Separate tests

Author: makbigc

pandas/tests/frame/test_quantile.py

@@ -12,14 +12,15 @@ class TestDataFrameQuantile:
     def test_quantile(self, datetime_frame):
         from numpy import percentile
 
-        q = datetime_frame.quantile(0.1, axis=0)
-        assert q['A'] == percentile(datetime_frame['A'], 10)
-        tm.assert_index_equal(q.index, datetime_frame.columns)
+        df = datetime_frame
+        q = df.quantile(0.1, axis=0)
+        assert q['A'] == percentile(df['A'], 10)
+        tm.assert_index_equal(q.index, df.columns)
 
-        q = datetime_frame.quantile(0.9, axis=1)
+        q = df.quantile(0.9, axis=1)
         assert (q['2000-01-17'] ==
-                percentile(datetime_frame.loc['2000-01-17'], 90))
-        tm.assert_index_equal(q.index, datetime_frame.index)
+                percentile(df.loc['2000-01-17'], 90))
+        tm.assert_index_equal(q.index, df.index)
 
         # test degenerate case
         q = DataFrame({'x': [], 'y': []}).quantile(0.1, axis=0)
@@ -96,20 +97,8 @@ def test_quantile_axis_parameter(self):
         with pytest.raises(ValueError, match=msg):
             df.quantile(0.1, axis="column")
 
-    def test_quantile_interpolation(self, datetime_frame, int_frame):
+    def test_quantile_interpolation(self):
         # see gh-10174
-        from numpy import percentile
-
-        # interpolation = linear (default case)
-        q = datetime_frame.quantile(0.1, axis=0, interpolation='linear')
-        assert q['A'] == percentile(datetime_frame['A'], 10)
-        q = int_frame.quantile(0.1)
-        assert q['A'] == percentile(int_frame['A'], 10)
-
-        # test with and without interpolation keyword
-        q1 = int_frame.quantile(0.1)
-        assert q1['A'] == np.percentile(int_frame['A'], 10)
-        tm.assert_series_equal(q, q1)
 
         # interpolation method other than default linear
         df = DataFrame({"A": [1, 2, 3], "B": [2, 3, 4]}, index=[1, 2, 3])
@@ -154,6 +143,27 @@ def test_quantile_interpolation(self, datetime_frame, int_frame):
                              index=[.25, .5], columns=['a', 'b', 'c'])
         assert_frame_equal(result, expected)
 
+    def test_quantile_interpolation_datetime(self, datetime_frame):
+        # see gh-10174
+
+        # interpolation = linear (default case)
+        df = datetime_frame
+        q = df.quantile(0.1, axis=0, interpolation='linear')
+        assert q['A'] == np.percentile(df['A'], 10)
+
+    def test_quantile_interpolation_int(self, int_frame):
+        # see gh-10174
+
+        df = int_frame
+        # interpolation = linear (default case)
+        q = df.quantile(0.1)
+        assert q['A'] == np.percentile(df['A'], 10)
+
+        # test with and without interpolation keyword
+        q1 = df.quantile(0.1)
+        assert q1['A'] == np.percentile(df['A'], 10)
+        tm.assert_series_equal(q, q1)
+
     def test_quantile_multi(self):
         df = DataFrame([[1, 1, 1], [2, 2, 2], [3, 3, 3]],
                        columns=['a', 'b', 'c'])