TST: tests for needs-test issues (#30222)

Author: jbrockmendel

pandas/tests/frame/test_axis_select_reindex.py

@@ -929,6 +929,14 @@ def test_filter_corner(self):
         result = empty.filter(like="foo")
         tm.assert_frame_equal(result, empty)
 
+    def test_filter_regex_non_string(self):
+        # GH#5798 trying to filter on non-string columns should drop,
+        #  not raise
+        df = pd.DataFrame(np.random.random((3, 2)), columns=["STRING", 123])
+        result = df.filter(regex="STRING")
+        expected = df[["STRING"]]
+        tm.assert_frame_equal(result, expected)
+
     def test_take(self, float_frame):
         # homogeneous
         order = [3, 1, 2, 0]

pandas/tests/frame/test_constructors.py

@@ -1726,10 +1726,16 @@ def test_constructor_with_datetimes(self):
         tm.assert_frame_equal(df, expected)
 
     def test_constructor_datetimes_with_nulls(self):
-        # gh-15869
+        # gh-15869, GH#11220
         for arr in [
             np.array([None, None, None, None, datetime.now(), None]),
             np.array([None, None, datetime.now(), None]),
+            [[np.datetime64("NaT")], [None]],
+            [[np.datetime64("NaT")], [pd.NaT]],
+            [[None], [np.datetime64("NaT")]],
+            [[None], [pd.NaT]],
+            [[pd.NaT], [np.datetime64("NaT")]],
+            [[pd.NaT], [None]],
         ]:
             result = DataFrame(arr).dtypes
             expected = Series([np.dtype("datetime64[ns]")])

pandas/tests/frame/test_quantile.py

@@ -7,6 +7,16 @@
 
 
 class TestDataFrameQuantile:
+    def test_quantile_sparse(self):
+        # GH#17198
+        s = pd.Series(pd.SparseArray([1, 2]))
+        s1 = pd.Series(pd.SparseArray([3, 4]))
+        df = pd.DataFrame({0: s, 1: s1})
+        result = df.quantile()
+
+        expected = pd.Series([1.5, 3.5], name=0.5)
+        tm.assert_series_equal(result, expected)
+
     def test_quantile(self, datetime_frame):
         from numpy import percentile
 

pandas/tests/frame/test_timeseries.py

@@ -609,6 +609,14 @@ def test_first_last_valid(
         assert expected_first == df.first_valid_index()
         assert expected_last == df.last_valid_index()
 
+    @pytest.mark.parametrize("klass", [Series, DataFrame])
+    def test_first_valid_index_all_nan(self, klass):
+        # GH#9752 Series/DataFrame should both return None, not raise
+        obj = klass([np.nan])
+
+        assert obj.first_valid_index() is None
+        assert obj.iloc[:0].first_valid_index() is None
+
     def test_first_subset(self):
         ts = tm.makeTimeDataFrame(freq="12h")
         result = ts.first("10d")

pandas/tests/indexes/multi/test_constructor.py

@@ -577,6 +577,17 @@ def test_from_product_respects_none_names():
     tm.assert_index_equal(result, expected)
 
 
+def test_from_product_readonly():
+    # GH#15286 passing read-only array to from_product
+    a = np.array(range(3))
+    b = ["a", "b"]
+    expected = MultiIndex.from_product([a, b])
+
+    a.setflags(write=False)
+    result = MultiIndex.from_product([a, b])
+    tm.assert_index_equal(result, expected)
+
+
 def test_create_index_existing_name(idx):
 
     # GH11193, when an existing index is passed, and a new name is not

pandas/tests/io/formats/test_format.py

@@ -1106,6 +1106,15 @@ def test_truncate_with_different_dtypes(self):
             assert "None" in result
             assert "NaN" not in result
 
+    def test_truncate_with_different_dtypes_multiindex(self):
+        # GH#13000
+        df = DataFrame({"Vals": range(100)})
+        frame = pd.concat([df], keys=["Sweep"], names=["Sweep", "Index"])
+        result = repr(frame)
+
+        result2 = repr(frame.iloc[:5])
+        assert result.startswith(result2)
+
     def test_datetimelike_frame(self):
 
         # GH 12211

pandas/tests/series/test_missing.py

@@ -473,6 +473,13 @@ def test_fillna_consistency(self):
         s2[1] = "foo"
         tm.assert_series_equal(s2, expected)
 
+    def test_where_sparse(self):
+        # GH#17198 make sure we dont get an AttributeError for sp_index
+        ser = pd.Series(pd.SparseArray([1, 2]))
+        result = ser.where(ser >= 2, 0)
+        expected = pd.Series(pd.SparseArray([0, 2]))
+        tm.assert_series_equal(result, expected)
+
     def test_datetime64tz_fillna_round_issue(self):
         # GH 14872
 

pandas/tests/window/test_rolling.py

@@ -418,3 +418,11 @@ def test_rolling_window_as_string():
 
     expected = Series(expData, index=Index(days, name="DateCol"), name="metric")
     tm.assert_series_equal(result, expected)
+
+
+def test_min_periods1():
+    # GH#6795
+    df = pd.DataFrame([0, 1, 2, 1, 0], columns=["a"])
+    result = df["a"].rolling(3, center=True, min_periods=1).max()
+    expected = pd.Series([1.0, 2.0, 2.0, 2.0, 1.0], name="a")
+    tm.assert_series_equal(result, expected)