to_csv ignoring index=False (v0.22.0 only)

[morganbye]

Code Sample, a copy-pastable example if possible

            df.to_csv(output_path,
                       sep='\t',
                       header=False,
                       index=False,
                       float_format='%d'
                       )

Problem description

In Pandas v0.19 and 0.20 the above code would result in a tab-separated file, without an index column.

In v0.22 the index column is printed regardless of the index flag.

Expected Output

.tsv file without index column

Output of pd.show_versions()

Details

INSTALLED VERSIONS ------------------ commit: None python: 2.7.11.final.0 python-bits: 64 OS: Linux OS-release: 2.6.32-573.26.1.el6.x86_64 machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: en_CA.UTF-8 LOCALE: None.None

pandas: 0.22.0
pytest: None
pip: 10.0.0
setuptools: 38.5.1
Cython: 0.28.2
numpy: 1.14.2
scipy: None
xarray: None
IPython: None
sphinx: None
patsy: None
dateutil: 2.7.0
pandas_gbq: None
pandas_datareader: None

[TomAugspurger]

Can you make a reproducible example? http://stackoverflow.com/help/mcve

[morganbye]

Pandas 20

$ python
Python 2.7.11 (default, Dec  7 2016, 16:59:17)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-16)] on linux2
Type "help", "copyright", "credits" or "license" for more information.

>>> import pandas as pd

>>> pd.show_versions()

<snip>
pandas: 0.20.0
pip: 10.0.0
setuptools: 38.5.1
Cython: 0.28.2
numpy: 1.14.2
scipy: None
<snip>

>>> d = {'col1': [1, 2], 'col2': [3, 4]}

>>> df = pd.DataFrame(data=d)

>>> df
  col1  col2
0     1     3
1     2     4

>>> df.to_csv('/home/mbye/testing/pandas_20.tsv', sep='\t', index=False)

>>> with open('/home/mbye/testing/pandas_20', 'r') as fh:
...     print fh.read()
...
col1	col2
1	3
2	4

Pandas 22

$ python
Python 2.7.11 (default, Dec  7 2016, 16:59:17)
[GCC 4.4.7 20120313 (Red Hat 4.4.7-16)] on linux2
Type "help", "copyright", "credits" or "license" for more information.

>>> import pandas as pd

>>> pd.show_versions()

INSTALLED VERSIONS
------------------
<snip>
pandas: 0.22.0
pip: 10.0.0
setuptools: 38.5.1
Cython: 0.28.2
numpy: 1.14.2
scipy: None
<snip>


>>> d = {'col1': [1, 2], 'col2': [3, 4]}

>>> df = pd.DataFrame(data=d)

>>> df
  col1  col2
0     1     3
1     2     4

>>> df.to_csv('/home/mbye/testing/pandas_22.tsv', sep='\t', index=False)

>>> with open('/home/mbye/testing/pandas_22', 'r') as fh:
...     print fh.read()
...
index	col1	col2
0	1	3
1	2	4

[WillAyd]

It looks like you are writing a file with a .tsv extension but reading a file without that - is that intentional?

FWIW I'm not able to reproduce on master

[morganbye]

Sorry about that, that's just a bad copy/paste job on my part. The open command does actually have .tsv in my console.

[WillAyd]

Hmm I just tried on pandas v0.22 and python2.7 and everything worked fine:

In [7]: from StringIO import StringIO
In [8]: buf = StringIO()
In [9]: df.to_csv(buf, sep='\t', index=False)
In [10]: buf.seek(0)
In [11]: buf.read()
Out[11]: 'col1\tcol2\n1\t3\n2\t4\n'

Are you seeing the same issue on master?

Details

INSTALLED VERSIONS

commit: None
python: 2.7.14.final.0
python-bits: 64
OS: Darwin
OS-release: 17.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: None.None

pandas: 0.22.0
pytest: None
pip: 9.0.1
setuptools: 38.5.1
Cython: 0.27.3
numpy: 1.14.0
scipy: None
pyarrow: None
xarray: None
IPython: 5.5.0
sphinx: None
patsy: None
dateutil: 2.6.1
pytz: 2018.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: None
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: None
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[morganbye]

Sorry guys, I'm closing this issue.

After Will's testing I went back and made another clean venv and got it working across pandas 19, 20 and 22. The problem is as soon as I to add the other libraries. Somehow, one of the modules I'm pulling from the work eggserver is somehow actually overwriting the Pandas config.

That's clearly not a Pandas issue but an insane developer.