Metadata-Version: 2.1
Name: numerai-reports
Version: 0.2.2
Summary: Reports for the Numerai machine learning competition
Home-page: https://github.com/uuazed/numerai_reports
Maintainer: uuazed
Maintainer-email: uuazed@gmail.com
License: MIT License
Platform: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numerapi
Requires-Dist: tqdm
Requires-Dist: joblib

[![Build Status](https://travis-ci.org/uuazed/numerai_reports.png)](https://travis-ci.org/uuazed/numerai_reports)
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# Numerai Reports
Collection of reports about the numer.ai machine learning competition.

This library was created to provide some reports and statistics about the
competition, like round summaries and payout summaries, but also tools to
analyze one's model performance. For now, all reports are pure numeric reports.

All information is retrieved via numerai's API and converted to pandas
DataFrames, to make it easy to work with. This allows to create your own
reports on top. `numerai_reports` also caches API results to disk to limit the
amount of request and to speed-up report generation.

If you encounter a problem or have suggestions, feel free to open an issue.

# Installation
`pip install --upgrade numerai_reports`

# Usage

Numerai_reports can be used as a regular, importable Python module or from the command
line (TODO).


## Python module

Usage example:

    from numerai_reports import data, reports
    lb = data.fetch_leaderboard(150, 159)
    print(reports.payments(lb, "slyfox"))
    print(reports.reputation(lb, "slyfox"))
    print(reports.pass_rate(lb))
    print(reports.out_of_n(lb))
    print(reports.dominance("uuazed"))


