add missing return

Author: MarcoGorelli

pandas/tests/frame/methods/test_reset_index.py

@@ -337,24 +337,19 @@ def test_reset_index_multiindex_nan(self):
         tm.assert_frame_equal(rs, df)
 
     @pytest.mark.parametrize(
-        "name",
+        "name, warn",
         [
-            None,
-            "foo",
-            2,
-            3.0,
-            pd.Timedelta(6),
-            Timestamp("2012-12-30", tz="UTC"),
-            "2012-12-31",
+            (None, UserWarning),
+            ("foo", UserWarning),
+            (2, None),
+            (3.0, None),
+            (pd.Timedelta(6), None),
+            (Timestamp("2012-12-30", tz="UTC"), FutureWarning),
+            ("2012-12-31", None),
         ],
     )
-    def test_reset_index_with_datetimeindex_cols(self, name):
+    def test_reset_index_with_datetimeindex_cols(self, name, warn):
         # GH#5818
-        warn = None
-        if isinstance(name, Timestamp) and name.tz is not None:
-            # _deprecate_mismatched_indexing
-            warn = FutureWarning
-
         df = DataFrame(
             [[1, 2], [3, 4]],
             columns=date_range("1/1/2013", "1/2/2013"),

pandas/tests/io/parser/test_parse_dates.py

@@ -1630,7 +1630,12 @@ def test_parse_date_column_with_empty_string(all_parsers):
     # see gh-6428
     parser = all_parsers
     data = "case,opdate\n7,10/18/2006\n7,10/18/2008\n621, "
-    result = parser.read_csv(StringIO(data), parse_dates=["opdate"])
+    result = parser.read_csv_check_warnings(
+        UserWarning,
+        "Parsing datetime strings without a format specified",
+        StringIO(data),
+        parse_dates=["opdate"],
+    )
 
     expected_data = [[7, "10/18/2006"], [7, "10/18/2008"], [621, " "]]
     expected = DataFrame(expected_data, columns=["case", "opdate"])

pandas/tests/scalar/period/test_period.py

@@ -51,8 +51,12 @@ def test_from_td64nat_raises(self):
             Period(td, freq="D")
 
     def test_construction(self):
-        i1 = Period("1/1/2005", freq="M")
-        i2 = Period("Jan 2005")
+        with tm.assert_produces_warning(
+            UserWarning,
+            match="Parsing datetime strings without a format specified",
+        ):
+            i1 = Period("1/1/2005", freq="M")
+            i2 = Period("Jan 2005")
 
         assert i1 == i2
 
@@ -81,7 +85,11 @@ def test_construction(self):
         assert i1 == i2
 
         i1 = Period(year=2005, month=3, day=1, freq="D")
-        i2 = Period("3/1/2005", freq="D")
+        with tm.assert_produces_warning(
+            UserWarning,
+            match="Parsing datetime strings without a format specified",
+        ):
+            i2 = Period("3/1/2005", freq="D")
         assert i1 == i2
 
         i3 = Period(year=2005, month=3, day=1, freq="d")
@@ -169,11 +177,19 @@ def test_construction_bday(self):
     def test_construction_quarter(self):
 
         i1 = Period(year=2005, quarter=1, freq="Q")
-        i2 = Period("1/1/2005", freq="Q")
+        with tm.assert_produces_warning(
+            UserWarning,
+            match="Parsing datetime strings without a format specified",
+        ):
+            i2 = Period("1/1/2005", freq="Q")
         assert i1 == i2
 
         i1 = Period(year=2005, quarter=3, freq="Q")
-        i2 = Period("9/1/2005", freq="Q")
+        with tm.assert_produces_warning(
+            UserWarning,
+            match="Parsing datetime strings without a format specified",
+        ):
+            i2 = Period("9/1/2005", freq="Q")
         assert i1 == i2
 
         i1 = Period("2005Q1")
@@ -248,9 +264,13 @@ def test_construction_month(self):
         assert i1 == i5
 
     def test_period_constructor_offsets(self):
-        assert Period("1/1/2005", freq=offsets.MonthEnd()) == Period(
-            "1/1/2005", freq="M"
-        )
+        with tm.assert_produces_warning(
+            UserWarning,
+            match="Parsing datetime strings without a format specified",
+        ):
+            assert Period("1/1/2005", freq=offsets.MonthEnd()) == Period(
+                "1/1/2005", freq="M"
+            )
         assert Period("2005", freq=offsets.YearEnd()) == Period("2005", freq="A")
         assert Period("2005", freq=offsets.MonthEnd()) == Period("2005", freq="M")
         assert Period("3/10/2012", freq=offsets.BusinessDay()) == Period(
@@ -281,7 +301,8 @@ def test_period_constructor_offsets(self):
         )
 
         with tm.assert_produces_warning(
-            UserWarning, match="without a format specified"
+            UserWarning,
+            match="Parsing datetime strings without a format specified",
         ):
             assert Period(200701, freq=offsets.MonthEnd()) == Period(200701, freq="M")
 
@@ -292,7 +313,11 @@ def test_period_constructor_offsets(self):
         assert i2.year == 18695
 
         i1 = Period(datetime(2007, 1, 1), freq="M")
-        i2 = Period("2007-01", freq="M")
+        with tm.assert_produces_warning(
+            UserWarning,
+            match="Parsing datetime strings without a format specified",
+        ):
+            i2 = Period("200701", freq="M")
         assert i1 == i2
 
         i1 = Period(date(2007, 1, 1), freq="M")

pandas/tests/tslibs/test_array_to_datetime.py

@@ -166,11 +166,17 @@ def test_coerce_of_invalid_datetimes(errors):
     if errors == "ignore":
         # Without coercing, the presence of any invalid
         # dates prevents any values from being converted.
-        result, _ = tslib.array_to_datetime(**kwargs)
+        with tm.assert_produces_warning(
+            UserWarning, match="without a format specified"
+        ):
+            result, _ = tslib.array_to_datetime(**kwargs)
         tm.assert_numpy_array_equal(result, arr)
     else:  # coerce.
         # With coercing, the invalid dates becomes iNaT
-        result, _ = tslib.array_to_datetime(arr, errors="coerce")
+        with tm.assert_produces_warning(
+            UserWarning, match="without a format specified"
+        ):
+            result, _ = tslib.array_to_datetime(arr, errors="coerce")
         expected = ["2013-01-01T00:00:00.000000000", iNaT, iNaT]
 
         tm.assert_numpy_array_equal(result, np.array(expected, dtype="M8[ns]"))