REF/TST: misplaced DataFrame.join tests

pandas/tests/frame/test_combine_concat.py

@@ -8,7 +8,7 @@
 import pandas._testing as tm
 
 
-class TestDataFrameConcatCommon:
+class TestDataFrameConcat:
     def test_concat_multiple_frames_dtypes(self):
 
         # GH 2759
@@ -107,77 +107,6 @@ def test_concat_tuple_keys(self):
         )
         tm.assert_frame_equal(results, expected)
 
-    def test_join_str_datetime(self):
-        str_dates = ["20120209", "20120222"]
-        dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
-
-        A = DataFrame(str_dates, index=range(2), columns=["aa"])
-        C = DataFrame([[1, 2], [3, 4]], index=str_dates, columns=dt_dates)
-
-        tst = A.join(C, on="aa")
-
-        assert len(tst.columns) == 3
-
-    def test_join_multiindex_leftright(self):
-        # GH 10741
-        df1 = pd.DataFrame(
-            [
-                ["a", "x", 0.471780],
-                ["a", "y", 0.774908],
-                ["a", "z", 0.563634],
-                ["b", "x", -0.353756],
-                ["b", "y", 0.368062],
-                ["b", "z", -1.721840],
-                ["c", "x", 1],
-                ["c", "y", 2],
-                ["c", "z", 3],
-            ],
-            columns=["first", "second", "value1"],
-        ).set_index(["first", "second"])
-
-        df2 = pd.DataFrame(
-            [["a", 10], ["b", 20]], columns=["first", "value2"]
-        ).set_index(["first"])
-
-        exp = pd.DataFrame(
-            [
-                [0.471780, 10],
-                [0.774908, 10],
-                [0.563634, 10],
-                [-0.353756, 20],
-                [0.368062, 20],
-                [-1.721840, 20],
-                [1.000000, np.nan],
-                [2.000000, np.nan],
-                [3.000000, np.nan],
-            ],
-            index=df1.index,
-            columns=["value1", "value2"],
-        )
-
-        # these must be the same results (but columns are flipped)
-        tm.assert_frame_equal(df1.join(df2, how="left"), exp)
-        tm.assert_frame_equal(df2.join(df1, how="right"), exp[["value2", "value1"]])
-
-        exp_idx = pd.MultiIndex.from_product(
-            [["a", "b"], ["x", "y", "z"]], names=["first", "second"]
-        )
-        exp = pd.DataFrame(
-            [
-                [0.471780, 10],
-                [0.774908, 10],
-                [0.563634, 10],
-                [-0.353756, 20],
-                [0.368062, 20],
-                [-1.721840, 20],
-            ],
-            index=exp_idx,
-            columns=["value1", "value2"],
-        )
-
-        tm.assert_frame_equal(df1.join(df2, how="right"), exp)
-        tm.assert_frame_equal(df2.join(df1, how="left"), exp[["value2", "value1"]])
-
     def test_concat_named_keys(self):
         # GH 14252
         df = pd.DataFrame({"foo": [1, 2], "bar": [0.1, 0.2]})

pandas/tests/frame/test_join.py

@@ -1,6 +1,9 @@
+from datetime import datetime
+
 import numpy as np
 import pytest
 
+import pandas as pd
 from pandas import DataFrame, Index, period_range
 import pandas._testing as tm
 
@@ -216,3 +219,76 @@ def test_suppress_future_warning_with_sort_kw(sort_kw):
     with tm.assert_produces_warning(None, check_stacklevel=False):
         result = a.join([b, c], how="outer", sort=sort_kw)
     tm.assert_frame_equal(result, expected)
+
+
+class TestDataFrameJoin:
+    def test_join_str_datetime(self):
+        str_dates = ["20120209", "20120222"]
+        dt_dates = [datetime(2012, 2, 9), datetime(2012, 2, 22)]
+
+        A = DataFrame(str_dates, index=range(2), columns=["aa"])
+        C = DataFrame([[1, 2], [3, 4]], index=str_dates, columns=dt_dates)
+
+        tst = A.join(C, on="aa")
+
+        assert len(tst.columns) == 3
+
+    def test_join_multiindex_leftright(self):
+        # GH 10741
+        df1 = pd.DataFrame(
+            [
+                ["a", "x", 0.471780],
+                ["a", "y", 0.774908],
+                ["a", "z", 0.563634],
+                ["b", "x", -0.353756],
+                ["b", "y", 0.368062],
+                ["b", "z", -1.721840],
+                ["c", "x", 1],
+                ["c", "y", 2],
+                ["c", "z", 3],
+            ],
+            columns=["first", "second", "value1"],
+        ).set_index(["first", "second"])
+
+        df2 = pd.DataFrame(
+            [["a", 10], ["b", 20]], columns=["first", "value2"]
+        ).set_index(["first"])
+
+        exp = pd.DataFrame(
+            [
+                [0.471780, 10],
+                [0.774908, 10],
+                [0.563634, 10],
+                [-0.353756, 20],
+                [0.368062, 20],
+                [-1.721840, 20],
+                [1.000000, np.nan],
+                [2.000000, np.nan],
+                [3.000000, np.nan],
+            ],
+            index=df1.index,
+            columns=["value1", "value2"],
+        )
+
+        # these must be the same results (but columns are flipped)
+        tm.assert_frame_equal(df1.join(df2, how="left"), exp)
+        tm.assert_frame_equal(df2.join(df1, how="right"), exp[["value2", "value1"]])
+
+        exp_idx = pd.MultiIndex.from_product(
+            [["a", "b"], ["x", "y", "z"]], names=["first", "second"]
+        )
+        exp = pd.DataFrame(
+            [
+                [0.471780, 10],
+                [0.774908, 10],
+                [0.563634, 10],
+                [-0.353756, 20],
+                [0.368062, 20],
+                [-1.721840, 20],
+            ],
+            index=exp_idx,
+            columns=["value1", "value2"],
+        )
+
+        tm.assert_frame_equal(df1.join(df2, how="right"), exp)
+        tm.assert_frame_equal(df2.join(df1, how="left"), exp[["value2", "value1"]])

pandas/tests/series/test_combine_concat.py

@@ -5,7 +5,7 @@
 from pandas import Series
 
 
-class TestSeriesCombine:
+class TestSeriesConcat:
     @pytest.mark.parametrize(
         "dtype", ["float64", "int8", "uint8", "bool", "m8[ns]", "M8[ns]"]
     )