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BUG: icol() should propegate fill_value for sparse data frames #2249 #2250

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BUG: icol() should propegate fill_value for sparse data frames #2249 #2250

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e26b196
TST: icol() should propegate fill_value for sparse data frames
Nov 14, 2012
e949f9c
BUG: icol() should propegate fill_value for sparse data frames #2249
Nov 14, 2012
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11 changes: 9 additions & 2 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1734,8 +1734,15 @@ def icol(self, i):
return self.ix[:, i]

values = self._data.iget(i)
return self._col_klass.from_array(values, index=self.index,
name=label)
if hasattr(self,'default_fill_value'):
s = self._col_klass.from_array(values, index=self.index,
name=label,
fill_value= self.default_fill_value)
else:
s = self._col_klass.from_array(values, index=self.index,
name=label)

return s

def _ixs(self, i, axis=0):
if axis == 0:
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4 changes: 2 additions & 2 deletions pandas/sparse/series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -147,11 +147,11 @@ def __new__(cls, data, index=None, sparse_index=None, kind='block',
return output

@classmethod
def from_array(cls, arr, index=None, name=None, copy=False):
def from_array(cls, arr, index=None, name=None, copy=False,fill_value=None):
"""
Simplified alternate constructor
"""
return SparseSeries(arr, index=index, name=name, copy=copy)
return SparseSeries(arr, index=index, name=name, copy=copy,fill_value=fill_value)

def __init__(self, data, index=None, sparse_index=None, kind='block',
fill_value=None, name=None, copy=False):
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5 changes: 5 additions & 0 deletions pandas/tests/test_frame.py
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Expand Up @@ -1327,6 +1327,11 @@ def test_irow_icol_duplicates(self):
xp = df.ix[:, [0]]
assert_frame_equal(rs, xp)

def test_icol_sparse_propegate_fill_value(self):
from pandas.sparse.api import SparseDataFrame
df=SparseDataFrame({'A' : [999,1]},default_fill_value=999)
self.assertTrue( len(df['A'].sp_values) == len(df.icol(0).sp_values))

def test_iget_value(self):
for i, row in enumerate(self.frame.index):
for j, col in enumerate(self.frame.columns):
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