Closed
Description
Output from running tests and troubleshooting
probably related to having numpy beta release or freshish numexpr...
$> nosetests -s -v --pdb pandas/tests/test_expressions.py
...
test_integer_arithmetic (pandas.tests.test_expressions.TestExpressions) ... > /home/yoh/deb/gits/pkg-exppsy/pandas/pandas/util/testing.py(1018)raise_assert_detail()
-> raise AssertionError(msg)
*(Pdb) print msg
DataFrame.iloc[:, 0] are different
DataFrame.iloc[:, 0] values are different (85.16148 %)
[left]: [2565992168703393792, 2110287360296998863, 0, 0, 2644539488379390509, -5278486589563110205, -4689350456247753643, 8450172506621111015, -2101438300051996672, 8028209804145959321, 302875106592253, -5278486589563110205, -4053175462519618527, -4071272324936764365, 0, 0, 0, 256, 8450172506621111015, 0, -145357957422043229, 3030756035345000135, 256, 0, -4071272324936764365, -5278486589563110205, -2863221430593058543, 0, 0, 0, 4951460147845608313, 0, -1595931050845505211, -5821812116355782473, -6284992600390200471, 2435553365352800019, -1595931050845505211, -4053175462519618527, 0, 3792227444683241861, -6776596920136667815, -5821812116355782473, 0, -8795647696940200745, 4593512421086651489, 256, 0, 0, 2644539488379390509, -5821812116355782473, -7924192819420782515, 1826852818786091687, 0, 2110287360296998863, -2559158286230232783, -4689350456247753643, -6646187150092009472, 8028209804145959321, 0, 437893890380859375, 0, -5278486589563110205, 0, 2467972595799031808, 2604998672350111773, -4689350456247753643, 7437354637604294721, 0, 285311670611, 5529354540715494413, 2435553365352800019, -1595931050845505211, 256, 823543, -2559158286230232783, 0, -3660930864499998817, 0, -4642015662142636065, -4071272324936764365, 4611686018427387904, 285311670611, 1, 0, 2565992168703393792, 8028209804145959321, -145357957422043229, 8450172506621111015, -5821812116355782473, 0, -4675932718989443137, 8037740809528595931, -4071272324936764365, 0, 6353754964178307979, 0, -1595931050845505211, -1595931050845505211, -3264474685660004015, 2823291043684304491, ...]
[right]: [-9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 302875106592253, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 256, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 256, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 256, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 437893890380859375, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 285311670611, -9223372036854775808, -9223372036854775808, -9223372036854775808, 256, 823543, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, 285311670611, 1, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, -9223372036854775808, ...]
(Pdb) up
> /home/yoh/deb/gits/pkg-exppsy/pandas/pandas/src/testing.pyx(173)pandas._testing.assert_almost_equal (pandas/src/testing.c:3274)()
-> raise_assert_detail(obj, msg, lobj, robj)
(Pdb)
> /home/yoh/deb/gits/pkg-exppsy/pandas/pandas/src/testing.pyx(59)pandas._testing.assert_almost_equal (pandas/src/testing.c:4156)()
-> cpdef assert_almost_equal(a, b,
(Pdb)
> /home/yoh/deb/gits/pkg-exppsy/pandas/pandas/util/testing.py(1181)assert_series_equal()
-> obj='{0}'.format(obj))
(Pdb)
> /home/yoh/deb/gits/pkg-exppsy/pandas/pandas/util/testing.py(1313)assert_frame_equal()
-> obj='DataFrame.iloc[:, {0}]'.format(i))
(Pdb)
> /home/yoh/deb/gits/pkg-exppsy/pandas/pandas/tests/test_expressions.py(100)run_arithmetic_test()
-> assert_func(expected, result)
(Pdb) p df
A B C D
0 30 89 97 21
1 47 22 16 80
2 78 23 84 33
3 88 25 61 59
4 61 1 41 96
5 27 67 76 98
6 37 13 13 82
7 23 60 93 1
8 20 6 18 90
9 89 97 27 73
10 13 95 37 38
11 27 53 70 77
12 33 51 44 39
13 43 89 95 5
14 36 84 51 97
15 44 8 82 31
16 84 18 50 35
17 4 52 74 37
18 23 52 73 42
19 76 99 11 67
20 59 95 87 68
21 55 18 89 73
22 4 26 64 19
23 94 59 47 36
24 43 79 37 26
25 27 42 41 84
26 17 30 4 3
27 24 37 63 88
28 66 14 92 86
29 52 38 27 97
... .. .. .. ..
9971 25 13 53 68
9972 9 46 89 93
9973 70 53 47 33
9974 10 30 47 3
9975 98 15 98 43
9976 34 5 53 76
9977 21 29 65 95
9978 30 83 67 82
9979 52 1 58 17
9980 4 84 38 79
9981 83 96 57 12
9982 13 38 93 72
9983 58 64 24 13
9984 18 46 5 43
9985 70 84 88 45
9986 79 94 57 29
9987 18 31 63 57
9988 58 90 99 5
9989 8 88 77 55
9990 46 12 61 61
9991 69 70 96 45
9992 71 67 48 25
9993 77 68 46 16
9994 88 55 80 37
9995 6 93 76 73
9996 11 68 45 52
9997 57 79 3 69
9998 63 48 79 8
9999 11 5 70 16
10000 10 32 32 88
[10001 rows x 4 columns]
(Pdb) p op
<function pow at 0x7efedaaad758>
Problem description
Not sure what to blame here -- numexpr or numpy or ... What would you expect while trying to get e.g. 30**30? max for int of original pow base type?
Output of pd.show_versions()
# Paste the output here pd.show_versions() here
$> ./ci/print_versions.py
INSTALLED VERSIONS
commit: ad13f08
python: 2.7.13.candidate.1
python-bits: 64
OS: Linux
OS-release: 4.8.0-1-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None
pandas: 0.19.0+git14-ga40e185
nose: 1.3.7
pip: 8.1.2
setuptools: 28.7.1
Cython: 0.25.2b0
numpy: 1.12.0b1
scipy: 0.18.1
statsmodels: 0.8.0rc1
xarray: None
IPython: 5.1.0
sphinx: 1.4.8
patsy: 0.4.1+dev
dateutil: 2.5.3
pytz: 2015.7
blosc: None
bottleneck: None
tables: 3.3.0
numexpr: 2.6.1
feather: None
matplotlib: 1.5.3
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 0.7.5
xlsxwriter: None
lxml: 3.6.4
bs4: 4.5.1
html5lib: 0.999
httplib2: 0.9.2
apiclient: 1.5.2
sqlalchemy: 1.0.15
pymysql: None
psycopg2: 2.6.2 (dt dec mx pq3 ext lo64)
jinja2: 2.8
s3fs: None
pandas_datareader: None