Title: Coronavirus COVID-19 (2019-nCoV) Data Acquisition and
Authors@R: person(given = "Emanuele", family = "Guidotti", email = "emanuele.guidotti@unine.ch", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8961-6623"))
Description: Pre-processed, ready-to-use, tidy format datasets of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic. The latest data are downloaded in real-time, processed and merged with demographic indicators from several trusted sources. The package implements advanced data visualization across the space and time dimensions by means of animated mapping. Besides worldwide data, the package includes granular data for Italy, Switzerland and the Diamond Princess.
Imports: devtools, utils, reshape2, dplyr, tidyr, sp, rgdal, ggplot2,
Author: Emanuele Guidotti [aut, cre] (<https://orcid.org/0000-0002-8961-6623>)

Title: Coronavirus COVID-19 (2019-nCoV) Epidemic Datasets
Description: Unified tidy format datasets of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic across several sources. The data are downloaded in real-time, cleaned and matched with exogenous variables.
Imports: devtools, utils, reshape2, dplyr, tidyr

person(given = "Emanuele", family = "Guidotti", email = "emanuele.guidotti@unine.ch", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8961-6623")),
person(given = "David", family = "Ardia", role = c("ctb"), comment = c(ORCID = "0000-0003-2823-782X"))
Description: Unified tidy format datasets of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) epidemic across several sources. The data are downloaded in real-time, cleaned and matched with exogenous variables. Vintage databases are also supported.
Author: Emanuele Guidotti [aut, cre] (<https://orcid.org/0000-0002-8961-6623>),

Description: Unified datasets for a better understanding of COVID-19.
The package collects COVID-19 data across governmental sources,
includes policy measures from 'Oxford COVID-19 Government Response Tracker' <https://www.bsg.ox.ac.uk/covidtracker>,
and extends the dataset via an interface to 'World Bank Open Data' <https://data.worldbank.org/>, 'Google Mobility Reports' <https://www.google.com/covid19/mobility/>, 'Apple Mobility Reports' <https://www.apple.com/covid19/mobility>.
Imports: utils, dplyr, tidyr (>= 1.0.0), wbstats