forked from pandas-dev/pandas
-
Notifications
You must be signed in to change notification settings - Fork 3
/
Copy pathtest_boolean.py
621 lines (460 loc) · 16 KB
/
test_boolean.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
# coding=utf-8
# pylint: disable-msg=E1101,W0612
import numpy as np
import pytest
from pandas.compat import lrange, range
from pandas.core.dtypes.common import is_integer
import pandas as pd
from pandas import Index, Series, Timestamp, date_range, isna
from pandas.core.indexing import IndexingError
import pandas.util.testing as tm
from pandas.util.testing import assert_series_equal
from pandas.tseries.offsets import BDay
def test_getitem_boolean(test_data):
s = test_data.series
mask = s > s.median()
# passing list is OK
result = s[list(mask)]
expected = s[mask]
assert_series_equal(result, expected)
tm.assert_index_equal(result.index, s.index[mask])
def test_getitem_boolean_empty():
s = Series([], dtype=np.int64)
s.index.name = 'index_name'
s = s[s.isna()]
assert s.index.name == 'index_name'
assert s.dtype == np.int64
# GH5877
# indexing with empty series
s = Series(['A', 'B'])
expected = Series(np.nan, index=['C'], dtype=object)
result = s[Series(['C'], dtype=object)]
assert_series_equal(result, expected)
s = Series(['A', 'B'])
expected = Series(dtype=object, index=Index([], dtype='int64'))
result = s[Series([], dtype=object)]
assert_series_equal(result, expected)
# invalid because of the boolean indexer
# that's empty or not-aligned
with pytest.raises(IndexingError):
s[Series([], dtype=bool)]
with pytest.raises(IndexingError):
s[Series([True], dtype=bool)]
def test_getitem_boolean_object(test_data):
# using column from DataFrame
s = test_data.series
mask = s > s.median()
omask = mask.astype(object)
# getitem
result = s[omask]
expected = s[mask]
assert_series_equal(result, expected)
# setitem
s2 = s.copy()
cop = s.copy()
cop[omask] = 5
s2[mask] = 5
assert_series_equal(cop, s2)
# nans raise exception
omask[5:10] = np.nan
pytest.raises(Exception, s.__getitem__, omask)
pytest.raises(Exception, s.__setitem__, omask, 5)
def test_getitem_setitem_boolean_corner(test_data):
ts = test_data.ts
mask_shifted = ts.shift(1, freq=BDay()) > ts.median()
# these used to raise...??
pytest.raises(Exception, ts.__getitem__, mask_shifted)
pytest.raises(Exception, ts.__setitem__, mask_shifted, 1)
# ts[mask_shifted]
# ts[mask_shifted] = 1
pytest.raises(Exception, ts.loc.__getitem__, mask_shifted)
pytest.raises(Exception, ts.loc.__setitem__, mask_shifted, 1)
# ts.loc[mask_shifted]
# ts.loc[mask_shifted] = 2
def test_setitem_boolean(test_data):
mask = test_data.series > test_data.series.median()
# similar indexed series
result = test_data.series.copy()
result[mask] = test_data.series * 2
expected = test_data.series * 2
assert_series_equal(result[mask], expected[mask])
# needs alignment
result = test_data.series.copy()
result[mask] = (test_data.series * 2)[0:5]
expected = (test_data.series * 2)[0:5].reindex_like(test_data.series)
expected[-mask] = test_data.series[mask]
assert_series_equal(result[mask], expected[mask])
def test_get_set_boolean_different_order(test_data):
ordered = test_data.series.sort_values()
# setting
copy = test_data.series.copy()
copy[ordered > 0] = 0
expected = test_data.series.copy()
expected[expected > 0] = 0
assert_series_equal(copy, expected)
# getting
sel = test_data.series[ordered > 0]
exp = test_data.series[test_data.series > 0]
assert_series_equal(sel, exp)
def test_where_unsafe_int(sint_dtype):
s = Series(np.arange(10), dtype=sint_dtype)
mask = s < 5
s[mask] = lrange(2, 7)
expected = Series(lrange(2, 7) + lrange(5, 10), dtype=sint_dtype)
assert_series_equal(s, expected)
def test_where_unsafe_float(float_dtype):
s = Series(np.arange(10), dtype=float_dtype)
mask = s < 5
s[mask] = lrange(2, 7)
expected = Series(lrange(2, 7) + lrange(5, 10), dtype=float_dtype)
assert_series_equal(s, expected)
@pytest.mark.parametrize("dtype", [np.int64, np.float64])
def test_where_unsafe_upcast(dtype):
s = Series(np.arange(10), dtype=dtype)
values = [2.5, 3.5, 4.5, 5.5, 6.5]
mask = s < 5
expected = Series(values + lrange(5, 10), dtype="float64")
s[mask] = values
assert_series_equal(s, expected)
@pytest.mark.parametrize("dtype", [
np.int8, np.int16, np.int32, np.float32
])
def test_where_unsafe_itemsize_fail(dtype):
