Fix multiple moves with pairing (#2817)

This was a simple bug

seaborn/_core/plot.py

@@ -1104,15 +1104,15 @@ def get_order(var):
 
             if move is not None:
                 moves = move if isinstance(move, list) else [move]
-                for move in moves:
+                for move_step in moves:
                     move_groupers = [
                         orient,
-                        *(getattr(move, "by", None) or grouping_properties),
+                        *(getattr(move_step, "by", None) or grouping_properties),
                         *default_grouping_vars,
                     ]
                     order = {var: get_order(var) for var in move_groupers}
                     groupby = GroupBy(order)
-                    df = move(df, groupby, orient)
+                    df = move_step(df, groupby, orient)
 
             df = self._unscale_coords(subplots, df, orient)
 

seaborn/tests/_core/test_plot.py

@@ -15,7 +15,7 @@
 from seaborn._core.plot import Plot
 from seaborn._core.scales import Nominal, Continuous
 from seaborn._core.rules import categorical_order
-from seaborn._core.moves import Move
+from seaborn._core.moves import Move, Shift
 from seaborn._marks.base import Mark
 from seaborn._stats.base import Stat
 from seaborn.external.version import Version
@@ -817,29 +817,35 @@ def test_movement(self, long_df):
 
         orig_df = long_df.copy(deep=True)
 
-        class MockMove(Move):
-            def __call__(self, data, groupby, orient):
-                return data.assign(x=data["x"] + 1)
-
         m = MockMark()
-        Plot(long_df, x="z", y="z").add(m, move=MockMove()).plot()
+        Plot(long_df, x="z", y="z").add(m, move=Shift(x=1)).plot()
         assert_vector_equal(m.passed_data[0]["x"], long_df["z"] + 1)
         assert_vector_equal(m.passed_data[0]["y"], long_df["z"])
 
         assert_frame_equal(long_df, orig_df)   # Test data was not mutated
 
     def test_movement_log_scale(self, long_df):
 
-        class MockMove(Move):
-            def __call__(self, data, groupby, orient):
-                return data.assign(x=data["x"] - 1)
-
         m = MockMark()
         Plot(
             long_df, x="z", y="z"
-        ).scale(x="log").add(m, move=MockMove()).plot()
+        ).scale(x="log").add(m, move=Shift(x=-1)).plot()
         assert_vector_equal(m.passed_data[0]["x"], long_df["z"] / 10)
 
+    def test_multi_move(self, long_df):
+
+        m = MockMark()
+        move_stack = [Shift(1), Shift(2)]
+        Plot(long_df, x="x", y="y").add(m, move=move_stack).plot()
+        assert_vector_equal(m.passed_data[0]["x"], long_df["x"] + 3)
+
+    def test_multi_move_with_pairing(self, long_df):
+        m = MockMark()
+        move_stack = [Shift(1), Shift(2)]
+        Plot(long_df, x="x").pair(y=["y", "z"]).add(m, move=move_stack).plot()
+        for frame in m.passed_data:
+            assert_vector_equal(frame["x"], long_df["x"] + 3)
+
     def test_methods_clone(self, long_df):
 
         p1 = Plot(long_df, "x", "y")