TST: Split up groupby.shift and groupby.diff tests into two different files.

Author: vladu

pandas/tests/groupby/test_groupby_diff.py

@@ -0,0 +1,54 @@
+import numpy as np
+import pytest
+
+from pandas import (
+    DataFrame,
+    NaT,
+    Series,
+    Timedelta,
+    Timestamp,
+)
+import pandas._testing as tm
+
+
+def test_group_diff_real(any_real_dtype):
+    df = DataFrame({"a": [1, 2, 3, 3, 2], "b": [1, 2, 3, 4, 5]}, dtype=any_real_dtype)
+    result = df.groupby("a")["b"].diff()
+    exp_dtype = "float"
+    if any_real_dtype in ["int8", "int16", "float32"]:
+        exp_dtype = "float32"
+    expected = Series([np.nan, np.nan, np.nan, 1.0, 3.0], dtype=exp_dtype, name="b")
+    tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "data",
+    [
+        [
+            Timestamp("2013-01-01"),
+            Timestamp("2013-01-02"),
+            Timestamp("2013-01-03"),
+        ],
+        [Timedelta("5 days"), Timedelta("6 days"), Timedelta("7 days")],
+    ],
+)
+def test_group_diff_datetimelike(data):
+    df = DataFrame({"a": [1, 2, 2], "b": data})
+    result = df.groupby("a")["b"].diff()
+    expected = Series([NaT, NaT, Timedelta("1 days")], name="b")
+    tm.assert_series_equal(result, expected)
+
+
+def test_group_diff_bool():
+    df = DataFrame({"a": [1, 2, 3, 3, 2], "b": [True, True, False, False, True]})
+    result = df.groupby("a")["b"].diff()
+    expected = Series([np.nan, np.nan, np.nan, False, False], name="b")
+    tm.assert_series_equal(result, expected)
+
+
+def test_group_diff_object_raises(object_dtype):
+    df = DataFrame(
+        {"a": ["foo", "bar", "bar"], "b": ["baz", "foo", "foo"]}, dtype=object_dtype
+    )
+    with pytest.raises(TypeError, match=r"unsupported operand type\(s\) for -"):
+        df.groupby("a")["b"].diff()

pandas/tests/groupby/test_groupby_shift_diff.py renamed to pandas/tests/groupby/test_groupby_shift.py

@@ -1,11 +1,8 @@
 import numpy as np
-import pytest
 
 from pandas import (
     DataFrame,
-    NaT,
     Series,
-    Timedelta,
     Timestamp,
 )
 import pandas._testing as tm
@@ -67,46 +64,3 @@ def test_group_shift_lose_timezone():
     result = df.groupby("a").shift(0).iloc[0]
     expected = Series({"date": now_dt}, name=result.name)
     tm.assert_series_equal(result, expected)
-
-
-def test_group_diff_real(any_real_dtype):
-    df = DataFrame({"a": [1, 2, 3, 3, 2], "b": [1, 2, 3, 4, 5]}, dtype=any_real_dtype)
-    result = df.groupby("a")["b"].diff()
-    exp_dtype = "float"
-    if any_real_dtype in ["int8", "int16", "float32"]:
-        exp_dtype = "float32"
-    expected = Series([np.nan, np.nan, np.nan, 1.0, 3.0], dtype=exp_dtype, name="b")
-    tm.assert_series_equal(result, expected)
-
-
-@pytest.mark.parametrize(
-    "data",
-    [
-        [
-            Timestamp("2013-01-01"),
-            Timestamp("2013-01-02"),
-            Timestamp("2013-01-03"),
-        ],
-        [Timedelta("5 days"), Timedelta("6 days"), Timedelta("7 days")],
-    ],
-)
-def test_group_diff_datetimelike(data):
-    df = DataFrame({"a": [1, 2, 2], "b": data})
-    result = df.groupby("a")["b"].diff()
-    expected = Series([NaT, NaT, Timedelta("1 days")], name="b")
-    tm.assert_series_equal(result, expected)
-
-
-def test_group_diff_bool():
-    df = DataFrame({"a": [1, 2, 3, 3, 2], "b": [True, True, False, False, True]})
-    result = df.groupby("a")["b"].diff()
-    expected = Series([np.nan, np.nan, np.nan, False, False], name="b")
-    tm.assert_series_equal(result, expected)
-
-
-def test_group_diff_object_raises(object_dtype):
-    df = DataFrame(
-        {"a": ["foo", "bar", "bar"], "b": ["baz", "foo", "foo"]}, dtype=object_dtype
-    )
-    with pytest.raises(TypeError, match=r"unsupported operand type\(s\) for -"):
-        df.groupby("a")["b"].diff()