clarify whatsnew and parametrize tests

Author: reidy-p

doc/source/whatsnew/v0.23.0.txt

@@ -375,7 +375,7 @@ Conversion
 - Bug in :class:`TimedeltaIndex` where division by a ``Series`` would return a ``TimedeltaIndex`` instead of a ``Series`` (issue:`19042`)
 - Bug in :class:`Series` with ``dtype='timedelta64[ns]`` where addition or subtraction of ``TimedeltaIndex`` could return a ``Series`` with an incorrect name (issue:`19043`)
 - Fixed bug where comparing :class:`DatetimeIndex` failed to raise ``TypeError`` when attempting to compare timezone-aware and timezone-naive datetimelike objects (:issue:`18162`)
-- Bug in :class:`DatetimeIndex` where the repr was not showing the time values for the end of the day (:issue:`19030`)
+- Bug in :class:`DatetimeIndex` where the repr was not showing high-precision time values at the end of a day (e.g., 23:59:59.999999999) (:issue:`19030`)
 
 
 Indexing

pandas/tests/io/formats/test_format.py

@@ -883,19 +883,29 @@ def test_datetimelike_frame(self):
                         '[10 rows x 2 columns]')
             assert repr(df) == expected
 
-    def test_datetimeindex_highprecision(self):
+
+    @pytest.mark.parametrize('start_date', [
+     '2017-01-01 23:59:59.999999999',
+     '2017-01-01 23:59:59.99999999',
+     '2017-01-01 23:59:59.9999999',
+     '2017-01-01 23:59:59.999999',
+     '2017-01-01 23:59:59.99999',
+     '2017-01-01 23:59:59.9999',
+    ])
+    def test_datetimeindex_highprecision(self, start_date):
         # GH19030
-        # Check that time values for the end of day are included in repr
-        df = DataFrame({'A': date_range(start='2017-01-01 23:59:59.999999999',
+        # Check that high-precision time values for the end of day are
+        # included in repr for DatetimeIndex
+        df = DataFrame({'A': date_range(start=start_date,
                                         freq='D', periods=5)})
         result = str(df)
-        assert "23:59:59.999999999" in result
+        assert start_date in result
 
-        dti = date_range(start='2017-01-01 23:59:59.999999999',
+        dti = date_range(start=start_date,
                          freq='D', periods=5)
         df = DataFrame({'A': range(5)}, index=dti)
         result = str(df.index)
-        assert "23:59:59.999999999" in result
+        assert start_date in result
 
     def test_nonunicode_nonascii_alignment(self):
         df = DataFrame([["aa\xc3\xa4\xc3\xa4", 1], ["bbbb", 2]])
@@ -1928,19 +1938,26 @@ def test_datetimeindex(self):
         result = str(s2.index)
         assert 'NaT' in result
 
-    def test_datetimeindex_highprecision(self):
+    @pytest.mark.parametrize('start_date', [
+     '2017-01-01 23:59:59.999999999',
+     '2017-01-01 23:59:59.99999999',
+     '2017-01-01 23:59:59.9999999',
+     '2017-01-01 23:59:59.999999',
+     '2017-01-01 23:59:59.99999',
+     '2017-01-01 23:59:59.9999',
+    ])
+    def test_datetimeindex_highprecision(self, start_date):
         # GH19030
-        # Check that time values for the end of day are included in repr
-        s1 = Series(date_range(start='2017-01-01 23:59:59.999999999',
-                               freq='D', periods=5))
+        # Check that high-precision time values for the end of day are
+        # included in repr for DatetimeIndex
+        s1 = Series(date_range(start=start_date, freq='D', periods=5))
         result = str(s1)
-        assert "23:59:59.999999999" in result
+        assert start_date in result
 
-        dti = date_range(start='2017-01-01 23:59:59.999999999', freq='D',
-                         periods=5)
+        dti = date_range(start=start_date, freq='D', periods=5)
         s2 = Series(3, index=dti)
         result = str(s2.index)
-        assert "23:59:59.999999999" in result
+        assert start_date in result
 
     def test_timedelta64(self):