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
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