Coronavirus-Worldwide-Dataset
OpenML dataset with id 43844
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22102669/Coronavirus-Worldwide-Dataset.arff
Upload date: 24 March 2022
Dataset Characteristics
Number of features: 36 (numeric: 31, symbolic: 0 and in total binary: 0 )
Number of instances: 36,137
Number of instances with missing values: 33,643
Number of missing values: 314,500
Context
From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. This raised concern because when a virus is new, we do not know how it affects people.
So daily level information on the affected people can give some interesting insights when it is made available to the broader data science community.
The European CDC publishes daily statistics on the COVID-19 pandemic. Not just for Europe, but for the entire world. We rely on the ECDC as they collect and harmonize data from around the world which allows us to compare what is happening in different countries.
Content
This dataset has daily level information on the number of affected cases, deaths and recovery etc. from coronavirus. It also contains various other parameters like average life expectancy, population density, smocking population etc. which users can find useful in further prediction that they need to make.
The data is available from 31 Dec,2019.
Inspiration
Give people weekly data so that they can use it to make accurate predictions.
This page was built for dataset: Coronavirus-Worldwide-Dataset
