The data analysis sandbox for JPX
Project description
====== jpxlab
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The data analysis sandbox for JPX
- Free software: MIT license
Features
- Convert the historical data of FLEX Historical
Usage: download
- Prerequisites: You have to contact with JPX's account manager and get FTP account
.. code-block::
$ cd tools/fetcher $ vim fetch.sh
edit FTP_USER
and FTP_PASS
$ ./build.sh $ ./fetch.sh 20191008
- The file is downloaded into
<repos root>/downloads
- You can also specify wiledcard to dowonload multiple files in batch (e.g.
./fetch.sh '201909??'
) - It fetches from under
/archives/
so most recent files are out of scope
Usage: convert from raw zip files to h5
.. code-block::
$ python cli.py convert --help
Usage: cli.py convert [OPTIONS] [FILES]...
convert raw zip files to h5
Options:
--help Show this message and exit.
Usage: resample h5 files into aggregated dataframe
.. code-block::
$ python cli.py resample --help
Usage: cli.py resample [OPTIONS] [FILES]...
resample the h5 file into aggregated dataframe
Options:
-f, --freq TEXT frequency of resampling (e.g. '1H' for hourly aggregation)
--help Show this message and exit.
Usage: launch the jupyter notebook (locally)
$ make notebook
Usage: launch the jupyter notebook (in docker)
$ make notebook_docker
Credits
This package was created with Cookiecutter_ and the audreyr/cookiecutter-pypackage
_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _audreyr/cookiecutter-pypackage
: https://github.com/audreyr/cookiecutter-pypackage
======= History
0.1.0 (2019-09-07)
- First release on PyPI.
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