COVID 19 Open Research Data Challenge Code

This repo contains code and notebooks for the COVID-19 Open Research Dataset Challenge (CORD-19) on kaggle

Using the library

On Kaggle

Clone and modify the Kaggle notebook

Off Kaggle

1. Download the data

Login to Kaggle and download the CORD Research Challenge data and extract to a folder called data.

You can also use the kaggle cli bash kaggle datasets download allen-institute-for-ai/CORD-19-research-challenge `` 2. Install

Install the library using pip

pip install git+https://github.com/dgunning/cord19.git

dir data\CORD-19-research-challenge

Usage

The library is meant for use in Jupyter or Kaggle notebooks

from cord import ResearchPapers

research_papers = ResearchPapers.load()

After loading the research papers you can display in a notebook

research_papers

Search

The search function returns the items that match the search query

research_papers.searchbar('vaccine transmission'

Search Bar

A more convenient way to search is through the search bar. This displays a search widgets in Jupyter notebook

research_papers.searchbar('vaccine transmission')

Selecting Subsets of Research Papers

There are many ways to select subsets of research papers including

• Papers since SARS research_papers.since_sars()
• Papers since SARS-COV-2 research_papers.since_sarscov2()
• Papers before SARS research_papers.before_sars()
• Papers before SARS-COV-2 research_papers.before_sarscov2()
• Papers before a date research_papers.before('1989-09-12')
• Papers after a date research_papers.after('1989-09-12')
• Papers that contains a string research_papers.contains("Fauci", column='authors')
• Papers that match a string (using regex) research_papers.match('H[0-9]N[0-9]')

Selecting individual Papers

You can select individual papers by using Python indexing []

research_papers[200]