Fix: Reanme duplicate function names in unittests

pandas/tests/groupby/aggregate/test_aggregate.py

@@ -281,8 +281,8 @@ def test_groupby_mixed_cols_axis1(func, expected_data, result_dtype_dict):
 def test_aggregate_item_by_item(df):
     grouped = df.groupby("A")
 
-    aggfun = lambda ser: ser.size
-    result = grouped.agg(aggfun)
+    aggfun_0 = lambda ser: ser.size
+    result = grouped.agg(aggfun_0)
     foo = (df.A == "foo").sum()
     bar = (df.A == "bar").sum()
     K = len(result.columns)
@@ -294,10 +294,10 @@ def test_aggregate_item_by_item(df):
     exp = Series(np.array([bar] * K), index=list("BCD"), name="bar")
     tm.assert_almost_equal(result.xs("bar"), exp)
 
-    def aggfun(ser):
+    def aggfun_1(ser):
         return ser.size
 
-    result = DataFrame().groupby(df.A).agg(aggfun)
+    result = DataFrame().groupby(df.A).agg(aggfun_1)
     assert isinstance(result, DataFrame)
     assert len(result) == 0
 

pandas/tests/groupby/test_groupby.py

@@ -112,6 +112,10 @@ def max_value(group):
 def test_groupby_return_type():
 
     # GH2893, return a reduced type
+
+    def func(dataf):
+        return dataf["val2"] - dataf["val2"].mean()
+
     df1 = DataFrame(
         [
             {"val1": 1, "val2": 20},
@@ -121,9 +125,6 @@ def test_groupby_return_type():
         ]
     )
 
-    def func(dataf):
-        return dataf["val2"] - dataf["val2"].mean()
-
     with tm.assert_produces_warning(FutureWarning):
         result = df1.groupby("val1", squeeze=True).apply(func)
     assert isinstance(result, Series)
@@ -137,9 +138,6 @@ def func(dataf):
         ]
     )
 
-    def func(dataf):
-        return dataf["val2"] - dataf["val2"].mean()
-
     with tm.assert_produces_warning(FutureWarning):
         result = df2.groupby("val1", squeeze=True).apply(func)
     assert isinstance(result, Series)
@@ -162,51 +160,51 @@ def test_inconsistent_return_type():
         }
     )
 
-    def f(grp):
+    def f_0(grp):
         return grp.iloc[0]
 
     expected = df.groupby("A").first()[["B"]]
-    result = df.groupby("A").apply(f)[["B"]]
+    result = df.groupby("A").apply(f_0)[["B"]]
     tm.assert_frame_equal(result, expected)
 
-    def f(grp):
+    def f_1(grp):
         if grp.name == "Tiger":
             return None
         return grp.iloc[0]
 
-    result = df.groupby("A").apply(f)[["B"]]
+    result = df.groupby("A").apply(f_1)[["B"]]
     e = expected.copy()
     e.loc["Tiger"] = np.nan
     tm.assert_frame_equal(result, e)
 
-    def f(grp):
+    def f_2(grp):
         if grp.name == "Pony":
             return None
         return grp.iloc[0]
 
-    result = df.groupby("A").apply(f)[["B"]]
+    result = df.groupby("A").apply(f_2)[["B"]]
     e = expected.copy()
     e.loc["Pony"] = np.nan
     tm.assert_frame_equal(result, e)
 
     # 5592 revisited, with datetimes
-    def f(grp):
+    def f_3(grp):
         if grp.name == "Pony":
             return None
         return grp.iloc[0]
 
-    result = df.groupby("A").apply(f)[["C"]]
+    result = df.groupby("A").apply(f_3)[["C"]]
     e = df.groupby("A").first()[["C"]]
     e.loc["Pony"] = pd.NaT
     tm.assert_frame_equal(result, e)
 
     # scalar outputs
-    def f(grp):
+    def f_4(grp):
         if grp.name == "Pony":
             return None
         return grp.iloc[0].loc["C"]
 
-    result = df.groupby("A").apply(f)
+    result = df.groupby("A").apply(f_4)
     e = df.groupby("A").first()["C"].copy()
     e.loc["Pony"] = np.nan
     e.name = None

pandas/tests/io/pytables/test_append.py

@@ -437,9 +437,6 @@ def check_col(key, name, size):
 
     with ensure_clean_store(setup_path) as store:
 
-        def check_col(key, name, size):
-            assert getattr(store.get_storer(key).table.description, name).itemsize, size
-
         df = DataFrame({"A": "foo", "B": "bar"}, index=range(10))
 
         # a min_itemsize that creates a data_column

pandas/tests/resample/test_resampler_grouper.py

@@ -65,10 +65,10 @@ def test_deferred_with_groupby():
     df = DataFrame(data, columns=["date", "id", "score"])
     df.date = pd.to_datetime(df.date)
 
-    def f(x):
+    def f_0(x):
         return x.set_index("date").resample("D").asfreq()
 
-    expected = df.groupby("id").apply(f)
+    expected = df.groupby("id").apply(f_0)
     result = df.set_index("date").groupby("id").resample("D").asfreq()
     tm.assert_frame_equal(result, expected)
 
@@ -80,10 +80,10 @@ def f(x):
         }
     ).set_index("date")
 
-    def f(x):
+    def f_1(x):
         return x.resample("1D").ffill()
 
-    expected = df.groupby("group").apply(f)
+    expected = df.groupby("group").apply(f_1)
     result = df.groupby("group").resample("1D").ffill()
     tm.assert_frame_equal(result, expected)
 
@@ -257,16 +257,16 @@ def test_apply():
     # reduction
     expected = g.resample("2s").sum()
 
-    def f(x):
+    def f_0(x):
         return x.resample("2s").sum()
 
-    result = r.apply(f)
+    result = r.apply(f_0)
     tm.assert_frame_equal(result, expected)
 
-    def f(x):
+    def f_1(x):
         return x.resample("2s").apply(lambda y: y.sum())
 
-    result = g.apply(f)
+    result = g.apply(f_1)
     # y.sum() results in int64 instead of int32 on 32-bit architectures
     expected = expected.astype("int64")
     tm.assert_frame_equal(result, expected)

pandas/tests/window/test_groupby.py

@@ -1064,10 +1064,10 @@ def test_expanding_corr_cov(self, f):
 
         result = getattr(r, f)(self.frame)
 
-        def func(x):
+        def func_0(x):
             return getattr(x.expanding(), f)(self.frame)
 
-        expected = g.apply(func)
+        expected = g.apply(func_0)
         # GH 39591: groupby.apply returns 1 instead of nan for windows
         # with all nan values
         null_idx = list(range(20, 61)) + list(range(72, 113))
@@ -1079,10 +1079,10 @@ def func(x):
 
         result = getattr(r.B, f)(pairwise=True)
 
-        def func(x):
+        def func_1(x):
             return getattr(x.B.expanding(), f)(pairwise=True)
 
-        expected = g.apply(func)
+        expected = g.apply(func_1)
         tm.assert_series_equal(result, expected)
 
     def test_expanding_apply(self, raw):

pyproject.toml

@@ -41,7 +41,6 @@ disable = [
   "access-member-before-definition",
   "bad-super-call",
   "c-extension-no-member",
-  "function-redefined",
   "import-error",
   "inherit-non-class",
   "invalid-repr-returned",