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BUG GH23224 Allow integer_array to be initialized with all None #23237

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Merged
merged 6 commits into from
Oct 23, 2018
Merged

BUG GH23224 Allow integer_array to be initialized with all None #23237

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4fd3202
BUG-23224 Allow integer_array to be initialized with all None
JustinZhengBC Oct 19, 2018
0590df8
BUG-23224 Add tests and other requested changes
JustinZhengBC Oct 19, 2018
9a2a053
BUG-23224 Merge master and fix conflict
JustinZhengBC Oct 19, 2018
349ca0a
Fix existing tests
JustinZhengBC Oct 19, 2018
a679c15
Merge branch 'master' into PR_TOOL_MERGE_PR_23237
jreback Oct 23, 2018
14399b1
use idiomatic
jreback Oct 23, 2018
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7 changes: 5 additions & 2 deletions pandas/core/arrays/integer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -173,8 +173,11 @@ def coerce_to_array(values, dtype, mask=None, copy=False):
values = np.array(values, copy=copy)
if is_object_dtype(values):
inferred_type = lib.infer_dtype(values)
if inferred_type not in ['floating', 'integer',
'mixed-integer', 'mixed-integer-float']:
if inferred_type is 'mixed' and isna(values).any():
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Shoudn't this any be all ?
Because now this allows something like this:

In [14]: pd.core.arrays.integer_array([np.nan, {'a':1}])
Out[14]: IntegerArray([nan, nan], dtype='Int64')

A cornercase, but basically any python object that is not a datetime or string (something that numpy will convert to an object array).

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good catch, yep need to have all here

values = np.empty(len(values))
values.fill(np.nan)
elif inferred_type not in ['floating', 'integer',
'mixed-integer', 'mixed-integer-float']:
raise TypeError("{} cannot be converted to an IntegerDtype".format(
values.dtype))

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9 changes: 5 additions & 4 deletions pandas/tests/arrays/test_integer.py
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Expand Up @@ -527,9 +527,9 @@ def test_integer_array_constructor():

@pytest.mark.parametrize('a, b', [
([1, None], [1, np.nan]),
pytest.param([None], [np.nan],
marks=pytest.mark.xfail(reason='GH-23224',
strict=True)),
([None], [np.nan]),
([None, np.nan], [np.nan, np.nan]),
([np.nan, np.nan], [np.nan, np.nan]),
])
def test_integer_array_constructor_none_is_nan(a, b):
result = integer_array(a)
Expand Down Expand Up @@ -559,7 +559,8 @@ def test_integer_array_constructor_copy():
1,
1.0,
pd.date_range('20130101', periods=2),
np.array(['foo'])])
np.array(['foo']),
[[1, 2], [3, 4]]])
def test_to_integer_array_error(values):
# error in converting existing arrays to IntegerArrays
with pytest.raises(TypeError):
Expand Down