A toolkit for examining laws of bibliometrics
Project description
Bibliometric Laws Toolkit
A toolkit to examine Laws of Bibliometrics based on bibliometric data
Installation
pip install biblio-laws
Functions
- Examine the laws of bibliometrics, namely, Bradford's Law, Lotka's Law, and Zipf's Law.
- Provide an easy tool to estimate parameters from the proposed formula of the laws.
Examples
Examine sample data distributions
from bibliolaws.datasets import *
from bibliolaws.zipf_law import ZipfLaw
from bibliolaws.bradford_law import BradfordLaw
from bibliolaws.lotka_law import LotkaLaw
# (1) Bradford's Law for relationship between journal and publication numbers
bf=BradfordLaw(load_bradford_sample_data())
bf.zone_analysis()
x,y=bf.figure_analysis()
# (2) Lotka's Law for relationship between author and publications numbers
lotka=LotkaLaw(load_lotka_sample_data())
lotka.print_table()
lotka.plot()
# (3) Zipf's Law for relationship between term rank and term freq.
zipf=ZipfLaw(load_zipf_sample_data())
zipf.print_table()
zipf.plot()
Screenshot of results
- Bradford's Law
- Lotka's Law
- Zipf's Law
License
The biblio-laws
project is provided by Donghua Chen.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
biblio-laws-0.0.1a1.tar.gz
(14.4 kB
view details)
File details
Details for the file biblio-laws-0.0.1a1.tar.gz
.
File metadata
- Download URL: biblio-laws-0.0.1a1.tar.gz
- Upload date:
- Size: 14.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.21.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c6d2da80d7e662c5a57839cc943ca340ae57282d34c0ce8b05286dce2e6fe739 |
|
MD5 | c75f08dbee677d8befe4188f7f7cf506 |
|
BLAKE2b-256 | 3bd27b74977414dd3d41784bb4f1469aac646da28c82535e1e794ecae9df4f33 |