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BUG: Preserve index order when constructing DataFrame from dict #26113

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BUG: Preserve index order when constructing DataFrame from dict #26113

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bchu Apr 13, 2019
cb57553
Fix single index case
bchu Apr 15, 2019
b0e46eb
Fix tests
bchu Apr 15, 2019
a972fb7
Fix alter axes test
bchu Apr 15, 2019
91b9a38
Fix test
bchu Apr 16, 2019
d419ee4
Fix test
bchu Apr 16, 2019
b54592f
Lint
bchu Apr 16, 2019
0aed1ca
Whitespace
bchu Apr 16, 2019
3201e19
Whats new
bchu Apr 16, 2019
bbbeec7
Backwards compat
bchu Apr 16, 2019
f9d82eb
Fix doctest
bchu Apr 17, 2019
adff27b
Tweak whats new
bchu Apr 17, 2019
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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v0.25.0.rst
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Expand Up @@ -305,7 +305,7 @@ Conversion
^^^^^^^^^^

- Bug in :func:`DataFrame.astype()` when passing a dict of columns and types the `errors` parameter was ignored. (:issue:`25905`)
-
- Bug in :class:`DataFrame` construction from dict, where the index would be sorted instead of using dict insertion order. (:issue:`24859`)
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pls make clear of how this affects 3.5 and 3.6+

let's move this to the other api changes section as its not a bug rather an api change.

-

Strings
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10 changes: 5 additions & 5 deletions pandas/core/frame.py
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Expand Up @@ -6304,11 +6304,11 @@ def _gotitem(self,

Different aggregations per column.

>>> df.agg({'A' : ['sum', 'min'], 'B' : ['min', 'max']})
A B
max NaN 8.0
min 1.0 2.0
sum 12.0 NaN
>>> df.agg({'A' : ['max', 'min'], 'B' : ['min', 'sum']})
A B
max 7.0 NaN
min 1.0 2.0
sum NaN 15.0

Aggregate over the columns.

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3 changes: 2 additions & 1 deletion pandas/core/indexes/api.py
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Expand Up @@ -146,7 +146,8 @@ def _union_indexes(indexes, sort=True):
if len(indexes) == 1:
result = indexes[0]
if isinstance(result, list):
result = Index(sorted(result))
result = sorted(result) if sort else result
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Can this branch be removed altogether or does that break 35 compatibility?

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Yeah, it breaks python 3.5 compat.

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Why not just move the compat check from the construction module to here then? Would be simpler

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It would be a little more complicated here since we would have to do another compat check in the len(indexes) > 1 case

result = Index(result)
return result

indexes, kind = _sanitize_and_check(indexes)
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4 changes: 2 additions & 2 deletions pandas/core/internals/construction.py
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Expand Up @@ -9,7 +9,7 @@

from pandas._libs import lib
from pandas._libs.tslibs import IncompatibleFrequency
from pandas.compat import lmap, lrange, raise_with_traceback
from pandas.compat import PY36, lmap, lrange, raise_with_traceback

from pandas.core.dtypes.cast import (
construct_1d_arraylike_from_scalar, construct_1d_ndarray_preserving_na,
Expand Down Expand Up @@ -301,7 +301,7 @@ def extract_index(data):
' an index')

if have_series or have_dicts:
index = _union_indexes(indexes)
index = _union_indexes(indexes, sort=not PY36)
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this needs a comment on why here


if have_raw_arrays:
lengths = list(set(raw_lengths))
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3 changes: 1 addition & 2 deletions pandas/tests/frame/test_alter_axes.py
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Expand Up @@ -620,10 +620,9 @@ def test_rename(self, float_frame):

# index
data = {
'A': {'foo': 0, 'bar': 1}
'A': {'bar': 0, 'foo': 1}
}

# gets sorted alphabetical
df = DataFrame(data)
renamed = df.rename(index={'foo': 'bar', 'bar': 'foo'})
tm.assert_index_equal(renamed.index, Index(['foo', 'bar']))
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8 changes: 5 additions & 3 deletions pandas/tests/frame/test_constructors.py
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Expand Up @@ -479,7 +479,8 @@ def test_constructor_subclass_dict(self):
dct.update(v.to_dict())
data[k] = dct
frame = DataFrame(data)
tm.assert_frame_equal(self.frame.sort_index(), frame)
old_frame = self.frame if PY36 else self.frame.sort_index()
tm.assert_frame_equal(old_frame, frame)

def test_constructor_dict_block(self):
expected = np.array([[4., 3., 2., 1.]])
Expand Down Expand Up @@ -1110,7 +1111,8 @@ def test_constructor_list_of_series(self):

sdict = OrderedDict(zip(['x', 'Unnamed 0'], data))
expected = DataFrame.from_dict(sdict, orient='index')
tm.assert_frame_equal(result.sort_index(), expected)
result = result if PY36 else result.sort_index()
tm.assert_frame_equal(result, expected)

# none named
data = [OrderedDict([['a', 1.5], ['b', 3], ['c', 4], ['d', 6]]),
Expand Down Expand Up @@ -1245,7 +1247,7 @@ def test_constructor_list_of_namedtuples(self):
def test_constructor_orient(self):
data_dict = self.mixed_frame.T._series
recons = DataFrame.from_dict(data_dict, orient='index')
expected = self.mixed_frame.sort_index()
expected = self.mixed_frame if PY36 else self.mixed_frame.sort_index()
tm.assert_frame_equal(recons, expected)

# dict of sequence
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2 changes: 1 addition & 1 deletion pandas/tests/indexing/multiindex/test_setitem.py
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Expand Up @@ -140,8 +140,8 @@ def test_multiindex_setitem(self):
# http://stackoverflow.com/questions/24572040/pandas-access-the-level-of-multiindex-for-inplace-operation
df_orig = DataFrame.from_dict({'price': {
('DE', 'Coal', 'Stock'): 2,
('DE', 'Gas', 'Stock'): 4,
('DE', 'Elec', 'Demand'): 1,
('DE', 'Gas', 'Stock'): 4,
('FR', 'Gas', 'Stock'): 5,
('FR', 'Solar', 'SupIm'): 0,
('FR', 'Wind', 'SupIm'): 0
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2 changes: 1 addition & 1 deletion pandas/tests/reshape/test_concat.py
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Expand Up @@ -1588,7 +1588,7 @@ def test_concat_series_axis1(self, sort=sort):
s = Series(randn(3), index=['c', 'a', 'b'], name='A')
s2 = Series(randn(4), index=['d', 'a', 'b', 'c'], name='B')
result = concat([s, s2], axis=1, sort=sort)
expected = DataFrame({'A': s, 'B': s2})
expected = DataFrame({'A': s, 'B': s2}).sort_index()
assert_frame_equal(result, expected)

def test_concat_series_axis1_names_applied(self):
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