TST: Clean tests/plotting/test_frame.py misc (pandas-dev#53914)

Author: mroeschke

pandas/tests/plotting/frame/test_frame_legend.py

@@ -26,7 +26,6 @@ class TestFrameLegend:
     )
     def test_mixed_yerr(self):
         # https://github.com/pandas-dev/pandas/issues/39522
-        import matplotlib as mpl
         from matplotlib.collections import LineCollection
         from matplotlib.lines import Line2D
 
@@ -46,8 +45,6 @@ def test_mixed_yerr(self):
 
     def test_legend_false(self):
         # https://github.com/pandas-dev/pandas/issues/40044
-        import matplotlib as mpl
-
         df = DataFrame({"a": [1, 1], "b": [2, 3]})
         df2 = DataFrame({"d": [2.5, 2.5]})
 
@@ -63,27 +60,31 @@ def test_legend_false(self):
         assert result == expected
 
     @td.skip_if_no_scipy
-    def test_df_legend_labels(self):
-        kinds = ["line", "bar", "barh", "kde", "area", "hist"]
+    @pytest.mark.parametrize("kind", ["line", "bar", "barh", "kde", "area", "hist"])
+    def test_df_legend_labels(self, kind):
         df = DataFrame(np.random.rand(3, 3), columns=["a", "b", "c"])
         df2 = DataFrame(np.random.rand(3, 3), columns=["d", "e", "f"])
         df3 = DataFrame(np.random.rand(3, 3), columns=["g", "h", "i"])
         df4 = DataFrame(np.random.rand(3, 3), columns=["j", "k", "l"])
 
-        for kind in kinds:
-            ax = df.plot(kind=kind, legend=True)
-            _check_legend_labels(ax, labels=df.columns)
+        ax = df.plot(kind=kind, legend=True)
+        _check_legend_labels(ax, labels=df.columns)
 
-            ax = df2.plot(kind=kind, legend=False, ax=ax)
-            _check_legend_labels(ax, labels=df.columns)
+        ax = df2.plot(kind=kind, legend=False, ax=ax)
+        _check_legend_labels(ax, labels=df.columns)
 
-            ax = df3.plot(kind=kind, legend=True, ax=ax)
-            _check_legend_labels(ax, labels=df.columns.union(df3.columns))
+        ax = df3.plot(kind=kind, legend=True, ax=ax)
+        _check_legend_labels(ax, labels=df.columns.union(df3.columns))
 
-            ax = df4.plot(kind=kind, legend="reverse", ax=ax)
-            expected = list(df.columns.union(df3.columns)) + list(reversed(df4.columns))
-            _check_legend_labels(ax, labels=expected)
+        ax = df4.plot(kind=kind, legend="reverse", ax=ax)
+        expected = list(df.columns.union(df3.columns)) + list(reversed(df4.columns))
+        _check_legend_labels(ax, labels=expected)
 
+    @td.skip_if_no_scipy
+    def test_df_legend_labels_secondary_y(self):
+        df = DataFrame(np.random.rand(3, 3), columns=["a", "b", "c"])
+        df2 = DataFrame(np.random.rand(3, 3), columns=["d", "e", "f"])
+        df3 = DataFrame(np.random.rand(3, 3), columns=["g", "h", "i"])
         # Secondary Y
         ax = df.plot(legend=True, secondary_y="b")
         _check_legend_labels(ax, labels=["a", "b (right)", "c"])
@@ -92,6 +93,8 @@ def test_df_legend_labels(self):
         ax = df3.plot(kind="bar", legend=True, secondary_y="h", ax=ax)
         _check_legend_labels(ax, labels=["a", "b (right)", "c", "g", "h (right)", "i"])
 
+    @td.skip_if_no_scipy
+    def test_df_legend_labels_time_series(self):
         # Time Series
         ind = date_range("1/1/2014", periods=3)
         df = DataFrame(np.random.randn(3, 3), columns=["a", "b", "c"], index=ind)
@@ -104,6 +107,13 @@ def test_df_legend_labels(self):
         ax = df3.plot(legend=True, ax=ax)
         _check_legend_labels(ax, labels=["a", "b (right)", "c", "g", "h", "i"])
 
+    @td.skip_if_no_scipy
+    def test_df_legend_labels_time_series_scatter(self):
+        # Time Series
+        ind = date_range("1/1/2014", periods=3)
+        df = DataFrame(np.random.randn(3, 3), columns=["a", "b", "c"], index=ind)
+        df2 = DataFrame(np.random.randn(3, 3), columns=["d", "e", "f"], index=ind)
+        df3 = DataFrame(np.random.randn(3, 3), columns=["g", "h", "i"], index=ind)
         # scatter
         ax = df.plot.scatter(x="a", y="b", label="data1")
         _check_legend_labels(ax, labels=["data1"])
@@ -112,6 +122,10 @@ def test_df_legend_labels(self):
         ax = df3.plot.scatter(x="g", y="h", label="data3", ax=ax)
         _check_legend_labels(ax, labels=["data1", "data3"])
 
+    @td.skip_if_no_scipy
+    def test_df_legend_labels_time_series_no_mutate(self):
+        ind = date_range("1/1/2014", periods=3)
+        df = DataFrame(np.random.randn(3, 3), columns=["a", "b", "c"], index=ind)
         # ensure label args pass through and
         # index name does not mutate
         # column names don't mutate
@@ -128,7 +142,7 @@ def test_df_legend_labels(self):
     def test_missing_marker_multi_plots_on_same_ax(self):
         # GH 18222
         df = DataFrame(data=[[1, 1, 1, 1], [2, 2, 4, 8]], columns=["x", "r", "g", "b"])
-        fig, ax = mpl.pyplot.subplots(nrows=1, ncols=3)
+        _, ax = mpl.pyplot.subplots(nrows=1, ncols=3)
         # Left plot
         df.plot(x="x", y="r", linewidth=0, marker="o", color="r", ax=ax[0])
         df.plot(x="x", y="g", linewidth=1, marker="x", color="g", ax=ax[0])
@@ -210,7 +224,7 @@ def test_missing_markers_legend_using_style(self):
             }
         )
 
-        fig, ax = mpl.pyplot.subplots()
+        _, ax = mpl.pyplot.subplots()
         for kind in "ABC":
             df.plot("X", kind, label=kind, ax=ax, style=".")