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April/November 2020
- Tristan Beau - UFR de Physique - Université de Paris - LPNHE laboratory
- Julien Browaeys - UFR de Physique - Université de Paris - MSC laboratory
- Olivier Dadoun - CNRS/IN2P3 - LPNHE laboratory
The CoCoA project (Covid Collaborative Analysis) is a Python™ framework which provides a simplified and unified access to various Covid related databases. It's designed to offer to many people (non-specialist general public, school pupils, students, science journalists, but also scientists who are not specialists in computing and data access methods) a simple and practical tool for studying data : raw data access, time series plots, maps. Then, it's easy to make simple or more complex analysis. Database access difficulties, method unification, geo-localisation of data, are processed transparently.
Thus, in only few lines of code, with almost no Python™ knowledge, one can produce a plot or a map. For example, after a CoCoA install, the next few lines of code:
import cocoa.cocoa as cc
cc.plot(where=['France','Italy','United kingdom'],which='deaths',what='cumul')
cc.map(where=['world'])
cc.hist(where='middle africa',which='confirmed')
cc.get(where=['usa'],what='daily',which='recovered')produce a temporal serie plot of Covid deaths for three countries (France, Italy, and United Kingdom as an example), or the deaths map over the world, or the histogram of confirmed cases in all countries from Middle Africa, or the pandas output of recovered people in the United States.
CoCoA is made to work :
- locally (local install of Python™, for example with
Spyder) - on
Jupyterplatform, either closed or opened such asGoogle Colab - through a
docker, using for examplemybinder.
Various applications code are available :
The full documentation is available on the Wiki.
The reference library is available using the help of function (see help_* notebook files) or on related pages :