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The data analysis sandbox for JPX

Project description

====== jpxlab

.. image:: https://img.shields.io/pypi/v/jpxlab.svg :target: https://pypi.python.org/pypi/jpxlab

.. image:: https://img.shields.io/travis/AlpacaDB/jpxlab.svg :target: https://travis-ci.org/AlpacaDB/jpxlab

.. image:: https://readthedocs.org/projects/jpxlab/badge/?version=latest :target: https://jpxlab.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status

.. image:: https://pyup.io/repos/github/AlpacaDB/jpxlab/shield.svg :target: https://pyup.io/repos/github/AlpacaDB/jpxlab/ :alt: Updates

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.

Project details


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