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CLN: Python 3.4 deprecation of assert_
#7131: replace instances of assert_(not b) with assertFalse(b) and some instances of assert_(b) with assertTrue(b). Work-in-progress
1 parent 9fff73f commit 1baee4c

11 files changed

+268
-271
lines changed

‎pandas/tests/test_base.py

+4-4
Original file line numberDiff line numberDiff line change
@@ -221,7 +221,7 @@ def test_value_counts_unique_nunique(self):
221221

222222
if isinstance(o, DatetimeIndex):
223223
# DatetimeIndex.unique returns DatetimeIndex
224-
self.assert_(o.unique().equals(klass(values)))
224+
self.assertTrue(o.unique().equals(klass(values)))
225225
else:
226226
self.assert_numpy_array_equal(o.unique(), values)
227227

@@ -262,9 +262,9 @@ def test_value_counts_unique_nunique(self):
262262
self.assert_numpy_array_equal(result[1:], values[2:])
263263

264264
if isinstance(o, DatetimeIndex):
265-
self.assert_(result[0] is pd.NaT)
265+
self.assertTrue(result[0] is pd.NaT)
266266
else:
267-
self.assert_(pd.isnull(result[0]))
267+
self.assertTrue(pd.isnull(result[0]))
268268

269269
if isinstance(o, DatetimeIndex):
270270
self.assertEqual(o.nunique(), 9)
@@ -351,7 +351,7 @@ def test_value_counts_inferred(self):
351351
dtype='datetime64[ns]')
352352
if isinstance(s, DatetimeIndex):
353353
expected = DatetimeIndex(expected)
354-
self.assert_(s.unique().equals(expected))
354+
self.assertTrue(s.unique().equals(expected))
355355
else:
356356
self.assert_numpy_array_equal(s.unique(), expected)
357357

‎pandas/tests/test_frame.py

+19-19
Original file line numberDiff line numberDiff line change
@@ -5089,7 +5089,7 @@ def _check_unaligned_frame(meth, op, df, other):
50895089

50905090
# DataFrame
50915091
self.assert_(df.eq(df).values.all())
5092-
self.assert_(not df.ne(df).values.any())
5092+
self.assertFalse(df.ne(df).values.any())
50935093
for op in ['eq', 'ne', 'gt', 'lt', 'ge', 'le']:
50945094
f = getattr(df, op)
50955095
o = getattr(operator, op)
@@ -5149,17 +5149,17 @@ def _test_seq(df, idx_ser, col_ser):
51495149
# NA
51505150
df.ix[0, 0] = np.nan
51515151
rs = df.eq(df)
5152-
self.assert_(not rs.ix[0, 0])
5152+
self.assertFalse(rs.ix[0, 0])
51535153
rs = df.ne(df)
51545154
self.assert_(rs.ix[0, 0])
51555155
rs = df.gt(df)
5156-
self.assert_(not rs.ix[0, 0])
5156+
self.assertFalse(rs.ix[0, 0])
51575157
rs = df.lt(df)
5158-
self.assert_(not rs.ix[0, 0])
5158+
self.assertFalse(rs.ix[0, 0])
51595159
rs = df.ge(df)
5160-
self.assert_(not rs.ix[0, 0])
5160+
self.assertFalse(rs.ix[0, 0])
51615161
rs = df.le(df)
5162-
self.assert_(not rs.ix[0, 0])
5162+
self.assertFalse(rs.ix[0, 0])
51635163

51645164

51655165

@@ -5169,14 +5169,14 @@ def _test_seq(df, idx_ser, col_ser):
51695169
df = DataFrame({'a': arr})
51705170
df2 = DataFrame({'a': arr2})
51715171
rs = df.gt(df2)
5172-
self.assert_(not rs.values.any())
5172+
self.assertFalse(rs.values.any())
51735173
rs = df.ne(df2)
51745174
self.assert_(rs.values.all())
51755175