# Can't do these, as we are forced to change the
# item size of the input to something we cannot.
s = Series(np.arange(10), dtype=dtype)
mask = s < 5
values = [2.5, 3.5, 4.5, 5.5, 6.5]
pytest.raises(Exception, s.__setitem__, tuple(mask), values)
def test_where_unsafe():
# see gh-9731
s = Series(np.arange(10), dtype="int64")
values = [2.5, 3.5, 4.5, 5.5]
mask = s > 5
expected = Series(lrange(6) + values, dtype="float64")
s[mask] = values
assert_series_equal(s, expected)
# see gh-3235
s = Series(np.arange(10), dtype='int64')
mask = s < 5
s[mask] = lrange(2, 7)
expected = Series(lrange(2, 7) + lrange(5, 10), dtype='int64')
assert_series_equal(s, expected)
assert s.dtype == expected.dtype
s = Series(np.arange(10), dtype='int64')
mask = s > 5
s[mask] = [0] * 4
expected = Series([0, 1, 2, 3, 4, 5] + [0] * 4, dtype='int64')
assert_series_equal(s, expected)
s = Series(np.arange(10))
mask = s > 5
with pytest.raises(ValueError):
s[mask] = [5, 4, 3, 2, 1]
with pytest.raises(ValueError):
s[mask] = [0] * 5
# dtype changes
s = Series([1, 2, 3, 4])
result = s.where(s > 2, np.nan)
expected = Series([np.nan, np.nan, 3, 4])
assert_series_equal(result, expected)
# GH 4667
# setting with None changes dtype
s = Series(range(10)).astype(float)
s[8] = None
result = s[8]
assert isna(result)
s = Series(range(10)).astype(float)
s[s > 8] = None
result = s[isna(s)]
expected = Series(np.nan, index=[9])
assert_series_equal(result, expected)
def test_where_raise_on_error_deprecation():
# gh-14968
# deprecation of raise_on_error
s = Series(np.random.randn(5))
cond = s > 0
with tm.assert_produces_warning(FutureWarning):
s.where(cond, raise_on_error=True)
with tm.assert_produces_warning(FutureWarning):
s.mask(cond, raise_on_error=True)
def test_where():
s = Series(np.random.randn(5))
cond = s > 0
rs = s.where(cond).dropna()
rs2 = s[cond]
assert_series_equal(rs, rs2)
rs = s.where(cond, -s)
assert_series_equal(rs, s.abs())
rs = s.where(cond)
assert (s.shape == rs.shape)
assert (rs is not s)
# test alignment
cond = Series([True, False, False, True, False], index=s.index)
s2 = -(s.abs())
expected = s2[cond].reindex(s2.index[:3]).reindex(s2.index)
rs = s2.where(cond[:3])
assert_series_equal(rs, expected)
expected = s2.abs()
expected.iloc[0] = s2[0]
rs = s2.where(cond[:3], -s2)
assert_series_equal(rs, expected)
def test_where_error():
s = Series(np.random.randn(5))
cond = s > 0
pytest.raises(ValueError, s.where, 1)
pytest.raises(ValueError, s.where, cond[:3].values, -s)
# GH 2745
s = Series([1, 2])
s[[True, False]] = [0, 1]
expected = Series([0, 2])
assert_series_equal(s, expected)
# failures
pytest.raises(ValueError, s.__setitem__, tuple([[[True, False]]]),
[0, 2, 3])
pytest.raises(ValueError, s.__setitem__, tuple([[[True, False]]]),
[])
@pytest.mark.parametrize('klass', [list, tuple, np.array, Series])
def test_where_array_like(klass):
# see gh-15414
s = Series([1, 2, 3])
cond = [False, True, True]
expected = Series([np.nan, 2, 3])
result = s.where(klass(cond))
assert_series_equal(result, expected)
@pytest.mark.parametrize('cond', [
[1, 0, 1],
Series([2, 5, 7]),
["True", "False", "True"],
[Timestamp("2017-01-01"), pd.NaT, Timestamp("2017-01-02")]
])
def test_where_invalid_input(cond):
# see gh-15414: only boolean arrays accepted
s = Series([1, 2, 3])
msg = "Boolean array expected for the condition"
with pytest.raises(ValueError, match=msg):
s.where(cond)
msg = "Array conditional must be same shape as self"
