Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

BUG: Large object array isin #16969

Closed
wants to merge 3 commits into from
Closed

BUG: Large object array isin #16969

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
3 commits
Select commit Hold shift + click to select a range
186607b
BUG #16012 - fix isin for large object arrays
Morgan243 Jul 15, 2017
4b59745
Linting errors; additional test clarification
Morgan243 Jul 18, 2017
31cb4b3
Removed unneeded details from whatsnew description
Morgan243 Jul 18, 2017
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.21.0.txt
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -204,3 +204,4 @@ Categorical
Other
^^^^^
- Bug in :func:`eval` where the ``inplace`` parameter was being incorrectly handled (:issue:`16732`)
- Bug when using :func:`isin` on a large object series and large comparison array (:issue:`16012`)
5 changes: 4 additions & 1 deletion pandas/core/algorithms.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -402,7 +402,10 @@ def isin(comps, values):
# work-around for numpy < 1.8 and comparisions on py3
# faster for larger cases to use np.in1d
f = lambda x, y: htable.ismember_object(x, values)
if (_np_version_under1p8 and compat.PY3) or len(comps) > 1000000:
# GH16012
# Ensure np.in1d doesn't get object types or it *may* throw an exception
if ((_np_version_under1p8 and compat.PY3) or len(comps) > 1000000 and
not is_object_dtype(comps)):
f = lambda x, y: np.in1d(x, y)
elif is_integer_dtype(comps):
try:
Expand Down
12 changes: 12 additions & 0 deletions pandas/tests/series/test_analytics.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1092,6 +1092,18 @@ def test_isin(self):
expected = Series([True, False, True, False, False, False, True, True])
assert_series_equal(result, expected)

# GH: 16012
# This specific issue has to have a series over 1e6 in len, but the
# comparison array (in_list) must be large enough so that numpy doesn't
# do a manual masking trick that will avoid this issue altogether
s = Series(list('abcdefghijk' * 10 ** 5))
# If numpy doesn't do the manual comparison/mask, these
# unorderable mixed types are what cause the exception in numpy
in_list = [-1, 'a', 'b', 'G', 'Y', 'Z', 'E',
'K', 'E', 'S', 'I', 'R', 'R'] * 6

assert s.isin(in_list).sum() == 200000

def test_isin_with_string_scalar(self):
# GH4763
s = Series(['A', 'B', 'C', 'a', 'B', 'B', 'A', 'C'])
Expand Down