51765176
arr3 = np.array([2j, np.nan, None])
51775177
df3 = DataFrame({'a': arr3})
51785178
rs = df3.gt(2j)
5179-
self.assert_(not rs.values.any())
5179+
self.assertFalse(rs.values.any())
51805180

51815181
# corner, dtype=object
51825182
df1 = DataFrame({'col': ['foo', np.nan, 'bar']})
@@ -8400,7 +8400,7 @@ def test_truncate_copy(self):
84008400
index = self.tsframe.index
84018401
truncated = self.tsframe.truncate(index[5], index[10])
84028402
truncated.values[:] = 5.
8403-
self.assert_(not (self.tsframe.values[5:11] == 5).any())
8403+
self.assertFalse((self.tsframe.values[5:11] == 5).any())
84048404

84058405
def test_xs(self):
84068406
idx = self.frame.index[5]
@@ -10499,13 +10499,13 @@ def test_clip(self):
1049910499
median = self.frame.median().median()
1050010500

1050110501
capped = self.frame.clip_upper(median)
10502-
self.assert_(not (capped.values > median).any())
10502+
self.assertFalse((capped.values > median).any())
1050310503

1050410504
floored = self.frame.clip_lower(median)
10505-
self.assert_(not (floored.values < median).any())
10505+
self.assertFalse((floored.values < median).any())
1050610506

1050710507
double = self.frame.clip(upper=median, lower=median)
10508-
self.assert_(not (double.values != median).any())
10508+
self.assertFalse((double.values != median).any())
1050910509

1051010510
def test_dataframe_clip(self):
1051110511

@@ -10536,7 +10536,7 @@ def test_get_X_columns(self):
1053610536
['a', 'b', 'e'])
1053710537

1053810538
def test_is_mixed_type(self):
10539-
self.assert_(not self.frame._is_mixed_type)
10539+
self.assertFalse(self.frame._is_mixed_type)
1054010540
self.assert_(self.mixed_frame._is_mixed_type)
1054110541

1054210542
def test_get_numeric_data(self):
@@ -11787,7 +11787,7 @@ def test_constructor_frame_copy(self):
1178711787
cop = DataFrame(self.frame, copy=True)
1178811788
cop['A'] = 5
1178911789
self.assert_((cop['A'] == 5).all())
11790-
self.assert_(not (self.frame['A'] == 5).all())
11790+
self.assertFalse((self.frame['A'] == 5).all())
1179111791

1179211792
def test_constructor_ndarray_copy(self):
1179311793
df = DataFrame(self.frame.values)
@@ -11797,15 +11797,15 @@ def test_constructor_ndarray_copy(self):
1179711797

1179811798
df = DataFrame(self.frame.values, copy=True)
1179911799
self.frame.values[6] = 6
11800-
self.assert_(not (df.values[6] == 6).all())
11800+
self.assertFalse((df.values[6] == 6).all())
1180111801

1180211802
def test_constructor_series_copy(self):
1180311803
series = self.frame._series
1180411804

1180511805
df = DataFrame({'A': series['A']})
1180611806
df['A'][:] = 5
1180711807

11808-
self.assert_(not (series['A'] == 5).all())
11808+
self.assertFalse((series['A'] == 5).all())
1180911809

1181011810
def test_constructor_compound_dtypes(self):
1181111811
# GH 5191
@@ -11938,7 +11938,7 @@ def test_consolidate_inplace(self):
1193811938

1193911939
def test_as_matrix_consolidate(self):
1194011940
self.frame['E'] = 7.
11941-
self.assert_(not self.frame._data.is_consolidated())
11941+
self.assertFalse(self.frame._data.is_consolidated())
1194211942
_ = self.frame.as_matrix()
1194311943
self.assert_(self.frame._data.is_consolidated())
1194411944

