BUG: throwing error in interpolate depending on dtype of column names · Issue #33956 · pandas-dev/pandas (original) (raw)
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- I have confirmed this bug exists on the latest version of pandas.
- (optional) I have confirmed this bug exists on the master branch of pandas. (on 862db64, last commit where build works as of 20:42 2020-05-03).
Note: Please read this guide detailing how to provide the necessary information for us to reproduce your bug.
Code Sample, a copy-pastable example
df Out[6]: A B C 0 1.0 2.0 3.0 1 2.0 4.0 6.0 2 3.0 6.0 9.0 3 4.0 NaN NaN 4 NaN 8.0 NaN 5 5.0 10.0 30.0 df.interpolate(method='ffill', axis=1)
Throws an error ValueError: Index column must be numeric or datetime type when using ffill method other than linear. Try setting a numeric or datetime index column before interpolating. But the following code works:
df.columns = [1, 2, 3] df Out[9]: 1 2 3 0 1.0 2.0 3.0 1 2.0 4.0 6.0 2 3.0 6.0 9.0 3 4.0 NaN NaN 4 NaN 8.0 NaN 5 5.0 10.0 30.0 df.interpolate(method='ffill', axis=1) Out[10]: 1 2 3 0 1.0 2.0 3.0 1 2.0 4.0 6.0 2 3.0 6.0 9.0 3 4.0 6.0 9.0 4 4.0 8.0 9.0 5 5.0 10.0 30.0
Problem description
Throwing an error should not depend on the dtype of column names.
Expected Output
A B C0 1.0 2.0 3.0 1 2.0 4.0 6.0 2 3.0 6.0 9.0 3 4.0 6.0 9.0 4 4.0 8.0 9.0 5 5.0 10.0 30.0
Output of pd.show_versions()
pd.show_versions()
INSTALLED VERSIONS
------------------
commit : 862db6421256cb7a00ae3e88a4a6999347b76271
python : 3.8.2.final.0
python-bits : 64
OS : Linux
OS-release : 5.3.0-51-generic
Version : #44~18.04.2-Ubuntu SMP Thu Apr 23 14:27:18 UTC 2020
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.1.0.dev0+1463.g862db6421
numpy : 1.18.1
pytz : 2020.1
dateutil : 2.8.1
pip : 20.1
setuptools : 46.1.3.post20200325
Cython : 0.29.17
pytest : 5.4.1
hypothesis : 5.10.4
sphinx : 3.0.3
blosc : None
feather : None
xlsxwriter : 1.2.8
lxml.etree : 4.5.0
html5lib : 1.0.1
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.13.0
pandas_datareader: None
bs4 : 4.9.0
bottleneck : 1.3.2
fastparquet : 0.3.3
gcsfs : None
matplotlib : 3.2.1
numexpr : 2.7.1
odfpy : None
openpyxl : 3.0.3
pandas_gbq : None
pyarrow : 0.17.0
pytables : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.4.1
sqlalchemy : 1.3.16
tables : 3.6.1
tabulate : 0.8.7
xarray : 0.15.1
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.48.0