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Preserve None in Series unique #20893

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Merged
merged 6 commits into from
May 11, 2018
Merged

Preserve None in Series unique #20893

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f33a4c5
Added test for preservation of NA values in Series unique
WillAyd May 1, 2018
9736ecb
Merge remote-tracking branch 'upstream/master' into uniq-tst
WillAyd May 1, 2018
f791e5e
Merge remote-tracking branch 'upstream/master' into uniq-tst
WillAyd May 4, 2018
1e83e60
Reverted none to nan conversion in unique
WillAyd May 4, 2018
df28111
Moved test; added comments
WillAyd May 5, 2018
f106b58
Merge remote-tracking branch 'upstream/master' into uniq-tst
WillAyd May 5, 2018
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7 changes: 6 additions & 1 deletion pandas/_libs/hashtable_class_helper.pxi.in
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Original file line number Diff line number Diff line change
Expand Up @@ -870,7 +870,12 @@ cdef class PyObjectHashTable(HashTable):
for i in range(n):
val = values[i]
hash(val)
if not checknull(val):

# `val is None` below is exception to prevent mangling of None and
# other NA values; note however that other NA values (ex: pd.NaT
# and np.nan) will still get mangled, so many not be a permanent
# solution; see GH 20866
if not checknull(val) or val is None:
k = kh_get_pymap(self.table, <PyObject*>val)
if k == self.table.n_buckets:
kh_put_pymap(self.table, <PyObject*>val, &ret)
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8 changes: 8 additions & 0 deletions pandas/tests/test_algos.py
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Expand Up @@ -491,6 +491,14 @@ def test_tuple_with_strings(self, arg, expected):
result = pd.unique(arg)
tm.assert_numpy_array_equal(result, expected)

def test_obj_none_preservation(self):
# GH 20866
arr = np.array(['foo', None], dtype=object)
result = pd.unique(arr)
expected = np.array(['foo', None], dtype=object)

tm.assert_numpy_array_equal(result, expected, strict_nan=True)


class TestIsin(object):

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