covid19R

The goal of covid19R is to provide a single package that allows users to access all of the tidy covid-19 datasets collected by data packages that implement the covid19R tidy data standard. It provides access

Installation

You can install the development version from github with:

remotes::install_github("covid19r/covid19r")

Getting the Data Information

To see what datasets are available, use get_covid19_data_info()

library(covid19R)

data_info <- get_covid19_data_info()

head(data_info) %>% knitr::kable()

data_set_name	package_name	function_to_get_data	data_details	data_url	license_url	data_types	location_types	spatial_extent	has_geospatial_info	refresh_status	last_update
covid19nytimes_states	covid19nytimes	refresh_covid19nytimes_states	Open Source data from the New York Times on distribution of confirmed Covid-19 cases and deaths in the US States. For more, see https://www.nytimes.com/article/coronavirus-county-data-us.html or the readme at https://github.com/nytimes/covid-19-data.	https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv	https://github.com/nytimes/covid-19-data/blob/master/LICENSE	cases_total, deaths_total	state	country	FALSE	Passed	2020-04-03
covid19nytimes_counties	covid19nytimes	refresh_covid19nytimes_counties	Open Source data from the New York Times on distribution of confirmed Covid-19 cases and deaths in the US by County. For more, see https://www.nytimes.com/article/coronavirus-county-data-us.html or the readme at https://github.com/nytimes/covid-19-data.	https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-counties.csv	https://github.com/nytimes/covid-19-data/blob/master/LICENSE	cases_total, deaths_total	county, state	country	FALSE	Passed	2020-04-03
covid19france	covid19france	refresh_covid19france	Open Source data from opencovid19-fr on distribution of confirmed Covid-19 cases and deaths in the US States. For more, see https://github.com/opencovid19-fr/data.	https://raw.githubusercontent.com/opencovid19-fr/data/master/dist/chiffres-cles.csv	https://github.com/opencovid19-fr/data/blob/master/LICENSE	confirmed, dead, icu, hospitalized, recovered, discovered	NA	NA	FALSE	Passed	2020-04-04

Accessing data

Once you have figured out what dataset you want, you can access it with get_covid19_dataset()

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

nytimes_states <- get_covid19_dataset("covid19nytimes_states")
#> Parsed with column specification:
#> cols(
#>   date = col_date(format = ""),
#>   location = col_character(),
#>   location_type = col_character(),
#>   location_standardized = col_character(),
#>   location_standardized_type = col_character(),
#>   data_type = col_character(),
#>   value = col_double()
#> )

nytimes_states %>%
  filter(date == max(date)) %>%
  filter(data_type == "cases_total") %>%
  arrange(desc(value)) %>%
  head()
#> # A tibble: 6 x 7
#>   date       location location_type location_standa… location_standa… data_type
#>   <date>     <chr>    <chr>         <chr>            <chr>            <chr>    
#> 1 2020-04-03 New York state         36               fips_code        cases_to…
#> 2 2020-04-03 New Jer… state         34               fips_code        cases_to…
#> 3 2020-04-03 Michigan state         26               fips_code        cases_to…
#> 4 2020-04-03 Califor… state         06               fips_code        cases_to…
#> 5 2020-04-03 Massach… state         25               fips_code        cases_to…
#> 6 2020-04-03 Louisia… state         22               fips_code        cases_to…
#> # … with 1 more variable: value <dbl>

The covid19R Data Standard

While many data sets have their own unique additional columns (e.g., Latitude, Longitude, population, etc.), all datasets have the following columns and are arranged in a long format:

date - The date in YYYY-MM-DD form
location - The name of the location as provided by the data source. The counties dataset provides county and state. They are combined and separated by a ,, and can be split by tidyr::separate(), if you wish.
location_type - The type of location using the covid19R controlled vocabulary. Nested locations are indicated by multiple location types being combined with a `_
location_standardized - A standardized location code using a national or international standard. In this case, FIPS state or county codes. See https://en.wikipedia.org/wiki/Federal_Information_Processing_Standard_state_code and https://en.wikipedia.org/wiki/FIPS_county_code for more
location_standardized_type The type of standardized location code being used according to the covid19R controlled vocabulary. Here we use fips_code
data_type - the type of data in that given row. Includes total_cases and total_deaths, cumulative measures of both.
value - number of cases of each data type

Vocabularies

The location_type, location_standardized_type, and data_type from datasets and spatial_extent from the data info table all have their own controlled vocabularies. Others might be introduced as the collection of packages matures. To see the possible values of a standardized vocabulary, use get_covid19_controlled_vocab()

get_covid19_controlled_vocab("location_type") %>%
  knitr::kable()

location_type	description
continent	continental scale
country	a country with soverign borders
state	a spatial area inside that country such as a state, province, canton, etc.
county	a spatial area demarcated within a state
city	a single municipality - the smallest spatial grain of government in a country

nuelma991/covid19R