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TST: Fixturize series/test_missing.py #22973

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merged 2 commits into from
Oct 4, 2018
Merged

TST: Fixturize series/test_missing.py #22973

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8f823af
Merge pull request #1 from pandas-dev/master
Anjali2019 Oct 3, 2018
4cf7f68
TST: Fixturize series/test_missing.py
Anjali2019 Oct 3, 2018
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46 changes: 23 additions & 23 deletions pandas/tests/series/test_missing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,8 +21,6 @@
import pandas.util.testing as tm
import pandas.util._test_decorators as td

from .common import TestData

try:
import scipy
_is_scipy_ge_0190 = (LooseVersion(scipy.__version__) >=
Expand Down Expand Up @@ -52,7 +50,7 @@ def _simple_ts(start, end, freq='D'):
return Series(np.random.randn(len(rng)), index=rng)


class TestSeriesMissingData(TestData):
class TestSeriesMissingData():

def test_remove_na_deprecation(self):
# see gh-16971
Expand Down Expand Up @@ -489,7 +487,7 @@ def test_isnull_for_inf_deprecated(self):
tm.assert_series_equal(r, e)
tm.assert_series_equal(dr, de)

def test_fillna(self):
def test_fillna(self, datetime_series):
ts = Series([0., 1., 2., 3., 4.], index=tm.makeDateIndex(5))

tm.assert_series_equal(ts, ts.fillna(method='ffill'))
Expand All @@ -506,7 +504,8 @@ def test_fillna(self):
tm.assert_series_equal(ts.fillna(value=5), exp)

pytest.raises(ValueError, ts.fillna)
pytest.raises(ValueError, self.ts.fillna, value=0, method='ffill')
pytest.raises(ValueError, datetime_series.fillna, value=0,
method='ffill')

# GH 5703
s1 = Series([np.nan])
Expand Down Expand Up @@ -576,9 +575,9 @@ def test_fillna_inplace(self):
expected = x.fillna(value=0)
assert_series_equal(y, expected)

def test_fillna_invalid_method(self):
def test_fillna_invalid_method(self, datetime_series):
try:
self.ts.fillna(method='ffil')
datetime_series.fillna(method='ffil')
except ValueError as inst:
assert 'ffil' in str(inst)

Expand Down Expand Up @@ -632,8 +631,8 @@ def test_timedelta64_nan(self):

# def test_logical_range_select(self):
# np.random.seed(12345)
# selector = -0.5 <= self.ts <= 0.5
# expected = (self.ts >= -0.5) & (self.ts <= 0.5)
# selector = -0.5 <= datetime_series <= 0.5
# expected = (datetime_series >= -0.5) & (datetime_series <= 0.5)
# assert_series_equal(selector, expected)

def test_dropna_empty(self):
Expand Down Expand Up @@ -688,8 +687,8 @@ def test_dropna_intervals(self):
expected = s.iloc[1:]
assert_series_equal(result, expected)

def test_valid(self):
ts = self.ts.copy()
def test_valid(self, datetime_series):
ts = datetime_series.copy()
ts[::2] = np.NaN

result = ts.dropna()
Expand Down Expand Up @@ -734,12 +733,12 @@ def test_pad_require_monotonicity(self):

pytest.raises(ValueError, rng2.get_indexer, rng, method='pad')

def test_dropna_preserve_name(self):
self.ts[:5] = np.nan
result = self.ts.dropna()
assert result.name == self.ts.name
name = self.ts.name
ts = self.ts.copy()
def test_dropna_preserve_name(self, datetime_series):
datetime_series[:5] = np.nan
result = datetime_series.dropna()
assert result.name == datetime_series.name
name = datetime_series.name
ts = datetime_series.copy()
ts.dropna(inplace=True)
assert ts.name == name

Expand Down Expand Up @@ -825,19 +824,20 @@ def test_series_pad_backfill_limit(self):
assert_series_equal(result, expected)


class TestSeriesInterpolateData(TestData):
class TestSeriesInterpolateData():

def test_interpolate(self):
ts = Series(np.arange(len(self.ts), dtype=float), self.ts.index)
def test_interpolate(self, datetime_series, string_series):
ts = Series(np.arange(len(datetime_series), dtype=float),
datetime_series.index)

ts_copy = ts.copy()
ts_copy[5:10] = np.NaN

linear_interp = ts_copy.interpolate(method='linear')
tm.assert_series_equal(linear_interp, ts)

ord_ts = Series([d.toordinal() for d in self.ts.index],
index=self.ts.index).astype(float)
ord_ts = Series([d.toordinal() for d in datetime_series.index],
index=datetime_series.index).astype(float)

ord_ts_copy = ord_ts.copy()
ord_ts_copy[5:10] = np.NaN
Expand All @@ -847,7 +847,7 @@ def test_interpolate(self):

# try time interpolation on a non-TimeSeries
# Only raises ValueError if there are NaNs.
non_ts = self.series.copy()
non_ts = string_series.copy()
non_ts[0] = np.NaN
pytest.raises(ValueError, non_ts.interpolate, method='time')

Expand Down