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TST: remove bunch of warnings for .astype(.....), xref #17636 (#17759)
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+39
-42
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4 files changed

+39
-42
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‎pandas/tests/indexing/test_categorical.py

+14-18
Original file line numberDiff line numberDiff line change
@@ -8,6 +8,7 @@
88
Categorical, CategoricalIndex)
99
from pandas.util.testing import assert_series_equal, assert_frame_equal
1010
from pandas.util import testing as tm
11+
from pandas.api.types import CategoricalDtype as CDT
1112

1213

1314
class TestCategoricalIndex(object):
@@ -16,36 +17,32 @@ def setup_method(self, method):
1617

1718
self.df = DataFrame({'A': np.arange(6, dtype='int64'),
1819
'B': Series(list('aabbca')).astype(
19-
'category', categories=list(
20-
'cab'))}).set_index('B')
20+
CDT(list('cab')))}).set_index('B')
2121
self.df2 = DataFrame({'A': np.arange(6, dtype='int64'),
2222
'B': Series(list('aabbca')).astype(
23-
'category', categories=list(
24-
'cabe'))}).set_index('B')
23+
CDT(list('cabe')))}).set_index('B')
2524
self.df3 = DataFrame({'A': np.arange(6, dtype='int64'),
2625
'B': (Series([1, 1, 2, 1, 3, 2])
27-
.astype('category', categories=[3, 2, 1],
28-
ordered=True))}).set_index('B')
26+
.astype(CDT([3, 2, 1], ordered=True)))
27+
}).set_index('B')
2928
self.df4 = DataFrame({'A': np.arange(6, dtype='int64'),
3029
'B': (Series([1, 1, 2, 1, 3, 2])
31-
.astype('category', categories=[3, 2, 1],
32-
ordered=False))}).set_index('B')
30+
.astype(CDT([3, 2, 1], ordered=False)))
31+
}).set_index('B')
3332

3433
def test_loc_scalar(self):
3534
result = self.df.loc['a']
3635
expected = (DataFrame({'A': [0, 1, 5],
3736
'B': (Series(list('aaa'))
38-
.astype('category',
39-
categories=list('cab')))})
37+
.astype(CDT(list('cab'))))})
4038
.set_index('B'))
4139
assert_frame_equal(result, expected)
4240

4341
df = self.df.copy()
4442
df.loc['a'] = 20
4543
expected = (DataFrame({'A': [20, 20, 2, 3, 4, 20],
4644
'B': (Series(list('aabbca'))
47-
.astype('category',
48-
categories=list('cab')))})
45+
.astype(CDT(list('cab'))))})
4946
.set_index('B'))
5047
assert_frame_equal(df, expected)
5148

@@ -319,13 +316,13 @@ def test_reindexing(self):
319316
result = self.df2.reindex(Categorical(['a', 'd'], categories=cats))
320317
expected = DataFrame({'A': [0, 1, 5, np.nan],
321318
'B': Series(list('aaad')).astype(
322-
'category', categories=cats)}).set_index('B')
319+
CDT(cats))}).set_index('B')
323320
assert_frame_equal(result, expected, check_index_type=True)
324321

325322
result = self.df2.reindex(Categorical(['a'], categories=cats))
326323
expected = DataFrame({'A': [0, 1, 5],
327324
'B': Series(list('aaa')).astype(
328-
'category', categories=cats)}).set_index('B')
325+
CDT(cats))}).set_index('B')
329326
assert_frame_equal(result, expected, check_index_type=True)
330327

331328
result = self.df2.reindex(['a', 'b', 'e'])
@@ -348,16 +345,15 @@ def test_reindexing(self):
348345
['a', 'd'], categories=cats, ordered=True))
349346
expected = DataFrame(
350347
{'A': [0, 1, 5, np.nan],
351-
'B': Series(list('aaad')).astype('category', categories=cats,
352-
ordered=True)}).set_index('B')
348+
'B': Series(list('aaad')).astype(
349+
CDT(cats, ordered=True))}).set_index('B')
353350
assert_frame_equal(result, expected, check_index_type=True)
354351

355352
result = self.df2.reindex(Categorical(
356353
['a', 'd'], categories=['a', 'd']))
357354
expected = DataFrame({'A': [0, 1, 5, np.nan],
358355
'B': Series(list('aaad')).astype(
359-
'category', categories=['a', 'd'
360-
])}).set_index('B')
356+
CDT(['a', 'd']))}).set_index('B')
361357
assert_frame_equal(result, expected, check_index_type=True)
362358

363359
# passed duplicate indexers are not allowed

‎pandas/tests/reshape/test_merge.py

+5-6
Original file line numberDiff line numberDiff line change
@@ -16,6 +16,7 @@
1616
from pandas.core.dtypes.common import is_categorical_dtype, is_object_dtype
1717
from pandas import DataFrame, Index, MultiIndex, Series, Categorical
1818
import pandas.util.testing as tm
19+
from pandas.api.types import CategoricalDtype as CDT
1920