@@ -12365,8 +12365,8 @@ def __nonzero__(self):
1236512365
r0 = getattr(all_na, name)(axis=0)
1236612366
r1 = getattr(all_na, name)(axis=1)
1236712367
if name == 'any':
12368-
self.assert_(not r0.any())
12369-
self.assert_(not r1.any())
12368+
self.assertFalse(r0.any())
12369+
self.assertFalse(r1.any())
1237012370
else:
1237112371
self.assert_(r0.all())
1237212372
self.assert_(r1.all())

‎pandas/tests/test_generic.py

+7-7
Original file line numberDiff line numberDiff line change
@@ -1148,15 +1148,15 @@ def test_equals(self):
11481148
self.assert_(s1.equals(s2))
11491149

11501150
s1[1] = 99
1151-
self.assert_(not s1.equals(s2))
1151+
self.assertFalse(s1.equals(s2))
11521152

11531153
# NaNs compare as equal
11541154
s1 = pd.Series([1, np.nan, 3, np.nan], index=[0, 2, 1, 3])
11551155
s2 = s1.copy()
11561156
self.assert_(s1.equals(s2))
11571157

11581158
s2[0] = 9.9
1159-
self.assert_(not s1.equals(s2))
1159+
self.assertFalse(s1.equals(s2))
11601160

11611161
idx = MultiIndex.from_tuples([(0, 'a'), (1, 'b'), (2, 'c')])
11621162
s1 = Series([1, 2, np.nan], index=idx)
@@ -1179,22 +1179,22 @@ def test_equals(self):
11791179
self.assert_(df1['diff'].equals(df2['diff']))
11801180
self.assert_(df1['bool'].equals(df2['bool']))
11811181
self.assert_(df1.equals(df2))
1182-
self.assert_(not df1.equals(object))
1182+
self.assertFalse(df1.equals(object))
11831183

11841184
# different dtype
11851185
different = df1.copy()
11861186
different['floats'] = different['floats'].astype('float32')
1187-
self.assert_(not df1.equals(different))
1187+
self.assertFalse(df1.equals(different))
11881188

11891189
# different index
11901190
different_index = -index
11911191
different = df2.set_index(different_index)
1192-
self.assert_(not df1.equals(different))
1192+
self.assertFalse(df1.equals(different))
11931193

11941194
# different columns
11951195
different = df2.copy()
11961196
different.columns = df2.columns[::-1]
1197-
self.assert_(not df1.equals(different))
1197+
self.assertFalse(df1.equals(different))
11981198

11991199
# DatetimeIndex
12001200
index = pd.date_range('2000-1-1', periods=10, freq='T')
@@ -1208,7 +1208,7 @@ def test_equals(self):
12081208
self.assert_(df3.equals(df2))
12091209

12101210
df2 = df1.set_index(['floats'], append=True)
1211-
self.assert_(not df3.equals(df2))
1211+
self.assertFalse(df3.equals(df2))
12121212

12131213
# NaN in index
12141214
df3 = df1.set_index(['floats'], append=True)

‎pandas/tests/test_graphics.py

+13-13
Original file line numberDiff line numberDiff line change
@@ -413,7 +413,7 @@ def test_ts_area_lim(self):
413413
ax = self.ts.plot(kind='area', stacked=False)
414414
xmin, xmax = ax.get_xlim()
415415
lines = ax.get_lines()
416-
self.assertEqual(xmin, lines[0].get_data(orig=False)[0][0])
416+
self.assertEqual(xmin, lines[0].get_data(orig=False)[0][0])
417417
self.assertEqual(xmax, lines[0].get_data(orig=False)[0][-1])
418418

419419
def test_line_area_nan_series(self):
@@ -1023,13 +1023,13 @@ def test_area_lim(self):
10231023
xmin, xmax = ax.get_xlim()
10241024
ymin, ymax = ax.get_ylim()
10251025
lines = ax.get_lines()
1026-
self.assertEqual(xmin, lines[0].get_data()[0][0])
1027-
self.assertEqual(xmax, lines[0].get_data()[0][-1])
1028-
self.assertEqual(ymin, 0)
1026+
self.assertEqual(xmin, lines[0].get_data()[0][0])
1027+
self.assertEqual(xmax, lines[0].get_data()[0][-1])
1028+
self.assertEqual(ymin, 0)
10291029

