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If Dataframe has index which timezone is set to dateutil.tz.tzlocal(), it could not be saved to parquet.

It might be related to #24310

Code Sample, a copy-pastable example

from dateutil.tz import tzlocal
ind = pd.date_range('2020-02-01','2020-04-14').tz_localize(tzlocal())
x = pd.DataFrame([[1,2]]*len(ind), index=ind, columns=['A','B'])
x.to_parquet('tmp.parquet')

Problem description

The code raises ValueError: Unable to convert timezone "tzlocal()" to string.

However saving to e.g. CSV works well:

x.to_csv('tmp.csv')

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit : None python : 3.7.1.final.0 python-bits : 64 OS : Darwin OS-release : 18.7.0 machine : x86_64 processor : i386 byteorder : little LC_ALL : en_US.UTF-8 LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.0.3 numpy : 1.18.2 pytz : 2019.3 dateutil : 2.8.1 pip : 20.0.2 setuptools : 42.0.1.post20191125 Cython : None pytest : 5.3.0 hypothesis : None sphinx : 2.2.0 blosc : None feather : None xlsxwriter : None lxml.etree : 4.4.1 html5lib : None pymysql : 0.9.3 psycopg2 : 2.8.5 (dt dec pq3 ext lo64) jinja2 : 2.10.1 IPython : 7.13.0 pandas_datareader: None bs4 : 4.6.3 bottleneck : None fastparquet : 0.3.2 gcsfs : None lxml.etree : 4.4.1 matplotlib : 3.1.3 numexpr : 2.7.0 odfpy : None openpyxl : None pandas_gbq : None pyarrow : 0.16.0 pytables : None pytest : 5.3.0 pyxlsb : None s3fs : 0.4.2 scipy : 1.3.1 sqlalchemy : 1.3.13 tables : 3.4.4 tabulate : None xarray : None xlrd : 1.1.0 xlwt : None xlsxwriter : None numba : 0.46.0

Comment From: jorisvandenbossche

@vfilimonov dateutil timezones are currently not supported by pyarrow, see https://issues.apache.org/jira/browse/ARROW-5248

So the best option, for now, is to convert the timezone to a datetime.timezone fixed offset of pytz timezone.

Comment From: vfilimonov

Thank you for quick response @jorisvandenbossche!

What would be the easiest way to convert index to fixed offset?

I could think of a workaround by iterating over index and parsing strings:

from dateutil.tz import tzlocal
ind = pd.date_range('2020-02-01','2020-04-14').tz_localize(tzlocal())

ind = [pd.Timestamp(str(_)) for _ in ind]

Comment From: jbrockmendel

@jorisvandenbossche is there any prospect of this being supported in pyarrow? if not it might make sense to add a helpful message for this case?