with pytest.raises(ValueError, match=msg):
s.where([True])
def test_where_ndframe_align():
msg = "Array conditional must be same shape as self"
s = Series([1, 2, 3])
cond = [True]
with pytest.raises(ValueError, match=msg):
s.where(cond)
expected = Series([1, np.nan, np.nan])
out = s.where(Series(cond))
tm.assert_series_equal(out, expected)
cond = np.array([False, True, False, True])
with pytest.raises(ValueError, match=msg):
s.where(cond)
expected = Series([np.nan, 2, np.nan])
out = s.where(Series(cond))
tm.assert_series_equal(out, expected)
def test_where_setitem_invalid():
# GH 2702
# make sure correct exceptions are raised on invalid list assignment
# slice
s = Series(list('abc'))
with pytest.raises(ValueError):
s[0:3] = list(range(27))
s[0:3] = list(range(3))
expected = Series([0, 1, 2])
assert_series_equal(s.astype(np.int64), expected, )
# slice with step
s = Series(list('abcdef'))
with pytest.raises(ValueError):
s[0:4:2] = list(range(27))
s = Series(list('abcdef'))
s[0:4:2] = list(range(2))
expected = Series([0, 'b', 1, 'd', 'e', 'f'])
assert_series_equal(s, expected)
# neg slices
s = Series(list('abcdef'))
with pytest.raises(ValueError):
s[:-1] = list(range(27))
s[-3:-1] = list(range(2))
expected = Series(['a', 'b', 'c', 0, 1, 'f'])
assert_series_equal(s, expected)
# list
s = Series(list('abc'))
with pytest.raises(ValueError):
s[[0, 1, 2]] = list(range(27))
s = Series(list('abc'))
with pytest.raises(ValueError):
s[[0, 1, 2]] = list(range(2))
# scalar
s = Series(list('abc'))
s[0] = list(range(10))
expected = Series([list(range(10)), 'b', 'c'])
assert_series_equal(s, expected)
@pytest.mark.parametrize('size', range(2, 6))
@pytest.mark.parametrize('mask', [
[True, False, False, False, False],
[True, False],
[False]
])
@pytest.mark.parametrize('item', [
2.0, np.nan, np.finfo(np.float).max, np.finfo(np.float).min
])
# Test numpy arrays, lists and tuples as the input to be
# broadcast
@pytest.mark.parametrize('box', [
lambda x: np.array([x]),
lambda x: [x],
lambda x: (x,)
])
def test_broadcast(size, mask, item, box):
selection = np.resize(mask, size)
data = np.arange(size, dtype=float)
# Construct the expected series by taking the source
# data or item based on the selection
expected = Series([item if use_item else data[
i] for i, use_item in enumerate(selection)])
s = Series(data)
s[selection] = box(item)
assert_series_equal(s, expected)
s = Series(data)
result = s.where(~selection, box(item))
assert_series_equal(result, expected)
s = Series(data)
result = s.mask(selection, box(item))
assert_series_equal(result, expected)
def test_where_inplace():
s = Series(np.random.randn(5))
cond = s > 0
rs = s.copy()
rs.where(cond, inplace=True)
assert_series_equal(rs.dropna(), s[cond])
assert_series_equal(rs, s.where(cond))
rs = s.copy()
rs.where(cond, -s, inplace=True)
assert_series_equal(rs, s.where(cond, -s))
def test_where_dups():
# GH 4550
# where crashes with dups in index
s1 = Series(list(range(3)))
s2 = Series(list(range(3)))
comb = pd.concat([s1, s2])
result = comb.where(comb < 2)
expected = Series([0, 1, np.nan, 0, 1, np.nan],
index=[0, 1, 2, 0, 1, 2])
assert_series_equal(result, expected)
# GH 4548
# inplace updating not working with dups
comb[comb < 1] = 5
expected = Series([5, 1, 2, 5, 1, 2], index=[0, 1, 2, 0, 1, 2])
assert_series_equal(comb, expected)
comb[comb < 2] += 10
expected = Series([5, 11, 2, 5, 11, 2], index=[0, 1, 2, 0, 1, 2])
assert_series_equal(comb, expected)
