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Description
Pandas version checks
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I have checked that this issue has not already been reported.
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I have confirmed this bug exists on the latest version of pandas.
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
from io import StringIO
import pandas as pd
data = """a,a,a,b,c,c
q,r,s,t,u,v
1,2,3,4,5,6
7,8,9,10,11,12"""
pd.read_csv(StringIO(data), header=[1, 0])
Issue Description
pandas accepts non-increasing MultiIndex header arguments, but they don't work. For instance, the snippet above produces
NaN
a a.1 a.2 b c c.1
0 a a a b c c
1 q r s t u v
2 1 2 3 4 5 6
3 7 8 9 10 11 12
i.e., a DataFrame whose columns are
MultiIndex([(nan, 'a'),
(nan, 'a.1'),
(nan, 'a.2'),
(nan, 'b'),
(nan, 'c'),
(nan, 'c.1')],
)
Parsing the data with header=[0, 0] is also accepted, and behaves sensibly:
a b c
a a.1 a.2 b c c.1
0 q r s t u v
1 1 2 3 4 5 6
2 7 8 9 10 11 12
but I can't see a reason to support redundant header levels.
Expected Behavior
I propose that non-increasing header arguments raise a ValueError('header elements must be increasing') or something to that effect.
Installed Versions
INSTALLED VERSIONS
commit : 7c913d6
python : 3.8.13.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.0-27-generic
Version : #28-Ubuntu SMP Thu Apr 14 04:55:28 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_CA.UTF-8
LOCALE : en_CA.UTF-8
pandas : 1.5.0.dev0+786.g7c913d6b75
numpy : 1.21.5
pytz : 2022.1
dateutil : 2.8.2
pip : 22.0.4
setuptools : 62.0.0
Cython : 0.29.28
pytest : 7.1.1
hypothesis : 6.41.0
sphinx : 4.5.0
blosc : None
feather : None
xlsxwriter : 3.0.3
lxml.etree : 4.8.0
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 8.2.0
pandas_datareader: None
bs4 : 4.11.0
bottleneck : 1.3.4
brotli :
fastparquet : 0.8.0
fsspec : 2021.11.0
gcsfs : 2021.11.0
markupsafe : 2.1.1
matplotlib : 3.5.1
numba : 0.55.1
numexpr : 2.8.0
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 7.0.0
pyreadstat : 1.1.4
pyxlsb : 1.0.9
s3fs : 2021.11.0
scipy : 1.8.0
snappy :
sqlalchemy : 1.4.35
tables : 3.7.0
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 2.0.1
xlwt : 1.3.0
zstandard : None