10301030
ax = _check_plot_works(neg_df.plot, kind='area', stacked=stacked)
10311031
ymin, ymax = ax.get_ylim()
1032-
self.assertEqual(ymax, 0)
1032+
self.assertEqual(ymax, 0)
10331033

10341034
@slow
10351035
def test_bar_colors(self):
@@ -1471,7 +1471,7 @@ def test_hist(self):
14711471
df = DataFrame(randn(100, 3))
14721472
_check_plot_works(df.hist)
14731473
axes = df.hist(grid=False)
1474-
self.assert_(not axes[1, 1].get_visible())
1474+
self.assertFalse(axes[1, 1].get_visible())
14751475

14761476
df = DataFrame(randn(100, 1))
14771477
_check_plot_works(df.hist)
@@ -1576,7 +1576,7 @@ def scat2(x, y, by=None, ax=None, figsize=None):
15761576
def test_andrews_curves(self):
15771577
from pandas.tools.plotting import andrews_curves
15781578
from matplotlib import cm
1579-
1579+
15801580
df = self.iris
15811581

15821582
_check_plot_works(andrews_curves, df, 'Name')
@@ -1601,15 +1601,15 @@ def test_andrews_curves(self):
16011601
ax = andrews_curves(df, 'Name', color=colors)
16021602
handles, labels = ax.get_legend_handles_labels()
16031603
self._check_colors(handles, linecolors=colors)
1604-
1604+
16051605
with tm.assert_produces_warning(FutureWarning):
16061606
andrews_curves(data=df, class_column='Name')
16071607

16081608
@slow
16091609
def test_parallel_coordinates(self):
16101610
from pandas.tools.plotting import parallel_coordinates
16111611
from matplotlib import cm
1612-
1612+
16131613
df = self.iris
16141614

16151615
_check_plot_works(parallel_coordinates, df, 'Name')
@@ -1634,7 +1634,7 @@ def test_parallel_coordinates(self):
16341634
ax = parallel_coordinates(df, 'Name', color=colors)
16351635
handles, labels = ax.get_legend_handles_labels()
16361636
self._check_colors(handles, linecolors=colors)
1637-
1637+
16381638
with tm.assert_produces_warning(FutureWarning):
16391639
parallel_coordinates(data=df, class_column='Name')
16401640
with tm.assert_produces_warning(FutureWarning):
@@ -1845,7 +1845,7 @@ def test_area_colors(self):
18451845
poly = [o for o in ax.get_children() if isinstance(o, PolyCollection)]
18461846
self._check_colors(poly, facecolors=rgba_colors)
18471847
tm.close()
1848-
1848+
18491849
ax = df.plot(kind='area', colormap=cm.jet)
18501850
rgba_colors = lmap(cm.jet, np.linspace(0, 1, len(df)))
18511851
self._check_colors(ax.get_lines(), linecolors=rgba_colors)
@@ -1920,7 +1920,7 @@ def test_hexbin_basic(self):
19201920
# hexbin should have 2 axes in the figure, 1 for plotting and another is colorbar
19211921
self.assertEqual(len(axes[0].figure.axes), 2)
19221922
# return value is single axes
1923-
self._check_axes_shape(axes, axes_num=1, layout=(1, ))
1923+
self._check_axes_shape(axes, axes_num=1, layout=(1, ))
19241924

19251925

19261926
@slow
@@ -2081,7 +2081,7 @@ def test_errorbar_with_partial_columns(self):
20812081
df_err = DataFrame(d_err)
20822082
for err in [d_err, df_err]:
20832083
ax = _check_plot_works(df.plot, yerr=err)
2084-
self._check_has_errorbars(ax, xerr=0, yerr=1)
2084+
self._check_has_errorbars(ax, xerr=0, yerr=1)
20852085

20862086
@slow
20872087
def test_errorbar_timeseries(self):

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