updates for PR comments

pandas/tests/reshape/merge/test_merge.py

@@ -51,7 +51,7 @@ def get_series():
  ]
 
 
-def get_series_nan():
+def get_series_na():
  return [
  pd.Series([np.nan], dtype='Int64'),
  pd.Series([np.nan], dtype='float'),
@@ -61,17 +61,21 @@ def get_series_nan():
 
 
 @pytest.fixture(params=get_series(), ids=lambda x: x.dtype.name)
-def value_col(request):
+def series_of_dtype(request):
+ # A parametrized fixture returning a variety of Series of different dtypes
  return request.param
 
 
 @pytest.fixture(params=get_series(), ids=lambda x: x.dtype.name)
-def value_col2(request):
+def series_of_dtype2(request):
+ # A duplicate of the series_of_dtype fixture, so that it
+ # can be used twice by a single function
  return request.param
 
 
-@pytest.fixture(params=get_series_nan(), ids=lambda x: x.dtype.name)
-def value_col_nan(request):
+@pytest.fixture(params=get_series_na(), ids=lambda x: x.dtype.name)
+def series_of_dtype_all_na(request):
+ # A parametrized fixture returning a variety of Series with all NA values
  return request.param
 
 
@@ -464,32 +468,35 @@ def check2(exp, kwarg):
  check1(exp_in, kwarg)
  check2(exp_out, kwarg)
 
- def test_merge_empty_frame(self, value_col, value_col2):
+ def test_merge_empty_frame(self, series_of_dtype, series_of_dtype2):
  # GH 25183
- df = pd.DataFrame({'a': value_col, 'b': value_col2},
- columns=['a', 'b'])
+ df = pd.DataFrame({'key': series_of_dtype, 'value': series_of_dtype2},
+ columns=['key', 'value'])
  df_empty = df[:0]
- exp = pd.DataFrame({
- 'b_x': pd.Series(dtype=df.dtypes['b']),
- 'a': pd.Series(dtype=df.dtypes['a']),
- 'b_y': pd.Series(dtype=df.dtypes['b']),
- }, columns=['b_x', 'a', 'b_y'])
- act = df_empty.merge(df, on='a')
- assert_frame_equal(act, exp)
-
- def test_merge_all_na_column(self, value_col, value_col_nan):
+ expected = pd.DataFrame({
+ 'value_x': pd.Series(dtype=df.dtypes['value']),
+ 'key': pd.Series(dtype=df.dtypes['key']),
+ 'value_y': pd.Series(dtype=df.dtypes['value']),
+ }, columns=['value_x', 'key', 'value_y'])
+ actual = df_empty.merge(df, on='key')
+ assert_frame_equal(actual, expected)
+
+ def test_merge_all_na_column(self, series_of_dtype,
+ series_of_dtype_all_na):
  # GH 25183
  df_left = pd.DataFrame(
- {'a': value_col, 'b': value_col_nan}, columns=['a', 'b'])
+ {'key': series_of_dtype, 'value': series_of_dtype_all_na},
+ columns=['key', 'value'])
  df_right = pd.DataFrame(
- {'a': value_col, 'b': value_col_nan}, columns=['a', 'b'])
- exp = pd.DataFrame({
- 'a': value_col,
- 'b_x': value_col_nan,
- 'b_y': value_col_nan,
- }, columns=['a', 'b_x', 'b_y'])
- act = df_left.merge(df_right, on='a')
- assert_frame_equal(act, exp)
+ {'key': series_of_dtype, 'value': series_of_dtype_all_na},
+ columns=['key', 'value'])
+ expected = pd.DataFrame({
+ 'key': series_of_dtype,
+ 'value_x': series_of_dtype_all_na,
+ 'value_y': series_of_dtype_all_na,
+ }, columns=['key', 'value_x', 'value_y'])
+ actual = df_left.merge(df_right, on='key')
+ assert_frame_equal(actual, expected)
 
  def test_merge_nosort(self):
  # #2098, anything to do?