TST: Add dedicated test for plt.savefig

pandas/tests/plotting/common.py

@@ -535,9 +535,6 @@ def _check_plot_works(f, default_axes=False, **kwargs):
         for ret in gen_plots(f, fig, **kwargs):
             tm.assert_is_valid_plot_return_object(ret)
 
-        with tm.ensure_clean(return_filelike=True) as path:
-            plt.savefig(path)
-
     finally:
         plt.close(fig)
 

pandas/tests/plotting/test_datetimelike.py

@@ -1645,9 +1645,6 @@ def _check_plot_works(f, freq=None, series=None, *args, **kwargs):
         ret = f(*args, **kwargs)
         assert ret is not None  # TODO: do something more intelligent
 
-        with tm.ensure_clean(return_filelike=True) as path:
-            plt.savefig(path)
-
         # GH18439, GH#24088, statsmodels#4772
         with tm.ensure_clean(return_filelike=True) as path:
             pickle.dump(fig, path)

pandas/tests/plotting/test_misc.py

@@ -1,4 +1,5 @@
 """ Test cases for misc plot functions """
+import os
 
 import numpy as np
 import pytest
@@ -10,7 +11,9 @@
     Index,
     Series,
     Timestamp,
+    date_range,
     interval_range,
+    period_range,
     plotting,
 )
 import pandas._testing as tm
@@ -23,6 +26,7 @@
 )
 
 mpl = pytest.importorskip("matplotlib")
+plt = pytest.importorskip("matplotlib.pyplot")
 cm = pytest.importorskip("matplotlib.cm")
 
 
@@ -69,6 +73,30 @@ def test_get_accessor_args():
     assert len(kwargs) == 24
 
 
+@pytest.mark.parametrize("kind", plotting.PlotAccessor._all_kinds)
+@pytest.mark.parametrize(
+    "data", [DataFrame(np.arange(15).reshape(5, 3)), Series(range(5))]
+)
+@pytest.mark.parametrize(
+    "index",
+    [
+        Index(range(5)),
+        date_range("2020-01-01", periods=5),
+        period_range("2020-01-01", periods=5),
+    ],
+)
+def test_savefig(kind, data, index):
+    fig, ax = plt.subplots()
+    data.index = index
+    kwargs = {}
+    if kind in ["hexbin", "scatter", "pie"]:
+        if isinstance(data, Series):
+            pytest.skip(f"{kind} not supported with Series")
+        kwargs = {"x": 0, "y": 1}
+    data.plot(kind=kind, ax=ax, **kwargs)
+    fig.savefig(os.devnull)
+
+
 class TestSeriesPlots:
     def test_autocorrelation_plot(self):
         from pandas.plotting import autocorrelation_plot