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TST: fix some scipy 0.17.0 changes #12239

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TST: fix some scipy 0.17.0 changes #12239

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9 changes: 8 additions & 1 deletion pandas/tests/test_generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,7 @@
from numpy import nan
import pandas as pd

from distutils.version import LooseVersion
from pandas import (Index, Series, DataFrame, Panel, isnull,
date_range, period_range)
from pandas.core.index import MultiIndex
Expand Down Expand Up @@ -1195,9 +1196,15 @@ def test_interp_alt_scipy(self):
assert_frame_equal(result, expectedk)

_skip_if_no_pchip()
import scipy
result = df.interpolate(method='pchip')
expected.ix[2, 'A'] = 3
expected.ix[5, 'A'] = 6.125

if LooseVersion(scipy.__version__) >= '0.17.0':
expected.ix[5, 'A'] = 6.0
else:
expected.ix[5, 'A'] = 6.125

assert_frame_equal(result, expected)

def test_interp_rowwise(self):
Expand Down
5 changes: 3 additions & 2 deletions pandas/tests/test_nanops.py
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Expand Up @@ -122,7 +122,7 @@ def check_results(self, targ, res, axis):

# timedeltas are a beast here
def _coerce_tds(targ, res):
if targ.dtype == 'm8[ns]':
if hasattr(targ, 'dtype') and targ.dtype == 'm8[ns]':
if len(targ) == 1:
targ = targ[0].item()
res = res.item()
Expand All @@ -141,7 +141,8 @@ def _coerce_tds(targ, res):
tm.assert_almost_equal(targ, res)
except:

if targ.dtype == 'm8[ns]':
# handle timedelta dtypes
if hasattr(targ, 'dtype') and targ.dtype == 'm8[ns]':
targ, res = _coerce_tds(targ, res)
tm.assert_almost_equal(targ, res)
return
Expand Down
12 changes: 11 additions & 1 deletion pandas/tests/test_stats.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,6 +2,7 @@
from pandas import compat
import nose

from distutils.version import LooseVersion
from numpy import nan
import numpy as np

Expand Down Expand Up @@ -47,6 +48,7 @@ def _check(s, expected, method='average'):

def test_rank_methods_series(self):
tm.skip_if_no_package('scipy', '0.13', 'scipy.stats.rankdata')
import scipy
from scipy.stats import rankdata

xs = np.random.randn(9)
Expand All @@ -61,10 +63,15 @@ def test_rank_methods_series(self):
for m in ['average', 'min', 'max', 'first', 'dense']:
result = ts.rank(method=m)
sprank = rankdata(vals, m if m != 'first' else 'ordinal')
tm.assert_series_equal(result, Series(sprank, index=index))
expected = Series(sprank, index=index)

if LooseVersion(scipy.__version__) >= '0.17.0':
expected = expected.astype('float64')
tm.assert_series_equal(result, expected)

def test_rank_methods_frame(self):
tm.skip_if_no_package('scipy', '0.13', 'scipy.stats.rankdata')
import scipy
from scipy.stats import rankdata

xs = np.random.randint(0, 21, (100, 26))
Expand All @@ -81,6 +88,9 @@ def test_rank_methods_frame(self):
rankdata, ax, vals,
m if m != 'first' else 'ordinal')
expected = DataFrame(sprank, columns=cols)

if LooseVersion(scipy.__version__) >= '0.17.0':
expected = expected.astype('float64')
tm.assert_frame_equal(result, expected)

def test_rank_dense_method(self):
Expand Down