Description
import pandas as pd
import numpy as np
n = 5 # not a problem for n < 5
df = pd.DataFrame({
'x': pd.Categorical(np.repeat([1, 2, 3, 4], n), ordered=True)
})
df.sort_values('x', kind='mergesort')output:
x
0 1
1 1
2 1
3 1
4 1
8 2
7 2
9 2
5 2
6 2
10 3
11 3
12 3
13 3
14 3
18 4
15 4
16 4
17 4
19 4
Problem description
When sorting (using mergesort) a dataframe by an ordered categorical column, the sorting should be stable. In the example above x==2 and x==4 the values have been scrambled.
Expected Output
The index should remain in order since the column is already sorted.
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.11.1-gentoo
machine: x86_64
processor: Intel(R)
byteorder: little
LC_ALL: en_US.utf8
LANG: en_US.utf8
LOCALE: en_US.UTF-8
pandas: 0.20.2
pytest: 3.1.2
pip: 9.0.1
setuptools: 36.0.1
Cython: 0.25.2
numpy: 1.13.0
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: 1.6.2
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None