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BUG: Duplicate indexes with and empty DataFrame.from_records will return a correct frame (GH3562) #3564

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Merged
merged 1 commit into from
May 10, 2013
Merged

BUG: Duplicate indexes with and empty DataFrame.from_records will return a correct frame (GH3562) #3564

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2 changes: 2 additions & 0 deletions RELEASE.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -77,6 +77,7 @@ pandas 0.11.1
- ``.loc`` was not raising when passed an integer list (GH3449_)
- Unordered time series selection was misbehaving when using label slicing (GH3448_)
- Duplicate indexes with getitem will return items in the correct order (GH3455_, GH3457_)
- Duplicate indexes with and empty DataFrame.from_records will return a correct frame (GH3562_)
- Fix sorting in a frame with a list of columns which contains datetime64[ns] dtypes (GH3461_)
- DataFrames fetched via FRED now handle '.' as a NaN. (GH3469_)
- Fix regression in a DataFrame apply with axis=1, objects were not being converted back
Expand Down Expand Up @@ -137,6 +138,7 @@ pandas 0.11.1
.. _GH3495: https://github.com/pydata/pandas/issues/3495
.. _GH3492: https://github.com/pydata/pandas/issues/3492
.. _GH3552: https://github.com/pydata/pandas/issues/3552
.. _GH3562: https://github.com/pydata/pandas/issues/3562
.. _GH3493: https://github.com/pydata/pandas/issues/3493


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3 changes: 2 additions & 1 deletion pandas/core/internals.py
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Expand Up @@ -1960,7 +1960,8 @@ def form_blocks(arrays, names, axes):
items = axes[0]

if len(arrays) < len(items):
extra_items = items - Index(names)
nn = set(names)
extra_items = Index([ i for i in items if i not in nn ])
else:
extra_items = []

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10 changes: 10 additions & 0 deletions pandas/tests/test_frame.py
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Expand Up @@ -3518,6 +3518,16 @@ def test_from_records_misc_brokenness(self):
results = df2_obj.get_dtype_counts()
expected = Series({ 'datetime64[ns]' : 1, 'int64' : 1 })

def test_from_records_empty(self):
# 3562
result = DataFrame.from_records([], columns=['a','b','c'])
expected = DataFrame(columns=['a','b','c'])
assert_frame_equal(result, expected)

result = DataFrame.from_records([], columns=['a','b','b'])
expected = DataFrame(columns=['a','b','b'])
assert_frame_equal(result, expected)

def test_to_records_floats(self):
df = DataFrame(np.random.rand(10, 10))
df.to_records()
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