Let initialisation from dicts use insertion order for py>=36, part I (#19830)

Author: topper-123

pandas/tests/frame/test_apply.py

@@ -646,7 +646,7 @@ def test_infer_output_shape_columns(self):
  'datetime': [pd.Timestamp('2017-11-29 03:30:00'),
  pd.Timestamp('2017-11-29 03:45:00')]})
  result = df.apply(lambda row: (row.number, row.string), axis=1)
- expected = Series([t[2:] for t in df.itertuples()])
+ expected = Series([(t.number, t.string) for t in df.itertuples()])
  assert_series_equal(result, expected)
 
  def test_infer_output_shape_listlike_columns(self):

pandas/tests/frame/test_block_internals.py

@@ -405,8 +405,8 @@ def test_get_numeric_data(self):
  result = df.get_dtype_counts()
  expected = Series({'int64': 1, 'float64': 1,
  datetime64name: 1, objectname: 1})
- result.sort_index()
- expected.sort_index()
+ result = result.sort_index()
+ expected = expected.sort_index()
  assert_series_equal(result, expected)
 
  df = DataFrame({'a': 1., 'b': 2, 'c': 'foo',

pandas/tests/frame/test_constructors.py

@@ -1381,9 +1381,8 @@ def test_constructor_with_datetimes(self):
  expected['float64'] = 1
  expected[floatname] = 1
 
- result.sort_index()
- expected = Series(expected)
- expected.sort_index()
+ result = result.sort_index()
+ expected = Series(expected).sort_index()
  tm.assert_series_equal(result, expected)
 
  # check with ndarray construction ndim>0
@@ -1392,7 +1391,7 @@ def test_constructor_with_datetimes(self):
  intname: np.array([1] * 10, dtype=intname)},
  index=np.arange(10))
  result = df.get_dtype_counts()
- result.sort_index()
+ result = result.sort_index()
  tm.assert_series_equal(result, expected)
 
  # GH 2809
@@ -1403,8 +1402,8 @@ def test_constructor_with_datetimes(self):
  df = DataFrame({'datetime_s': datetime_s})
  result = df.get_dtype_counts()
  expected = Series({datetime64name: 1})
- result.sort_index()
- expected.sort_index()
+ result = result.sort_index()
+ expected = expected.sort_index()
  tm.assert_series_equal(result, expected)
 
  # GH 2810
@@ -1414,8 +1413,8 @@ def test_constructor_with_datetimes(self):
  df = DataFrame({'datetimes': datetimes, 'dates': dates})
  result = df.get_dtype_counts()
  expected = Series({datetime64name: 1, objectname: 1})
- result.sort_index()
- expected.sort_index()
+ result = result.sort_index()
+ expected = expected.sort_index()
  tm.assert_series_equal(result, expected)
 
  # GH 7594
@@ -1538,8 +1537,8 @@ def test_constructor_for_list_with_dtypes(self):
  result = df.get_dtype_counts()
  expected = Series(
  {'int64': 1, 'float64': 2, datetime64name: 1, objectname: 1})
- result.sort_index()
- expected.sort_index()
+ result = result.sort_index()
+ expected = expected.sort_index()
  tm.assert_series_equal(result, expected)
 
  def test_constructor_frame_copy(self):
@@ -1851,7 +1850,7 @@ def test_from_records_misc_brokenness(self):
  rows.append([datetime(2010, 1, 1), 1])
  rows.append([datetime(2010, 1, 2), 1])
  df2_obj = DataFrame.from_records(rows, columns=['date', 'test'])
- results = df2_obj.get_dtype_counts()
+ results = df2_obj.get_dtype_counts().sort_index()
  expected = Series({'datetime64[ns]': 1, 'int64': 1})
  tm.assert_series_equal(results, expected)
 

pandas/tests/frame/test_dtypes.py

@@ -725,9 +725,9 @@ def test_timedeltas(self):
  df = DataFrame(dict(A=Series(date_range('2012-1-1', periods=3,
  freq='D')),
  B=Series([timedelta(days=i) for i in range(3)])))
- result = df.get_dtype_counts().sort_values()
+ result = df.get_dtype_counts().sort_index()
  expected = Series(
- {'datetime64[ns]': 1, 'timedelta64[ns]': 1}).sort_values()
+ {'datetime64[ns]': 1, 'timedelta64[ns]': 1}).sort_index()
  assert_series_equal(result, expected)
 
  df['C'] = df['A'] + df['B']

pandas/tests/frame/test_indexing.py

@@ -2430,8 +2430,8 @@ def _check_get(df, cond, check_dtypes=True):
 
