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BUG-16807-1 SparseFrame fills with default_fill_value if data is None #24842

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Merged
merged 6 commits into from
Mar 3, 2019
Merged

BUG-16807-1 SparseFrame fills with default_fill_value if data is None #24842

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BUG-16807-1 SparseFrame fills with default_fill_value if data is None
JustinZhengBC Jan 19, 2019
d93806f
BUG-16807 add tests
JustinZhengBC Jan 22, 2019
8fdf316
fix typo
JustinZhengBC Jan 22, 2019
cee871f
Merge branch 'master' into BUG-16807-1
JustinZhengBC Mar 1, 2019
cc01978
BUG-16807 move whatsnew note
JustinZhengBC Mar 1, 2019
fe3eebd
move whatsnew note
JustinZhengBC Mar 3, 2019
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.24.0.rst
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Expand Up @@ -1835,6 +1835,7 @@ Sparse
- Bug in :meth:`SparseArray.nonzero` and :meth:`SparseDataFrame.dropna` returning shifted/incorrect results (:issue:`21172`)
- Bug in :meth:`DataFrame.apply` where dtypes would lose sparseness (:issue:`23744`)
- Bug in :func:`concat` when concatenating a list of :class:`Series` with all-sparse values changing the ``fill_value`` and converting to a dense Series (:issue:`24371`)
- Bug in :class:`SparseFrame` constructor where passing ``None`` as the data would cause ``default_fill_value`` to be ignored (:issue:`16807`)
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@WillAyd WillAyd Feb 28, 2019 •
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Move to 0.24.2


Style
^^^^^
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4 changes: 2 additions & 2 deletions pandas/core/sparse/frame.py
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Expand Up @@ -124,8 +124,8 @@ def __init__(self, data=None, index=None, columns=None, default_kind=None,
columns = Index([])
else:
for c in columns:
data[c] = SparseArray(np.nan, index=index,
kind=self._default_kind,
data[c] = SparseArray(self._default_fill_value,
index=index, kind=self._default_kind,
fill_value=self._default_fill_value)
mgr = to_manager(data, columns, index)
if dtype is not None:
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8 changes: 8 additions & 0 deletions pandas/tests/sparse/frame/test_frame.py
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Expand Up @@ -1246,6 +1246,14 @@ def test_notna(self):
'B': [True, False, True, True, False]})
tm.assert_frame_equal(res.to_dense(), exp)

def test_default_fill_value_with_no_data(self):
# GH 16807
expected = pd.SparseDataFrame([[1.0, 1.0], [1.0, 1.0]],
columns=list('ab'), index=range(2))
result = pd.SparseDataFrame(columns=list('ab'), index=range(2),
default_fill_value=1.0)
tm.assert_frame_equal(expected, result)


class TestSparseDataFrameArithmetic(object):

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