def test_where_numeric_with_string():
# GH 9280
s = pd.Series([1, 2, 3])
w = s.where(s > 1, 'X')
assert not is_integer(w[0])
assert is_integer(w[1])
assert is_integer(w[2])
assert isinstance(w[0], str)
assert w.dtype == 'object'
w = s.where(s > 1, ['X', 'Y', 'Z'])
assert not is_integer(w[0])
assert is_integer(w[1])
assert is_integer(w[2])
assert isinstance(w[0], str)
assert w.dtype == 'object'
w = s.where(s > 1, np.array(['X', 'Y', 'Z']))
assert not is_integer(w[0])
assert is_integer(w[1])
assert is_integer(w[2])
assert isinstance(w[0], str)
assert w.dtype == 'object'
def test_where_timedelta_coerce():
s = Series([1, 2], dtype='timedelta64[ns]')
expected = Series([10, 10])
mask = np.array([False, False])
rs = s.where(mask, [10, 10])
assert_series_equal(rs, expected)
rs = s.where(mask, 10)
assert_series_equal(rs, expected)
rs = s.where(mask, 10.0)
assert_series_equal(rs, expected)
rs = s.where(mask, [10.0, 10.0])
assert_series_equal(rs, expected)
rs = s.where(mask, [10.0, np.nan])
expected = Series([10, None], dtype='object')
assert_series_equal(rs, expected)
def test_where_datetime_conversion():
s = Series(date_range('20130102', periods=2))
expected = Series([10, 10])
mask = np.array([False, False])
rs = s.where(mask, [10, 10])
assert_series_equal(rs, expected)
rs = s.where(mask, 10)
assert_series_equal(rs, expected)
rs = s.where(mask, 10.0)
assert_series_equal(rs, expected)
rs = s.where(mask, [10.0, 10.0])
assert_series_equal(rs, expected)
rs = s.where(mask, [10.0, np.nan])
expected = Series([10, None], dtype='object')
assert_series_equal(rs, expected)
# GH 15701
timestamps = ['2016-12-31 12:00:04+00:00',
'2016-12-31 12:00:04.010000+00:00']
s = Series([pd.Timestamp(t) for t in timestamps])
rs = s.where(Series([False, True]))
expected = Series([pd.NaT, s[1]])
assert_series_equal(rs, expected)
def test_where_dt_tz_values(tz_naive_fixture):
ser1 = pd.Series(pd.DatetimeIndex(['20150101', '20150102', '20150103'],
tz=tz_naive_fixture))
ser2 = pd.Series(pd.DatetimeIndex(['20160514', '20160515', '20160516'],
tz=tz_naive_fixture))
mask = pd.Series([True, True, False])
result = ser1.where(mask, ser2)
exp = pd.Series(pd.DatetimeIndex(['20150101', '20150102', '20160516'],
tz=tz_naive_fixture))
assert_series_equal(exp, result)
def test_mask():
# compare with tested results in test_where
s = Series(np.random.randn(5))
cond = s > 0
rs = s.where(~cond, np.nan)
assert_series_equal(rs, s.mask(cond))
rs = s.where(~cond)
rs2 = s.mask(cond)
assert_series_equal(rs, rs2)
rs = s.where(~cond, -s)
rs2 = s.mask(cond, -s)
assert_series_equal(rs, rs2)
cond = Series([True, False, False, True, False], index=s.index)
s2 = -(s.abs())
rs = s2.where(~cond[:3])
rs2 = s2.mask(cond[:3])
assert_series_equal(rs, rs2)
rs = s2.where(~cond[:3], -s2)
rs2 = s2.mask(cond[:3], -s2)
assert_series_equal(rs, rs2)
pytest.raises(ValueError, s.mask, 1)
pytest.raises(ValueError, s.mask, cond[:3].values, -s)
# dtype changes
s = Series([1, 2, 3, 4])
result = s.mask(s > 2, np.nan)
expected = Series([1, 2, np.nan, np.nan])
assert_series_equal(result, expected)
# see gh-21891
s = Series([1, 2])
res = s.mask([True, False])
exp = Series([np.nan, 2])
tm.assert_series_equal(res, exp)
def test_mask_inplace():
s = Series(np.random.randn(5))
cond = s > 0
rs = s.copy()
rs.mask(cond, inplace=True)
assert_series_equal(rs.dropna(), s[~cond])
assert_series_equal(rs, s.mask(cond))
rs = s.copy()
rs.mask(cond, -s, inplace=True)
assert_series_equal(rs, s.mask(cond, -s))