@
     radviz,
     scatter_matrix,
 )
-from pandas.plotting._matplotlib.timeseries import tsplot
 from pandas.plotting._matplotlib.tools import table
 
 PLOT_CLASSES = {
@@ -66,7 +65,6 @@ def plot(data, kind, **kwargs):
     "boxplot",
     "boxplot_frame",
     "boxplot_frame_groupby",
-    "tsplot",
     "table",
     "andrews_curves",
     "autocorrelation_plot",

pandas/plotting/_matplotlib/hist.py

@@ -1,5 +1,3 @@
-import warnings
-
 import numpy as np
 
 from pandas.core.dtypes.common import is_integer, is_list_like
@@ -182,12 +180,10 @@ def _grouped_plot(
 
     if figsize == "default":
         # allowed to specify mpl default with 'default'
-        warnings.warn(
-            "figsize='default' is deprecated. Specify figure size by tuple instead",
-            FutureWarning,
-            stacklevel=5,
+        raise ValueError(
+            "figsize='default' is no longer supported. "
+            "Specify figure size by tuple instead"
         )
-        figsize = None
 
     grouped = data.groupby(by)
     if column is not None:

pandas/plotting/_matplotlib/timeseries.py

@@ -1,7 +1,6 @@
 # TODO: Use the fact that axis can have units to simplify the process
 
 import functools
-import warnings
 
 import numpy as np
 
@@ -25,7 +24,6 @@
     TimeSeries_DateFormatter,
     TimeSeries_DateLocator,
     TimeSeries_TimedeltaFormatter,
-    register_pandas_matplotlib_converters,
 )
 import pandas.tseries.frequencies as frequencies
 from pandas.tseries.offsets import DateOffset
@@ -34,49 +32,6 @@
 # Plotting functions and monkey patches
 
 
-@register_pandas_matplotlib_converters
-def tsplot(series, plotf, ax=None, **kwargs):
-    """
-    Plots a Series on the given Matplotlib axes or the current axes
-
-    Parameters
-    ----------
-    axes : Axes
-    series : Series
-
-    Notes
-    _____
-    Supports same kwargs as Axes.plot
-
-
-    .. deprecated:: 0.23.0
-       Use Series.plot() instead
-    """
-    import matplotlib.pyplot as plt
-
-    warnings.warn(
-        "'tsplot' is deprecated and will be removed in a "
-        "future version. Please use Series.plot() instead.",
-        FutureWarning,
-        stacklevel=3,
-    )
-
-    # Used inferred freq is possible, need a test case for inferred
-    if ax is None:
-        ax = plt.gca()
-
-    freq, series = _maybe_resample(series, ax, kwargs)
-
-    # Set ax with freq info
-    _decorate_axes(ax, freq, kwargs)
-    ax._plot_data.append((series, plotf, kwargs))
-    lines = plotf(ax, series.index._mpl_repr(), series.values, **kwargs)
-
-    # set date formatter, locators and rescale limits
-    format_dateaxis(ax, ax.freq, series.index)
-    return lines
-
-
 def _maybe_resample(series, ax, kwargs):
     # resample against axes freq if necessary
     freq, ax_freq = _get_freq(ax, series)

pandas/tests/plotting/test_converter.py

@@ -139,15 +139,6 @@ def test_registry_resets(self):
             for k, v in original.items():
                 units.registry[k] = v
 
-    def test_old_import_warns(self):
-        with tm.assert_produces_warning(FutureWarning) as w:
-            from pandas.tseries import converter
-
-            converter.register()
-
-        assert len(w)
-        assert "pandas.plotting.register_matplotlib_converters" in str(w[0].message)
-
 
 class TestDateTimeConverter:
     def setup_method(self, method):

pandas/tests/plotting/test_hist_method.py

@@ -313,7 +313,8 @@ def test_grouped_hist_legacy(self):
         with pytest.raises(AttributeError):
             _grouped_hist(df.A, by=df.C, foo="bar")
 
-        with tm.assert_produces_warning(FutureWarning):
+        msg = "Specify figure size by tuple instead"
+        with pytest.raises(ValueError, match=msg):
             df.hist(by="C", figsize="default")
 
     @pytest.mark.slow

pandas/tests/plotting/test_misc.py

@@ -32,14 +32,9 @@ def test_get_accessor_args():
     with pytest.raises(TypeError, match=msg):
         func(backend_name="", data=[], args=[], kwargs={})
 
-    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
-        x, y, kind, kwargs = func(
-            backend_name="", data=Series(), args=["line", None], kwargs={}
-        )
-    assert x is None
-    assert y is None
-    assert kind == "line"
-    assert kwargs == {"ax": None}
+    msg = "should not be called with positional arguments"
+    with pytest.raises(TypeError, match=msg):
+        func(backend_name="", data=Series(), args=["line", None], kwargs={})
 
     x, y, kind, kwargs = func(
         backend_name="",