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BUG: interpolate with no nans and limit #8235

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Sep 10, 2014
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5 changes: 5 additions & 0 deletions doc/source/v0.15.0.txt
Original file line number Diff line number Diff line change
Expand Up @@ -756,3 +756,8 @@ Bug Fixes
- Bug with kde plot and NaNs (:issue:`8182`)
- Bug in ``GroupBy.count`` with float32 data type were nan values were not excluded (:issue:`8169`).
- Bug with stacked barplots and NaNs (:issue:`8175`).



- Bug in interpolation methods with the ``limit`` keyword when no values
needed interpolating (:issue:`7173`).
2 changes: 2 additions & 0 deletions pandas/core/common.py
Original file line number Diff line number Diff line change
Expand Up @@ -1534,6 +1534,8 @@ def interpolate_1d(xvalues, yvalues, method='linear', limit=None,
def _interp_limit(invalid, limit):
"""mask off values that won't be filled since they exceed the limit"""
all_nans = np.where(invalid)[0]
if all_nans.size == 0: # no nans anyway
return []
violate = [invalid[x:x + limit + 1] for x in all_nans]
violate = np.array([x.all() & (x.size > limit) for x in violate])
return all_nans[violate] + limit
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7 changes: 7 additions & 0 deletions pandas/tests/test_generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -656,6 +656,13 @@ def test_interp_datetime64(self):
expected = Series([1., 1., 3.], index=date_range('1/1/2000', periods=3))
assert_series_equal(result, expected)

def test_interp_limit_no_nans(self):
# GH 7173
s = pd.Series([1., 2., 3.])
result = s.interpolate(limit=1)
expected = s
assert_series_equal(result, expected)

def test_describe(self):
_ = self.series.describe()
_ = self.ts.describe()
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