2021

2122
N = 50
@@ -1414,16 +1415,15 @@ def left():
14141415
return DataFrame(
14151416
{'X': Series(np.random.choice(
14161417
['foo', 'bar'],
1417-
size=(10,))).astype('category', categories=['foo', 'bar']),
1418+
size=(10,))).astype(CDT(['foo', 'bar'])),
14181419
'Y': np.random.choice(['one', 'two', 'three'], size=(10,))})
14191420

14201421

14211422
@pytest.fixture
14221423
def right():
14231424
np.random.seed(1234)
14241425
return DataFrame(
1425-
{'X': Series(['foo', 'bar']).astype('category',
1426-
categories=['foo', 'bar']),
1426+
{'X': Series(['foo', 'bar']).astype(CDT(['foo', 'bar'])),
14271427
'Z': [1, 2]})
14281428

14291429

@@ -1468,9 +1468,8 @@ def test_other_columns(self, left, right):
14681468

14691469
@pytest.mark.parametrize(
14701470
'change', [lambda x: x,
1471-
lambda x: x.astype('category',
1472-
categories=['foo', 'bar', 'bah']),
1473-
lambda x: x.astype('category', ordered=True)])
1471+
lambda x: x.astype(CDT(['foo', 'bar', 'bah'])),
1472+
lambda x: x.astype(CDT(ordered=True))])
14741473
@pytest.mark.parametrize('how', ['inner', 'outer', 'left', 'right'])
14751474
def test_dtype_on_merged_different(self, change, how, left, right):
14761475
# our merging columns, X now has 2 different dtypes

‎pandas/tests/reshape/test_pivot.py

+5-4
Original file line numberDiff line numberDiff line change
@@ -1,3 +1,4 @@
1+
12
from datetime import datetime, date, timedelta
23

34
import pytest
@@ -13,6 +14,7 @@
1314
from pandas.compat import range, product
1415
import pandas.util.testing as tm
1516
from pandas.tseries.util import pivot_annual, isleapyear
17+
from pandas.api.types import CategoricalDtype as CDT
1618

1719

1820
class TestPivotTable(object):
@@ -98,13 +100,12 @@ def test_pivot_table_dropna_categoricals(self):
98100
'B': [1, 2, 3, 1, 2, 3, 1, 2, 3],
99101
'C': range(0, 9)})
100102

101-
df['A'] = df['A'].astype('category', ordered=False,
102-
categories=categories)
103+
df['A'] = df['A'].astype(CDT(categories, ordered=False))
103104
result_true = df.pivot_table(index='B', columns='A', values='C',
104105
dropna=True)
105106
expected_columns = Series(['a', 'b', 'c'], name='A')
106-
expected_columns = expected_columns.astype('category', ordered=False,
107-
categories=categories)
107+
expected_columns = expected_columns.astype(
108+
CDT(categories, ordered=False))
108109
expected_index = Series([1, 2, 3], name='B')
109110
expected_true = DataFrame([[0.0, 3.0, 6.0],
110111
[1.0, 4.0, 7.0],

‎pandas/tests/reshape/test_tile.py

+15-14
Original file line numberDiff line numberDiff line change
@@ -9,6 +9,7 @@
99
Interval, IntervalIndex, Categorical,
1010
cut, qcut, date_range)
1111
import pandas.util.testing as tm
12+
from pandas.api.types import CategoricalDtype as CDT
1213

1314
from pandas.core.algorithms import quantile
1415
import pandas.core.reshape.tile as tmod
@@ -299,7 +300,7 @@ def test_cut_return_intervals(self):
299300
exp_bins = np.linspace(0, 8, num=4).round(3)
300301
exp_bins[0] -= 0.008
301302
exp = Series(IntervalIndex.from_breaks(exp_bins, closed='right').take(
302-
[0, 0, 0, 1, 1, 1, 2, 2, 2])).astype('category', ordered=True)
303+
[0, 0, 0, 1, 1, 1, 2, 2, 2])).astype(CDT(ordered=True))
303304
tm.assert_series_equal(res, exp)
304305

305306
def test_qcut_return_intervals(self):
@@ -308,22 +309,22 @@ def test_qcut_return_intervals(self):
308309
exp_levels = np.array([Interval(-0.001, 2.664),
309310
Interval(2.664, 5.328), Interval(5.328, 8)])
310311
exp = Series(exp_levels.take([0, 0, 0, 1, 1, 1, 2, 2, 2])).astype(
311-
'category', ordered=True)
312+
CDT(ordered=True))
312313
tm.assert_series_equal(res, exp)
313314