  # upcasting case (GH # 2794)
  df = DataFrame(dict((c, Series([1] * 3, dtype=c))
- for c in ['int64', 'int32',
- 'float32', 'float64']))
+ for c in ['float32', 'float64',
+ 'int32', 'int64']))
  df.iloc[1, :] = 0
  result = df.where(df >= 0).get_dtype_counts()
 

pandas/tests/frame/test_mutate_columns.py

@@ -166,17 +166,17 @@ def test_insert(self):
 
  # new item
  df['x'] = df['a'].astype('float32')
- result = Series(dict(float64=5, float32=1))
- assert (df.get_dtype_counts() == result).all()
+ result = Series(dict(float32=1, float64=5))
+ assert (df.get_dtype_counts().sort_index() == result).all()
 
  # replacing current (in different block)
  df['a'] = df['a'].astype('float32')
- result = Series(dict(float64=4, float32=2))
- assert (df.get_dtype_counts() == result).all()
+ result = Series(dict(float32=2, float64=4))
+ assert (df.get_dtype_counts().sort_index() == result).all()
 
  df['y'] = df['a'].astype('int32')
- result = Series(dict(float64=4, float32=2, int32=1))
- assert (df.get_dtype_counts() == result).all()
+ result = Series(dict(float32=2, float64=4, int32=1))
+ assert (df.get_dtype_counts().sort_index() == result).all()
 
  with tm.assert_raises_regex(ValueError, 'already exists'):
  df.insert(1, 'a', df['b'])

pandas/tests/frame/test_nonunique_indexes.py

@@ -155,14 +155,14 @@ def check(result, expected=None):
 
  # rename, GH 4403
  df4 = DataFrame(
- {'TClose': [22.02],
- 'RT': [0.0454],
+ {'RT': [0.0454],
+ 'TClose': [22.02],
  'TExg': [0.0422]},
  index=MultiIndex.from_tuples([(600809, 20130331)],
  names=['STK_ID', 'RPT_Date']))
 
- df5 = DataFrame({'STK_ID': [600809] * 3,
- 'RPT_Date': [20120930, 20121231, 20130331],
+ df5 = DataFrame({'RPT_Date': [20120930, 20121231, 20130331],
+ 'STK_ID': [600809] * 3,
  'STK_Name': [u('饡驦'), u('饡驦'), u('饡驦')],
  'TClose': [38.05, 41.66, 30.01]},
  index=MultiIndex.from_tuples(

pandas/tests/frame/test_reshape.py

@@ -719,9 +719,10 @@ def verify(df):
  assert_frame_equal(left, right)
 
  # GH7401
- df = pd.DataFrame({'A': list('aaaaabbbbb'), 'C': np.arange(10),
+ df = pd.DataFrame({'A': list('aaaaabbbbb'),
  'B': (date_range('2012-01-01', periods=5)
- .tolist() * 2)})
+ .tolist() * 2),
+ 'C': np.arange(10)})
 
  df.iloc[3, 1] = np.NaN
  left = df.set_index(['A', 'B']).unstack()

pandas/tests/frame/test_to_csv.py

@@ -1054,10 +1054,10 @@ def test_to_csv_with_dst_transitions(self):
 
  def test_to_csv_quoting(self):
  df = DataFrame({
- 'c_string': ['a', 'b,c'],
- 'c_int': [42, np.nan],
- 'c_float': [1.0, 3.2],
  'c_bool': [True, False],
+ 'c_float': [1.0, 3.2],
+ 'c_int': [42, np.nan],
+ 'c_string': ['a', 'b,c'],
  })
 
  expected = """\