/affiliation_parser

Simple python parser for MEDLINE, Pubmed OA affiliation string

Primary LanguagePython

Affiliation Parser

Fast and simple parser for MEDLINE and Pubmed Open-Access affiliation string. We can parse multiple fields from the affiliation string including department, affiliation, location, country, email and zip code from affiliation text.

We also provide function to match affiliation string to GRID dataset.

Example

Here is an example to parse affiliation

from affiliation_parser import parse_affil
parse_affil("Department of Health Science, Kochi Women's University, Kochi 780-8515, Japan. watanabe@cc.kochi-wu.ac.jp")

output is a dictionary

{'full_text': "Department of Health Science, Kochi Women's University, Kochi , Japan. ",
 'department': 'Department of Health Science',
 'institution': "Kochi Women's University",
 'location': 'Kochi , Japan',
 'country': 'japan',
 'zipcode': '780-8515',
 'email': 'watanabe@cc.kochi-wu.ac.jp'}

Here is an example to match affiliation to GRID dataset.

from affiliation_parser import match_affil
match_affil("Department of Physics, Chulalongkorn University, Thailand")  # string
match_affil([
    "Department of Physics, Chulalongkorn University, Thailand",
    "Department of Physics, Mahidol University, Thailand"
])  # or list of string

Output is list (or a list of list) of dictionary consist of GRID ID and matching score

[{
    'score': 0.783,
    'index': 515,
    'grid_id': 'grid.7922.e',
    'institution': 'Chulalongkorn University',
    'city': 'Bangkok',
    'state': nan,
    'country': 'Thailand'},
    ...
}]

Dependencies

use pip install -r requirements.txt in order to install required packages

Installation

Clone the repository and install using setup.py or simple copy affiliation_parser folder to your workspace.

git clone https://github.com/titipata/affiliation_parser
cd affiliation_parser
pip install .

Example results from MEDLINE database

I put some snippet on how to produce quick summarization from MEDLINE data here.

Total number of publications per country

Number of publications over time from selected countries