The covid19nytimes package harvests the data made freely available by the New York Times. See https://www.nytimes.com/article/coronavirus-county-data-us.html for more.
You can install the released version of covid19nytimes from CRAN with:
install.packages("covid19nytimes")
Or the latest development version from github
devtools::install_github("covid19R/covid19nytimes")
The package has the data from states and counties. The package comes with static data that was downloaded at the time of the last package update.
library(covid19nytimes)
head(covid19nytimes_states_demo) %>% knitr::kable()
| date | location | location_type | location_code | location_code_type | data_type | value | | :--------- | :------------- | :------------- | :------------- | :------------------- | :------------ | ----: | | 2020-04-12 | Alabama | state | 01 | fips_code | cases_total | 3583 | | 2020-04-12 | Alabama | state | 01 | fips_code | deaths_total | 93 | | 2020-04-12 | Alaska | state | 02 | fips_code | cases_total | 270 | | 2020-04-12 | Alaska | state | 02 | fips_code | deaths_total | 6 | | 2020-04-12 | American Samoa | state | 60 | fips_code | cases_total | 0 | | 2020-04-12 | American Samoa | state | 60 | fips_code | deaths_total | 0 |
head(covid19nytimes_counties_demo) %>% knitr::kable()
| date | location | location_type | location_code | location_code_type | data_type | value | | :--------- | :----------------------- | :------------- | :------------- | :------------------- | :------------ | ----: | | 2020-04-12 | Abbeville,South Carolina | county_state | 45001 | fips_code | cases_total | 9 | | 2020-04-12 | Abbeville,South Carolina | county_state | 45001 | fips_code | deaths_total | 0 | | 2020-04-12 | Acadia,Louisiana | county_state | 22001 | fips_code | cases_total | 99 | | 2020-04-12 | Acadia,Louisiana | county_state | 22001 | fips_code | deaths_total | 5 | | 2020-04-12 | Accomack,Virginia | county_state | 51001 | fips_code | cases_total | 15 | | 2020-04-12 | Accomack,Virginia | county_state | 51001 | fips_code | deaths_total | 0 |
To get the most updated data, run the following functions
covid19nytimes_states <- refresh_covid19nytimes_states()
covid19nytimes_counties <- refresh_covid19nytimes_counties()
The data follows the covid19R standard for tidy Covid-19 data. The data columns are as follows:
,
, and can be split by tidyr::separate()
, if
you wish.fips_code
total_cases
and total_deaths
, cumulative measures of both.library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(ggplot2)
covid19nytimes_states %>%
filter(location %in% c("Washington", "New York", "Massachusetts", "Michigan", "Illinois")) %>%
filter(data_type == "deaths_total") %>%
ggplot(aes(x = date, y = value, color = location)) +
geom_line() +
theme_minimal(base_size=14) +
scale_y_continuous()
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