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The covid19italy R package provides a tidy format dataset of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) pandemic outbreak in Italy. The package includes the following three datasets:
italy_total - daily summary of the outbreak on the
national levelitaly_region - daily summary of the outbreak on the
region levelitaly_province - daily summary of the outbreak on the
province levelMore information about the package datasets available here, and supporting dashboard available here.
Data source: Italy Department of Civil Protection
You can install the released version of covid19italy from CRAN with:
install.packages("covid19italy")Or, install the most recent version from GitHub with:
# install.packages("devtools")
devtools::install_github("RamiKrispin/covid19Italy")While the covid19italy CRAN version
is updated every month or two, the Github (Dev)
version is updated on a daily bases. The update_data
function enables to overcome this gap and keep the installed version
with the most recent data available on the Github version:
library(covid19italy)
update_data()Note: must restart the R session to have the updates available
data(italy_total)
head(italy_total)
#> date hospitalized_with_symptoms intensive_care total_hospitalized home_confinement cumulative_positive_cases daily_positive_cases recovered death positive_clinical_activity
#> 1 2020-02-24 101 26 127 94 221 0 1 7 NA
#> 2 2020-02-25 114 35 150 162 311 90 1 10 NA
#> 3 2020-02-26 128 36 164 221 385 74 3 12 NA
#> 4 2020-02-27 248 56 304 284 588 203 45 17 NA
#> 5 2020-02-28 345 64 409 412 821 233 46 21 NA
#> 6 2020-02-29 401 105 506 543 1049 228 50 29 NA
#> positive_surveys_tests cumulative_cases total_tests total_people_tested new_intensive_care total_positive_molecular_test total_positive_rapid_antigen_test molecular_test rapid_antigen_test
#> 1 NA 229 4324 NA NA NA NA NA NA
#> 2 NA 322 8623 NA NA NA NA NA NA
#> 3 NA 400 9587 NA NA NA NA NA NA
#> 4 NA 650 12014 NA NA NA NA NA NA
#> 5 NA 888 15695 NA NA NA NA NA NA
#> 6 NA 1128 18661 NA NA NA NA NA NAlibrary(plotly)
plot_ly(data = italy_total,
x = ~ date,
y = ~home_confinement,
name = 'Home Confinement',
fillcolor = '#FDBBBC',
type = 'scatter',
mode = 'none',
stackgroup = 'one') %>%
add_trace( y = ~ hospitalized_with_symptoms,
name = "Hospitalized with Symptoms",
fillcolor = '#E41317') %>%
add_trace(y = ~intensive_care,
name = 'Intensive Care',
fillcolor = '#9E0003') %>%
layout(title = "Italy - Distribution of Active Covid19 Cases",
legend = list(x = 0.8, y = 0.9),
yaxis = list(title = "Number of Cases"),
xaxis = list(title = "Source: Italy Department of Civil Protection"))
plot_ly(data = italy_total,
x = ~ date,
y = ~ cumulative_positive_cases,
name = 'Active',
fillcolor = '#1f77b4',
type = 'scatter',
mode = 'none',
stackgroup = 'one') %>%
add_trace( y = ~ death,
name = "Death",
fillcolor = '#E41317') %>%
add_trace(y = ~recovered,
name = 'Recovered',
fillcolor = 'forestgreen') %>%
layout(title = "Italy - Distribution of Covid19 Cases",
legend = list(x = 0.1, y = 0.9),
yaxis = list(title = "Number of Cases"),
xaxis = list(title = "Source: Italy Department of Civil Protection"))
italy_region %>%
filter(date == max(date)) %>%
select(region_name, cumulative_positive_cases, recovered, death, cumulative_cases) %>%
arrange(-cumulative_cases) %>%
mutate(region = factor(region_name, levels = region_name)) %>%
plot_ly(y = ~ region,
x = ~ cumulative_positive_cases,
orientation = 'h',
text = ~ cumulative_positive_cases,
textposition = 'auto',
type = "bar",
name = "Active",
marker = list(color = "#1f77b4")) %>%
add_trace(x = ~ recovered,
text = ~ recovered,
textposition = 'auto',
name = "Recovered",
marker = list(color = "forestgreen")) %>%
add_trace(x = ~ death,
text = ~ death,
textposition = 'auto',
name = "Death",
marker = list(color = "red")) %>%
layout(title = "Cases Distribution by Region",
barmode = 'stack',
yaxis = list(title = "Region"),
xaxis = list(title = "Number of Cases"),
hovermode = "compare",
legend = list(x = 0.65, y = 0.9),
margin = list(
l = 20,
r = 10,
b = 10,
t = 30,
pad = 2
)) 
italy_province %>%
filter(date == max(date), region_name == "Lombardia") %>%
plot_ly(labels = ~province_name, values = ~total_cases,
textinfo="label+percent",
type = 'pie') %>%
layout(title = "Lombardia - Cases Distribution by Province") %>%
hide_legend()
A supporting dashboard for the covid19italy datasets available here.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.