Pandas: Requiring default index for to_feather() is unintuitive

[drkarthi]

Code Sample

import pandas as pd
df = pd.DataFrame({'a': [1,2,3,4], 'b': [5,6,7,8]} )
df = df.drop(1)
df.to_feather("test.feather")

Problem description

I saw documentation in the code requiring default index at: https://github.com/pandas-dev/pandas/blob/794be8c7ab6897b7206f2c6ec60d22fea2e440a3/pandas/io/feather_format.py#L46-L52

However, I think it is unintuitive to require the user to have a default index before writing to feather (for example this is not a requirement to writing to csv). Why is this a requirement? What are your thoughts about reindexing being the default?

Expected Output

Output of pd.show_versions()

INSTALLED VERSIONS

commit : None
python : 3.6.9.final.0
python-bits : 64
OS : Darwin
OS-release : 17.7.0
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 0.25.0
numpy : 1.17.0
pytz : 2019.2
dateutil : 2.8.0
pip : 19.2.2
setuptools : 41.0.1
Cython : None
pytest : 5.1.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 3.8.0
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.8.3 (dt dec pq3 ext lo64)
jinja2 : 2.8.1
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
gcsfs : None
lxml.etree : 3.8.0
matplotlib : 3.1.1
numexpr : 2.7.0
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 0.14.1
pytables : None
s3fs : None
scipy : 1.3.1
sqlalchemy : 1.3.7
tables : None
xarray : None
xlrd : None
xlwt : None
xlsxwriter : None

[jreback]

feather (which is just pyarrow under the hood) does not save the index, so round-tripping fails with a non-default index. this is a design decision of the format to make it simpler. parquet does allow saving of the index.

[drkarthi]

Got it, thanks for the info