Difference between revisions of "COVID-19"
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− | Script for downloading the CSV file into '''R''' ([https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide | + | '''NOTE:''' Script for downloading the CSV file into '''R''' ([https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide More info]) |
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#these libraries need to be loaded | #these libraries need to be loaded |
Inside the Coronavirus Genome by J. Corum and C. Zimmer, April 3, 2020 — NY Times
— The genome of the new coronavirus is less than 30,000 letters long, while the human genome is over 3 billion. Scientists have identified genes for as many as 29 proteins, which carry out a range of jobs from making copies of the coronavirus to suppressing the body’s immune responses.
Genetic Data for SARS-CoV-2, April 12, 2020 — Wolfram
— This interactive dashboard displays recent information on the COVID-19 (coronavirus) pandemic, patient symptoms and outcomes, and the genetic makeup of the novel coronavirus (SARS-CoV-2).
How do sources compare? by H. Ritchie et al., March 19, 2020 — Our World in Data
— There are three key sources providing regular updates of COVID-19 cases and deaths globally and by country.
NOTE: Script for downloading the CSV file into R (More info)
1 #these libraries need to be loaded
2 library(utils)
3
4 #read the Dataset sheet into “R”. The dataset will be called "data".
5 data <- read.csv("https://opendata.ecdc.europa.eu/covid19/casedistribution/csv", na.strings = "", fileEncoding = "UTF-8-BOM")
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