pandas@e6b0c29 (original) (raw)

`@@ -21,8 +21,6 @@

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`import pandas.util.testing as tm

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`import pandas.util._test_decorators as td

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from .common import TestData

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-

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`try:

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`import scipy

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`_is_scipy_ge_0190 = (LooseVersion(scipy.version) >=

`@@ -52,7 +50,7 @@ def _simple_ts(start, end, freq='D'):

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`return Series(np.random.randn(len(rng)), index=rng)

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class TestSeriesMissingData(TestData):

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class TestSeriesMissingData():

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`def test_remove_na_deprecation(self):

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`# see gh-16971

`@@ -489,7 +487,7 @@ def test_isnull_for_inf_deprecated(self):

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`tm.assert_series_equal(r, e)

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`tm.assert_series_equal(dr, de)

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def test_fillna(self):

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def test_fillna(self, datetime_series):

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`ts = Series([0., 1., 2., 3., 4.], index=tm.makeDateIndex(5))

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`tm.assert_series_equal(ts, ts.fillna(method='ffill'))

`@@ -506,7 +504,8 @@ def test_fillna(self):

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`tm.assert_series_equal(ts.fillna(value=5), exp)

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`pytest.raises(ValueError, ts.fillna)

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

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pytest.raises(ValueError, datetime_series.fillna, value=0,

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method='ffill')

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`# GH 5703

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`s1 = Series([np.nan])

`@@ -576,9 +575,9 @@ def test_fillna_inplace(self):

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`expected = x.fillna(value=0)

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`assert_series_equal(y, expected)

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def test_fillna_invalid_method(self):

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def test_fillna_invalid_method(self, datetime_series):

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`try:

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self.ts.fillna(method='ffil')

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datetime_series.fillna(method='ffil')

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`except ValueError as inst:

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`assert 'ffil' in str(inst)

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`@@ -632,8 +631,8 @@ def test_timedelta64_nan(self):

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`# def test_logical_range_select(self):

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`# np.random.seed(12345)

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selector = -0.5 <= self.ts <= 0.5

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expected = (self.ts >= -0.5) & (self.ts <= 0.5)

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selector = -0.5 <= datetime_series <= 0.5

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expected = (datetime_series >= -0.5) & (datetime_series <= 0.5)

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`# assert_series_equal(selector, expected)

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`def test_dropna_empty(self):

`@@ -688,8 +687,8 @@ def test_dropna_intervals(self):

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`expected = s.iloc[1:]

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`assert_series_equal(result, expected)

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def test_valid(self):

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ts = self.ts.copy()

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def test_valid(self, datetime_series):

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ts = datetime_series.copy()

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`ts[::2] = np.NaN

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`result = ts.dropna()

`@@ -734,12 +733,12 @@ def test_pad_require_monotonicity(self):

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

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def test_dropna_preserve_name(self):

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self.ts[:5] = np.nan

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result = self.ts.dropna()

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assert result.name == self.ts.name

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name = self.ts.name

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ts = self.ts.copy()

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def test_dropna_preserve_name(self, datetime_series):

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datetime_series[:5] = np.nan

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result = datetime_series.dropna()

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assert result.name == datetime_series.name

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name = datetime_series.name

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ts = datetime_series.copy()

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`ts.dropna(inplace=True)

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`assert ts.name == name

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`@@ -825,19 +824,20 @@ def test_series_pad_backfill_limit(self):

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`assert_series_equal(result, expected)

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class TestSeriesInterpolateData(TestData):

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class TestSeriesInterpolateData():

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def test_interpolate(self):

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ts = Series(np.arange(len(self.ts), dtype=float), self.ts.index)

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def test_interpolate(self, datetime_series, string_series):

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ts = Series(np.arange(len(datetime_series), dtype=float),

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datetime_series.index)

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`ts_copy = ts.copy()

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`ts_copy[5:10] = np.NaN

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`linear_interp = ts_copy.interpolate(method='linear')

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`tm.assert_series_equal(linear_interp, ts)

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

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index=self.ts.index).astype(float)

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ord_ts = Series([d.toordinal() for d in datetime_series.index],

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index=datetime_series.index).astype(float)

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`ord_ts_copy = ord_ts.copy()

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`ord_ts_copy[5:10] = np.NaN

`@@ -847,7 +847,7 @@ def test_interpolate(self):

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`# try time interpolation on a non-TimeSeries

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`# Only raises ValueError if there are NaNs.

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non_ts = self.series.copy()

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non_ts = string_series.copy()

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`non_ts[0] = np.NaN

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`pytest.raises(ValueError, non_ts.interpolate, method='time')

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