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ERR: better error reporting for failing parsing in timedelta/timeseries #10720 #10883

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ERR: better error reporting for failing parsing in timedelta/timeseries #10720 #10883

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79e9112
BUG: 10720 adding all
springcoil Aug 22, 2015
5f99110
Updating my test based on feedback
springcoil Aug 22, 2015
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3 changes: 2 additions & 1 deletion pandas/core/common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1718,7 +1718,8 @@ def _interpolate_scipy_wrapper(x, y, new_x, method, fill_value=None,
bounds_error=bounds_error)
new_y = terp(new_x)
elif method == 'spline':
# GH #10633

# GH 10633
if not order:
raise ValueError("order needs to be specified and greater than 0")
terp = interpolate.UnivariateSpline(x, y, k=order, **kwargs)
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8 changes: 8 additions & 0 deletions pandas/tests/test_generic.py
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Expand Up @@ -799,6 +799,14 @@ def test_nan_interpolate(self):
tm._skip_if_no_scipy()
result = s.interpolate(method='polynomial', order=1)
assert_series_equal(result, expected)
# GH #10633: first attempt
def test_interpolate_spline(self):
np.random.seed(1)
s = pd.Series(np.arange(10)**2)
s[np.random.randint(0,9,3)] = np.nan
with tm.assertRaises(ValueError):
s.interpolate(method='spline')


def test_nan_irregular_index(self):
s = Series([1, 2, np.nan, 4], index=[1, 3, 5, 9])
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4 changes: 2 additions & 2 deletions pandas/tseries/tests/test_timeseries.py
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Expand Up @@ -923,8 +923,8 @@ def test_to_datetime_with_apply(self):
assert_series_equal(result, expected)

td = pd.Series(['May 04', 'Jun 02', ''], index=[1,2,3])
self.assertRaises(ValueError, lambda : pd.to_datetime(td,format='%b %y', errors='raise'))
self.assertRaises(ValueError, lambda : td.apply(pd.to_datetime, format='%b %y', errors='raise'))
self.assertRaisesRegexp(ValueError, 'Unknown string format. You can coerce errors to NaT by passing coerce', lambda : pd.to_datetime(td,format='%b %y', errors='raise'))
self.assertRaisesRegexp(ValueError, 'Unknown string format. You can coerce errors to NaT by passing coerce',lambda : td.apply(pd.to_datetime, format='%b %y', errors='raise'))
expected = pd.to_datetime(td, format='%b %y', errors='coerce')

result = td.apply(lambda x: pd.to_datetime(x, format='%b %y', errors='coerce'))
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