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BUG/TST: test fixes for windows compat #4123

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Merged
merged 1 commit into from
Jul 4, 2013
+12 −7
Merged

BUG/TST: test fixes for windows compat #4123

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5 changes: 4 additions & 1 deletion pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2206,7 +2206,10 @@ def _sanitize_column(self, key, value):
'length of index')

if not isinstance(value, np.ndarray):
value = com._asarray_tuplesafe(value)
if isinstance(value, list) and len(value) > 0:
value = com._possibly_convert_platform(value)
else:
value = com._asarray_tuplesafe(value)
elif isinstance(value, PeriodIndex):
value = value.asobject
elif value.ndim == 2:
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14 changes: 8 additions & 6 deletions pandas/tests/test_frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4891,14 +4891,17 @@ def make_dtnat_arr(n,nnat=None):
s[-i] = NaT
s[i] = NaT
return s

# N=35000
s1=make_dtnat_arr(chunksize+5)
s2=make_dtnat_arr(chunksize+5,0)

# s3=make_dtnat_arr(chunksize+5,0)
df=DataFrame(dict(a=s1,b=s2))
df.to_csv('/tmp/1.csv',chunksize=chunksize)
recons = DataFrame.from_csv('/tmp/1.csv').convert_objects('coerce')
assert_frame_equal(df, recons,check_names=False,check_less_precise=True)
with ensure_clean('1.csv') as path:
df=DataFrame(dict(a=s1,b=s2))
df.to_csv(path,chunksize=chunksize)
recons = DataFrame.from_csv(path).convert_objects('coerce')
assert_frame_equal(df, recons,check_names=False,check_less_precise=True)

for ncols in [4]:
base = int((chunksize// ncols or 1) or 1)
Expand Down Expand Up @@ -6864,7 +6867,7 @@ def test_replace_convert(self):
df = DataFrame([['foo', 'bar', 'bah'], ['bar', 'foo', 'bah']])
m = {'foo': 1, 'bar': 2, 'bah': 3}
rep = df.replace(m)
expec = Series([np.int_, np.int_, np.int_])
expec = Series([ np.int64] * 3)
res = rep.dtypes
assert_series_equal(expec, res)

Expand Down Expand Up @@ -10079,7 +10082,6 @@ def test_insert_column_bug_4032(self):

result = df.rename(columns={})
str(result)

expected = DataFrame([[1,1.1],[2, 2.2]],columns=['a','b'])
assert_frame_equal(result,expected)
df.insert(0, 'c', [1.3, 2.3])
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