Package 'coronavirus'

Title: The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset
Description: Provides a daily summary of the Coronavirus (COVID-19) cases by state/province. Data source: Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus <https://systems.jhu.edu/research/public-health/ncov/>.
Authors: Rami Krispin [aut, cre], Jarrett Byrnes [aut]
Maintainer: Rami Krispin <[email protected]>
License: MIT + file LICENSE
Version: 0.4.1
Built: 2024-10-10 04:48:04 UTC
Source: https://github.com/RamiKrispin/coronavirus

Help Index

The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset

Description

Daily summary of the Coronavirus (COVID-19) cases by state/province.

Usage

coronavirus

Format

A data frame with 7 variables.

date

Date in YYYY-MM-DD format.

province

Name of province/state, for countries where data is provided split across multiple provinces/states.

country

Name of country/region.

lat

Latitude of center of geographic region, defined as either country or, if available, province.

long

Longitude of center of geographic region, defined as either country or, if available, province.

type

An indicator for the type of cases (confirmed, death, recovered).

cases

Number of cases on given date.

uid

Country code

iso2

Officially assigned country code identifiers with two-letter

iso3

Officially assigned country code identifiers with three-letter

code3

UN country code

combined_key

Country and province (if applicable)

population

Country or province population

continent_name

Continent name

continent_code

Continent code

Details

The dataset contains the daily summary of Coronavirus cases (confirmed, death, and recovered), by state/province.

Source

Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus website.

Examples

data(coronavirus)

require(dplyr)

# Get top confirmed cases by state
coronavirus %>%
  filter(type == "confirmed") %>%
  group_by(country) %>%
  summarise(total = sum(cases)) %>%
  arrange(-total) %>%
  head(20)

# Get the number of recovered cases in China by province
coronavirus %>%
  filter(type == "recovered", country == "China") %>%
  group_by(province) %>%
  summarise(total = sum(cases)) %>%
  arrange(-total)

The COVID-19 Worldwide Vaccine Dataset

Description

Daily summary of the COVID-19 vaccination by country/province.

Usage

covid19_vaccine

Format

A data frame with 8 variables.

date

Data collection date in YYYY-MM-DD format

country_region

Country or region name

continent_name

Continent name

continent_code

Continent code

combined_key

Country and province (if applicable)

doses_admin

Cumulative number of doses administered. When a vaccine requires multiple doses, each one is counted independently

people_at_least_one_dose

Cumulative number of people who received at least one vaccine dose. When the person receives a prescribed second dose, it is not counted twice

population

Country or province population

uid

Country code

iso2

Officially assigned country code identifiers with two-letter

iso3

Officially assigned country code identifiers with three-letter

code3

UN country code

fips

Federal Information Processing Standards code that uniquely identifies counties within the USA

lat

Latitude

long

Longitude

Details

The dataset provides the daily cumulative number of people who received vaccine (or at least one vaccine dose) by country and province (when applicable)

Source

- Vaccine data - Johns Hopkins University Centers for Civic Impact (JHU CCSE) COVID-19 repository.

- Country code (uid, iso2, iso3, etc.) are sourced from this repository, see section 4 for full data resources.

- Continent code mapping is sourced from DATA HUB

Examples

data(covid19_vaccine)

head(covid19_vaccine)

Get information about the datasets provided by the coronavirus package

Description

Returns information about the datasets in this package for covid19R harvesting

Usage

get_info_coronavirus()

Value

a tibble of information about the datasets in this package

Examples

## Not run: 

# get the dataset info from this package
get_info_coronavirus()

## End(Not run)

Refresh the 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset in the Covid19R Project Format

Description

Daily summary of the Coronavirus (COVID-19) cases by state/province.

Usage

refresh_coronavirus_jhu()

Value

A tibble object * date - The date in YYYY-MM-DD form * location - The name of the location as provided by the data source. * location_type - The type of location using the covid19R controlled vocabulary. * location_code - A standardized location code using a national or international standard. Drawn from iso-3166-2.js's version * location_code_type The type of standardized location code being used according to the covid19R controlled vocabulary. Here we use 'iso_3166_2' * data_type - the type of data in that given row using the covid19R controlled vocabulary. Includes cases_new, deaths_new, recovered_new. * value - number of cases of each data type

A data.frame object

Source

coronavirus - Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus website

Examples

## Not run: 
# update the data
jhu_covid19_dat <- refresh_coronavirus_jhu()

## End(Not run)

Update the coronavirus Dataset

Description

Update the package datasets on the global environment with the most recent data on the Dev version

Usage

update_dataset(silence = FALSE)

Arguments

silence

A boolean, if set to TRUE, will automatically install updates without prompt question, by default set to FALSE

Details

As the CRAN version is being updated every one-two months, the dev version of the package is being updated on a daily bases. This function enables to refresh the package dataset to the most up-to-date data. Changes will be available on the global environment

Value

A data.frame object

Source

coronavirus - Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus website