RangeIndex is converted to Int64Index on save to HDF5 (to_hdf)

[vfilimonov]

Hello, I'm not sure if it is an intended behavior or not, and I did not find any mention about this in the documentation or in the github issue tracker. I'm filing it - just in case it was not planned to work this way.

Problem description

On save to HDF5 file RangeIndex of pandas.DataFrame is converted to Int64Index (which could add quite some to the stored space for the long tables).

df = pd.DataFrame(np.random.randn(1000,2))
df.index

results in RangeIndex(start=0, stop=1000, step=1)

Then

df.to_hdf('tmp.h5', 'df')
df = pd.read_hdf('tmp.h5', 'df')
df.index

results in Int64Index([ 0, 1, ..., 999], dtype='int64', length=1000)

Output of pd.show_versions()

INSTALLED VERSIONS

commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 63 Stepping 2, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0
pytest: 3.3.2
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.27.3
numpy: 1.14.1
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.6.6
patsy: 0.5.0
dateutil: 2.6.1
pytz: 2018.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: None
matplotlib: 2.1.2
openpyxl: 2.4.10
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: 1.0.2
lxml: 4.1.1
bs4: 4.6.0
html5lib: 1.0.1
sqlalchemy: 1.2.1
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[max-sixty]

Is there a more efficient way of representing a range in HDF5?

[jreback]

duplicated of #8319

its not worth it trying to finese, this, rather just have an option to turn it off

[jreback]

PR's to fix are welcome!