Clean up tests.

Author: tv3141

pandas/tests/groupby/test_counting.py

@@ -4,7 +4,7 @@
 import pytest
 
 from pandas import (DataFrame, Index, MultiIndex, Period, Series, Timedelta,
-    Timestamp)
+                    Timestamp)
 import pandas._testing as tm
 
 
@@ -222,54 +222,20 @@ def test_count_with_only_nans_in_first_group(self):
         expected = Series([], index=mi, dtype=np.int64, name="C")
         tm.assert_series_equal(result, expected, check_index_type=False)
 
-    #def test_count_groupby_index_with_nan_in_data(self):
-    #    # https://github.com/pandas-dev/pandas/issues/21824
-    #    df = DataFrame({"Person": ["John", "Myla", "John", "John", "Myla"],
-    #                       "Age": [24., np.nan, 21., 33, 26],
-    #                       "Single": [False, True, True, True, False]})
-
-    #    res = df.set_index(["Person", "Single"]).count(level="Person")
-    #    expected = DataFrame(index=Index(["John", "Myla"], name="Person"),
-    #                         data={"Age": [2, 1]})
-
     def test_count_groupby_index_with_nan_in_index(self):
         # https://github.com/pandas-dev/pandas/issues/21824
         df = DataFrame({"Person": ["John", "Myla", None, "John", "Myla"],
-                           "Age": [24., 5, 21., 33, 26],
-                           "Single": [False, True, True, True, False]})
+                        "Age": [24., 5, 21., 33, 26],
+                        "Single": [False, True, True, True, False]})
 
         res = df.set_index(["Person", "Single"]).count(level="Person")
         expected = DataFrame(index=Index(["John", "Myla"], name="Person"),
                              data={"Age": [2, 2]})
 
-    #def test_count_groupby_index_with_nan_in_data_and_in_index(self):
-    #    # https://github.com/pandas-dev/pandas/issues/21824
-    #    df = DataFrame({"Person": ["John", "Myla", None, "John", "Myla"],
-    #                       "Age": [24., np.nan, 21., 33, 26],
-    #                       "Single": [False, True, True, True, False]})
-
-    #    res = df.set_index(["Person", "Single"]).count(level="Person")
-    #    expected = DataFrame(index=Index(["John", "Myla"], name="Person"),
-    #                         data={"Age": [2, 1]})
-
-
     def test_count_groupby_column_with_nan_in_groupby_column(self):
+        # https://github.com/pandas-dev/pandas/issues/32841
         df = DataFrame({"A": [1, 1, 1, 1, 1], "B": [5, 4, np.NaN, 3, 0]})
         res = df.groupby(["B"]).count()
         expected = DataFrame(index=Index([0.0, 3.0, 4.0, 5.0], name="B"),
                              data={"A": [1, 1, 1, 1]})
         tm.assert_frame_equal(expected, res)
-
-    #def test_count_groupby_column_with_nan_in_data(self):
-    #    df = DataFrame({"A": [1, np.NaN, 1, 1, 1], "B": [5, 4., 2, 3, 0]})
-    #    res = df.groupby(["B"]).count()
-    #    expected = DataFrame(index=Index([0.0, 2.0, 3.0, 4.0, 5.0], name="B"),
-    #                         data={"A": [1, 1, 1, 0, 1]})
-    #    tm.assert_frame_equal(expected, res)
-
-    #def test_count_groupby_column_with_nan_in_data_and_in_groupby_column(self):
-    #    df = DataFrame({"A": [1, np.NaN, 1, 1, 1], "B": [5, 4, np.NaN, 3, 0]})
-    #    res = df.groupby(["B"]).count()
-    #    expected = DataFrame(index=Index([0.0, 3.0, 4.0, 5.0], name="B"),
-    #                         data={"A": [1, 1, 0, 1]})
-    #    tm.assert_frame_equal(expected, res)