Difference between revisions of "COVID-19"
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* [https://wolfr.am/COVID19Dashboard Wolfram] | * [https://wolfr.am/COVID19Dashboard Wolfram] | ||
* [https://www.worldometers.info/coronavirus/ Worldometers] | * [https://www.worldometers.info/coronavirus/ Worldometers] | ||
+ | |||
+ | <small>NOTABLE | ||
+ | #these libraries need to be loaded | ||
+ | library(utils) | ||
+ | |||
+ | #read the Dataset sheet into “R”. The dataset will be called "data". | ||
+ | data <- read.csv("https://opendata.ecdc.europa.eu/covid19/casedistribution/csv", na.strings = "", fileEncoding = "UTF-8-BOM") | ||
+ | </small> | ||
<hr class="stylish2"> | <hr class="stylish2"> |
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.
NOTABLE
library(utils)
data <- read.csv("https://opendata.ecdc.europa.eu/covid19/casedistribution/csv", na.strings = "", fileEncoding = "UTF-8-BOM")
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