Description
Code Sample, a copy-pastable example if possible
# Your code here
import pandas as pd
pd.np.random.seed(0)
(
pd.DataFrame(pd.np.random.rand(10, 5), columns=['a', 'b', 'c', 'd', 'e'])
.assign(b=lambda df: (df.b*10).astype(int))
.set_index(['a', 'b', 'c'])
.sort_index(axis=0, level=['b', 'a'])
)
Out[96]:
d e
a b c
0.087129 0 0.832620 0.778157 0.870012
0.639921 1 0.944669 0.521848 0.414662
0.670638 2 0.128926 0.315428 0.363711
0.359508 4 0.697631 0.060225 0.666767
0.645894 4 0.891773 0.963663 0.383442
0.791725 5 0.568045 0.925597 0.071036
0.617635 6 0.616934 0.943748 0.681820
0.264556 7 0.456150 0.568434 0.018790
0.978618 7 0.461479 0.780529 0.118274
0.548814 7 0.602763 0.544883 0.423655Problem description
I don't understand why the a index is not sorted (see the b=7 rows).
Indeed, set_index does not seem to take into account levels not aligned with dataframe indexes. Since index is ['a', 'b', 'c'] it can only sort with levels=['a'], levels=['a', 'b'], levels=['a', 'b', 'c'], levels=['b'], levels=['b', 'c'], levels=['c'].
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https://pandas-docs.github.io/pandas-docs-travis/
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Expected Output
pd.np.random.seed(0)
(
pd.DataFrame(pd.np.random.rand(10, 5), columns=['a', 'b', 'c', 'd', 'e'])
.assign(b=lambda df: (df.b*10).astype(int))
.sort_values(['b', 'a'])
.set_index(['a', 'b', 'c'])
)
Out[104]:
d e
a b c
0.087129 0 0.832620 0.778157 0.870012
0.639921 1 0.944669 0.521848 0.414662
0.670638 2 0.128926 0.315428 0.363711
0.359508 4 0.697631 0.060225 0.666767
0.645894 4 0.891773 0.963663 0.383442
0.791725 5 0.568045 0.925597 0.071036
0.617635 6 0.616934 0.943748 0.681820
0.264556 7 0.456150 0.568434 0.018790
0.548814 7 0.602763 0.544883 0.423655
0.978618 7 0.461479 0.780529 0.118274
Output of pd.show_versions()
pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.5.final.0
python-bits: 64
OS: Darwin
OS-release: 15.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: fr_FR.UTF-8
pandas: 0.23.2
pytest: 3.6.1
pip: 18.0
setuptools: 40.4.3
Cython: None
numpy: 1.14.3
scipy: 1.0.1
pyarrow: None
xarray: None
IPython: 7.0.1
sphinx: None
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.2.2
openpyxl: None
xlrd: 1.1.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.9999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None