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.

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

DataFrame.xs("key", axis=1, drop_level=False) still dropping level #19056

Open
boulund opened this issue Jan 3, 2018 · 3 comments

Comments

Projects
None yet
5 participants
@boulund
Copy link

commented Jan 3, 2018

Code Sample, a copy-pastable example if possible

df = pd.DataFrame([[1, 2, 3], [2, 4, 6]], columns=["type1_subtype1_subsubtype1", "type1_subtype1_subsubtype2", "type2_subtype1_subsubtype2"], index=["rowtype_rowsubtype1_rowlevel1", "row_rowlevel0_rowlevel1"])
df.columns = d.columns.str.split("_", expand=True).rename(["Sample_type", "Subtype", "SubSubtype"])
df.index = d.index.str.split("_", expand=True).rename(["Rowtype", "rowsubtype", "rowlevel"])
print("Incorrect behavior:")
print(df.xs("type1", axis=1, drop_level=False))
print("Expected output:")
print(df.transpose().xs("type1", drop_level=False).transpose())

Problem description

I checked if there was a previous issue about this in the issue tracker but my searches gave nothing similar.

It appears that drop_level=False doesn't work as intended when taking a cross section along axis=1. Current workaround is to transpose the dataframe, then do the cross section, and then transpose it back again (as in my example above).

Expected Output

Sample_type                         type1            
Subtype                          subtype1            
SubSubtype                    subsubtype1 subsubtype2
Rowtype rowsubtype  rowlevel                         
rowtype rowsubtype1 rowlevel1           1           2
row     rowlevel0   rowlevel1           2           4

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Linux
OS-release: 3.10.0-693.11.1.el7.x86_64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.1
pytest: 3.0.7
pip: 9.0.1
setuptools: 36.5.0.post20170921
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.2
feather: 0.3.1
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
None

@tothandor

This comment has been minimized.

Copy link

commented Mar 1, 2018

I can confirm that for Pandas version 0.22 (Python 2.7 64-bit).

@simonjayhawkins

This comment has been minimized.

Copy link
Member

commented Dec 21, 2018

#6507 maybe related.

drop_level=False also ignored on index when fully specified tuple..

import pandas as pd
df = pd.DataFrame([[1, 2, 3], [2, 4, 6]], columns=["type1_subtype1_subsubtype1", "type1_subtype1_subsubtype2", "type2_subtype1_subsubtype2"], index=["rowtype_rowsubtype1_rowlevel1", "row_rowlevel0_rowlevel1"])
df.columns = df.columns.str.split("_", expand=True).rename(["Sample_type", "Subtype", "SubSubtype"])
df.index = df.index.str.split("_", expand=True).rename(["Rowtype", "rowsubtype", "rowlevel"])
df.xs(('row','rowlevel0','rowlevel1'), drop_level=False)
Sample_type  Subtype   SubSubtype 
type1        subtype1  subsubtype1    2
                       subsubtype2    4
type2        subtype1  subsubtype2    6
Name: (row, rowlevel0, rowlevel1), dtype: int64
@bicarlsen

This comment has been minimized.

Copy link

commented Apr 28, 2019

I am having the same issue for Pandas version 0.23.0 (Python v 3.6.5 64-bit)

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
You can’t perform that action at this time.