This repository is intended to provide a tidy time-series data set of Covid-19 case data collected by Johns Hopkins University (JHU) at https://github.com/CSSEGISandData/COVID-19.
I have also created a Shiny app to view the data and forecasts for state growth rates over the next 10 days: https://slushmier.shinyapps.io/covid_analysis/
app.R - code for the Shiny app I have running at https://slushmier.shinyapps.io/covid_analysis/
covid_pull.R - formats the daily reports from the JHU datasets to create a clean tidy dataset by US districts, states,
and territories
covid_us_time_series.csv - The most recently updated tidy, time-series dataset of the JHU data. I upload this either every
day after the District of Columbia announces new cases or early the following morning. Contains colums for state, date, Confirmed,
Deaths, Recovered, and New Cases
covid_us_time_series_aggregate.csv - Same as above; has aggregate counts for whole country
covid_us_time_series_counties.csv - Same as two above with county counts starting from 23 March 2020.
simplify_spatial.R - simplifies a TIGR counties shapefile and merges it with population counts; probably only works on my computer
testing_data.R - Pulls and writes a CSV of the dataset compiled at https://covidtracking.com/api/states/daily to data/testing_atlantic.csv
counties_simple shapefile - Provides a US counties shapefile with simplified boundaries
county_pop.csv - 2018 Census data of population count by county
state_all.geojson - Couples testing data and state boundaries, used for map in app.R
state_pop.csv - 2018 Census data of population count by state
states_simple shapefile - Provides a US states shapefile with simplified boundaries
testing_atlantic.csv - CSV of data on Covid-19 tests provided by state, compiled from covidtracking.com