Skip to content

BUG: sorting with large float and multiple columns incorrect #14944

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.

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

Closed
wants to merge 8 commits into from
Closed
Show file tree
Hide file tree
Changes from 3 commits
Commits
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
3 changes: 2 additions & 1 deletion pandas/core/algorithms.py
Original file line number Diff line number Diff line change
Expand Up @@ -343,7 +343,8 @@ def factorize(values, sort=False, order=None, na_sentinel=-1, size_hint=None):

table = hash_klass(size_hint or len(vals))
uniques = vec_klass()
labels = table.get_labels(vals, uniques, 0, na_sentinel, True)
check_nulls = not is_integer_dtype(values)
labels = table.get_labels(vals, uniques, 0, na_sentinel, check_nulls)

labels = _ensure_platform_int(labels)

Expand Down
20 changes: 18 additions & 2 deletions pandas/tests/frame/test_sorting.py
Original file line number Diff line number Diff line change
Expand Up @@ -6,11 +6,12 @@

from pandas.compat import lrange
from pandas import (DataFrame, Series, MultiIndex, Timestamp,
date_range)
date_range, NaT)

from pandas.util.testing import (assert_series_equal,
assert_frame_equal,
assertRaisesRegexp)
assertRaisesRegexp,
is_sorted)
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

you don't need to import the is_sorted


import pandas.util.testing as tm

Expand Down Expand Up @@ -491,3 +492,18 @@ def test_frame_column_inplace_sort_exception(self):

cp = s.copy()
cp.sort_values() # it works!

def test_sort_nat_values_in_int_column(self):

# GH 14922, sorting with large float and multiple columns incorrect
int_values = (2, int(NaT))
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

use np.iinfo(np.int64).min instead (and NaT) is already an int

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thought NaT is implicitly indicating what went wrong...

float_values = (2.0, -1.797693e308)

df = DataFrame(dict(int=int_values, float=float_values),
columns=["int", "float"])

df_sorted = df.sort_values(["int", "float"])
df_expected = DataFrame(dict(int=int_values[::-1], float=float_values[::-1]),
columns=["int", "float"], index=[1, 0])

assert_frame_equal(df_sorted, df_expected)