Compute scholarly metrics in Python with Pandas and NumPy
Project description
scholarmetrics
Compute scholarly metrics in Python with Pandas and NumPy.
Documentation: https://scholarmetrics.readthedocs.io.
Example
J.E. Hirsch’s h-index or Hirsch-index.
>>> from scholarmetrics import hindex >>> citations = [6, 10, 5, 46, 0, 2] >>> hindex(citations) 4
Contributing
Please see CONTRIBUTING.rst.
For a list of contributors see AUTHORS.rst.
License
MIT License, see LICENSE.
History
0.1.0 (2017-03-13)
First release on PyPI.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
No source distribution files available for this release.See tutorial on generating distribution archives.
Built Distributions
Close
Hashes for scholarmetrics-0.1.0-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 43c449a627ad206ccc877aef342adcdb7b53dbd41161f4b20768220af39d1f3c |
|
MD5 | 369f5b72e0d41068ed090cbb7a1a60da |
|
BLAKE2b-256 | 14fe55e90eedafa9652cf6c32c1d204ac05f3dc3f85375b6a341283569f90f10 |