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BUG: pd.to_datetime doesn't raises AttributeError with specific input… #13909

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Merged
merged 1 commit into from
Aug 5, 2016
Merged

BUG: pd.to_datetime doesn't raises AttributeError with specific input… #13909

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.19.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -858,6 +858,7 @@ Bug Fixes
- Bug in ``factorize`` raises ``AmbiguousTimeError`` if data contains datetime near DST boundary (:issue:`13750`)
- Bug in ``.set_index`` raises ``AmbiguousTimeError`` if new index contains DST boundary and multi levels (:issue:`12920`)
- Bug in ``pd.read_hdf()`` returns incorrect result when a ``DataFrame`` with a ``categorical`` column and a query which doesn't match any values (:issue:`13792`)
- Bug in ``pd.to_datetime()`` raise ``AttributeError`` with NaN and the other string is not valid when errors='ignore' (:issue:`12424`)


- Bug in ``Series`` comparison operators when dealing with zero dim NumPy arrays (:issue:`13006`)
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6 changes: 6 additions & 0 deletions pandas/tests/test_algos.py
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Expand Up @@ -568,6 +568,12 @@ def test_value_counts_datetime_outofbounds(self):
exp = pd.Series([3, 2, 1], index=exp_index)
tm.assert_series_equal(res, exp)

# GH 12424
res = pd.to_datetime(pd.Series(['2362-01-01', np.nan]),
errors='ignore')
exp = pd.Series(['2362-01-01', np.nan], dtype=object)
tm.assert_series_equal(res, exp)

def test_categorical(self):
s = Series(pd.Categorical(list('aaabbc')))
result = s.value_counts()
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6 changes: 3 additions & 3 deletions pandas/tslib.pyx
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Expand Up @@ -2396,10 +2396,10 @@ cpdef array_to_datetime(ndarray[object] values, errors='raise',

# set as nan except if its a NaT
if _checknull_with_nat(val):
if val.view('i8') == NPY_NAT:
oresult[i] = NaT
else:
if PyFloat_Check(val):
oresult[i] = np.nan
else:
oresult[i] = NaT
elif util.is_datetime64_object(val):
if get_datetime64_value(val) == NPY_NAT:
oresult[i] = NaT
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