314315
def test_series_retbins(self):
315316
# GH 8589
316317
s = Series(np.arange(4))
317318
result, bins = cut(s, 2, retbins=True)
318319
expected = Series(IntervalIndex.from_breaks(
319-
[-0.003, 1.5, 3], closed='right').repeat(2)).astype('category',
320-
ordered=True)
320+
[-0.003, 1.5, 3], closed='right').repeat(2)).astype(
321+
CDT(ordered=True))
321322
tm.assert_series_equal(result, expected)
322323

323324
result, bins = qcut(s, 2, retbins=True)
324325
expected = Series(IntervalIndex.from_breaks(
325-
[-0.001, 1.5, 3], closed='right').repeat(2)).astype('category',
326-
ordered=True)
326+
[-0.001, 1.5, 3], closed='right').repeat(2)).astype(
327+
CDT(ordered=True))
327328
tm.assert_series_equal(result, expected)
328329

329330
def test_qcut_duplicates_bin(self):
@@ -351,7 +352,7 @@ def test_single_quantile(self):
351352
result = qcut(s, 1)
352353
intervals = IntervalIndex([Interval(8.999, 9.0),
353354
Interval(8.999, 9.0)], closed='right')
354-
expected = Series(intervals).astype('category', ordered=True)
355+
expected = Series(intervals).astype(CDT(ordered=True))
355356
tm.assert_series_equal(result, expected)
356357

357358
s = Series([-9., -9.])
@@ -361,7 +362,7 @@ def test_single_quantile(self):
361362
result = qcut(s, 1)
362363
intervals = IntervalIndex([Interval(-9.001, -9.0),
363364
Interval(-9.001, -9.0)], closed='right')
364-
expected = Series(intervals).astype('category', ordered=True)
365+
expected = Series(intervals).astype(CDT(ordered=True))
365366
tm.assert_series_equal(result, expected)
366367

367368
s = Series([0., 0.])
@@ -371,7 +372,7 @@ def test_single_quantile(self):
371372
result = qcut(s, 1)
372373
intervals = IntervalIndex([Interval(-0.001, 0.0),
373374
Interval(-0.001, 0.0)], closed='right')
374-
expected = Series(intervals).astype('category', ordered=True)
375+
expected = Series(intervals).astype(CDT(ordered=True))
375376
tm.assert_series_equal(result, expected)
376377

377378
s = Series([9])
@@ -380,7 +381,7 @@ def test_single_quantile(self):
380381
tm.assert_series_equal(result, expected)
381382
result = qcut(s, 1)
382383
intervals = IntervalIndex([Interval(8.999, 9.0)], closed='right')
383-
expected = Series(intervals).astype('category', ordered=True)
384+
expected = Series(intervals).astype(CDT(ordered=True))
384385
tm.assert_series_equal(result, expected)
385386

386387
s = Series([-9])
@@ -389,7 +390,7 @@ def test_single_quantile(self):
389390
tm.assert_series_equal(result, expected)
390391
result = qcut(s, 1)
391392
intervals = IntervalIndex([Interval(-9.001, -9.0)], closed='right')
392-
expected = Series(intervals).astype('category', ordered=True)
393+
expected = Series(intervals).astype(CDT(ordered=True))
393394
tm.assert_series_equal(result, expected)
394395

395396
s = Series([0])
@@ -398,7 +399,7 @@ def test_single_quantile(self):
398399
tm.assert_series_equal(result, expected)
399400
result = qcut(s, 1)
400401
intervals = IntervalIndex([Interval(-0.001, 0.0)], closed='right')
401-
expected = Series(intervals).astype('category', ordered=True)
402+
expected = Series(intervals).astype(CDT(ordered=True))
402403
tm.assert_series_equal(result, expected)
403404

404405
def test_single_bin(self):
@@ -450,7 +451,7 @@ def test_datetime_cut(self):
450451
Timestamp('2013-01-02 08:00:00')),
451452
Interval(Timestamp('2013-01-02 08:00:00'),
452453
Timestamp('2013-01-03 00:00:00'))]))
453-
.astype('category', ordered=True))
454+
.astype(CDT(ordered=True)))
454455

455456
tm.assert_series_equal(result, expected)
456457

@@ -479,7 +480,7 @@ def test_datetime_bin(self):
479480
Series(IntervalIndex.from_intervals([
480481
Interval(Timestamp(bin_data[0]), Timestamp(bin_data[1])),
481482
Interval(Timestamp(bin_data[1]), Timestamp(bin_data[2]))]))
482-
.astype('category', ordered=True))
483+
.astype(CDT(ordered=True)))
483484

484485
for conv in [Timestamp, Timestamp, np.datetime64]:
485486
bins = [conv(v) for v in bin_data]

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