Skip to main content

A package for bibliometric analysis of journals

Project description

Bibliometria

A package for bibliometric analysis of journals.

This package provides tools for retrieving journal information and comparing metrics,
combining the data from SCImago Journal Rank and Web of Science.

Installation

pip install bibliometria
import bibliometria as bm
# or import the functions directly
from bibliometria import get_sjr, get_wos, title_matches, title_best_match, journal_metrics, journal_info

Usage

Data

The package contains two built-in datasets with SJR and WoS data that can be downloaded from this repository or via internal loading functions:

import bibliometria as bm

sjr = bm.get_sjr()
>>> pd.DataFrame

wos = bm.get_wos()
>>> pd.DataFrame

Main functions

The package exposes four main functions for working with journal data.


title_matches
title_matches(title_query, limit=10, score_cutoff=60)
>>> pd.DataFrame

Fuzzy-searches a journal by title across SJR and WoS and returns a DataFrame of the top candidate matches with similarity scores and basic metadata (title, ISSN/eISSN, SJR, quartiles, etc.).


title_best_match

title_best_match(title_query) 
>>> pd.Series

Returns the single best fuzzy match for a journal title as a pandas Series with similarity score and metadata, or None if no suitable match is found.


journal_metrics

journal_metrics(query, query_type="title") 
>>> pd.Series

Retrieve core bibliometric indicators for a journal, using either:

  • query_type="title" – fuzzy match by journal title, or
  • query_type="issn" – exact match by ISSN / eISSN

The returned Series contains a small set of metrics such as:

  • sjr, sjr_best_quartile, h_index (from SJR)
  • wos_quartile, wos_jif, wos_jif_5_year (from WoS)

If the journal is not found, an “empty” Series with all fields set to None is returned, and a warning is emitted.


journal_info

journal_info(query, query_type="title") 
>>> pd.DataFrame

Return a single-row DataFrame with all available fields for a journal from both SJR and WoS,
merged into one record. Supports the same lookup modes as journal_metrics:

  • query_type="title" – fuzzy title match
  • query_type="issn" – exact ISSN / eISSN match

The result also includes a few metadata columns describing the lookup:

  • query, query_type, source_primary, matched_title, match_score

Interactive examples

You can explore example outputs in the notebook:

Open In Colab

Contribution

This package is in the testing status. To report a bug or suggest an improvement, you can open an issue or contact us directly.

Authors: Vladislava Termus, Alexandra Pogozheva

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bibliometria-0.1.0.tar.gz (3.9 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bibliometria-0.1.0-py3-none-any.whl (3.9 MB view details)

Uploaded Python 3

File details

Details for the file bibliometria-0.1.0.tar.gz.

File metadata

  • Download URL: bibliometria-0.1.0.tar.gz
  • Upload date:
  • Size: 3.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.0

File hashes

Hashes for bibliometria-0.1.0.tar.gz
Algorithm Hash digest
SHA256 e2ceb2fb62b0f52497439350405aeed3f3fa5cf1dc4847885342cc7da8339ea6
MD5 052344d691286f5b3bb82747ca73481b
BLAKE2b-256 5957516c99471946bc1cf5825cd4f50207ff5fde2a165bea974b84a0b77ec07f

See more details on using hashes here.

File details

Details for the file bibliometria-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: bibliometria-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 3.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.0

File hashes

Hashes for bibliometria-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 5469e2c904eb243678e3960a0517b40aa38c2891a25e838b37010e118b055dd6
MD5 f8b08c0e66001cd0407c3ce5b28ec7e2
BLAKE2b-256 75a1238806da86abbd271a6419a1afac5b4c2554ee96d12e6fd08d1bc910c561

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page