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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 levelThe data was pull from 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")The covid19italy package dev version is been updated on a daily bases. The update_data function enables a simple refresh of the installed package datasets with the most updated version on Github:
library(covid19italy)
update_data()Note: must restart the R session to have the updates available
The italy_total dataset provides an overall summary of the cases in Italy since the beginning of the covid19 outbreak since February 24, 2020. The dataset contains the following fields:
date - timestamp, a Date objecthospitalized_with_symptoms - daily number of patients hospitalized with symptomsintensive_care - daily number of patients on intensive caretotal_hospitalized - daily total number of patients hospitalized (hospitalized_with_symptoms + intensive_care)home_confinement - daily number of people under home confinementcumulative_positive_cases - a daily snapshot of the number of positive casesdaily_positive_cases - daily new positive casesdaily_cases - daily new positive, recovered, and death casesrecovered - total number of recovered cases (cumulative)death - total number of death cases (cumulative)positive_clinical_activity - positive cases emerged from clinical activitypositive_surveys_tests - positive cases emerging from surveys and tests, planned at national or regional levelcumulative_cases - total number of positive cases (cumulative)total_tests - total number of tests performed (cumulative)library(covid19italy)
data(italy_total)
str(italy_total)
#> Classes 'tbl_df', 'tbl' and 'data.frame': 520 obs. of 19 variables:
#> $ date : Date, format: "2020-02-24" "2020-02-25" ...
#> $ hospitalized_with_symptoms : num 101 114 128 248 345 ...
#> $ intensive_care : num 26 35 36 56 64 105 140 166 229 295 ...
#> $ total_hospitalized : num 127 150 164 304 409 ...
#> $ home_confinement : num 94 162 221 284 412 ...
#> $ cumulative_positive_cases : num 221 311 385 588 821 ...
#> $ daily_positive_cases : num 0 90 74 203 233 228 528 258 428 443 ...
#> $ recovered : num 1 1 3 45 46 50 83 149 160 276 ...
#> $ death : num 7 10 12 17 21 29 34 52 79 107 ...
#> $ positive_clinical_activity : num NA NA NA NA NA NA NA NA NA NA ...
#> $ positive_surveys_tests : num NA NA NA NA NA NA NA NA NA NA ...
#> $ cumulative_cases : num 229 322 400 650 888 ...
#> $ total_tests : num 4324 8623 9587 12014 15695 ...
#> $ total_people_tested : num NA NA NA NA NA NA NA NA NA NA ...
#> $ new_intensive_care : num NA NA NA NA NA NA NA NA NA NA ...
#> $ total_positive_molecular_test : num NA NA NA NA NA NA NA NA NA NA ...
#> $ total_positive_rapid_antigen_test: num NA NA NA NA NA NA NA NA NA NA ...
#> $ molecular_test : num NA NA NA NA NA NA NA NA NA NA ...
#> $ rapid_antigen_test : num NA NA NA NA NA NA NA NA NA NA ...
head(italy_total)
#> date hospitalized_with_symptoms intensive_care total_hospitalized
#> 1 2020-02-24 101 26 127
#> 2 2020-02-25 114 35 150
#> 3 2020-02-26 128 36 164
#> 4 2020-02-27 248 56 304
#> 5 2020-02-28 345 64 409
#> 6 2020-02-29 401 105 506
#> home_confinement cumulative_positive_cases daily_positive_cases recovered
#> 1 94 221 0 1
#> 2 162 311 90 1
#> 3 221 385 74 3
#> 4 284 588 203 45
#> 5 412 821 233 46
#> 6 543 1049 228 50
#> death positive_clinical_activity positive_surveys_tests cumulative_cases
#> 1 7 NA NA 229
#> 2 10 NA NA 322
#> 3 12 NA NA 400
#> 4 17 NA NA 650
#> 5 21 NA NA 888
#> 6 29 NA NA 1128
#> total_tests total_people_tested new_intensive_care
#> 1 4324 NA NA
#> 2 8623 NA NA
#> 3 9587 NA NA
#> 4 12014 NA NA
#> 5 15695 NA NA
#> 6 18661 NA NA
#> total_positive_molecular_test total_positive_rapid_antigen_test
#> 1 NA NA
#> 2 NA NA
#> 3 NA NA
#> 4 NA NA
#> 5 NA NA
#> 6 NA NA
#> molecular_test rapid_antigen_test
#> 1 NA NA
#> 2 NA NA
#> 3 NA NA
#> 4 NA NA
#> 5 NA NA
#> 6 NA NAThe italy_region dataset provides an overall summary of the cases in Italy’s regions. The dataset contains the following fields:
date - timestamp, a Date objectregion_code - the region coderegion_name - the region namelat - region latitude coordinatelong - region longitude coordinatehospitalized_with_symptoms - daily number of patients hospitalized with symptomsintensive_care - daily number of patients on intensive caretotal_hospitalized - daily total number of patients hospitalized (hospitalized_with_symptoms + intensive_care)home_confinement - daily number of people under home confinementcumulative_positive_cases - a daily snapshot of the number of positive casesdaily_positive_cases - daily new positive casesdaily_cases - daily new positive, recovered, and death casesrecovered - total number of recovered cases (cumulative)death - total number of death cases (cumulative)positive_clinical_activity - positive cases emerged from clinical activitypositive_surveys_tests - positive cases emerging from surveys and tests, planned at national or regional levelcumulative_cases - total number of positive cases, recovered, and death (cumulative)total_tests - total number of tests performed (cumulative)region_spatial - the spatial region names as in the output of the ne_states function from the rnaturalearth packagedata(italy_region)
str(italy_region)
#> 'data.frame': 10920 obs. of 26 variables:
#> $ date : Date, format: "2020-02-24" "2020-02-24" ...
#> $ region_code : chr "13" "17" "18" "15" ...
#> $ region_name : chr "Abruzzo" "Basilicata" "Calabria" "Campania" ...
#> $ lat : num 42.4 40.6 38.9 40.8 44.5 ...
#> $ long : num 13.4 15.8 16.6 14.3 11.3 ...
#> $ hospitalized_with_symptoms: num 0 0 0 0 10 0 1 0 76 0 ...
#> $ intensive_care : num 0 0 0 0 2 0 1 0 19 0 ...
#> $ total_hospitalized : num 0 0 0 0 12 0 2 0 95 0 ...
#> $ home_confinement : num 0 0 0 0 6 0 0 0 71 0 ...
#> $ cumulative_positive_cases : num 0 0 0 0 18 0 2 0 166 0 ...
#> $ daily_positive_cases : num 0 0 0 0 0 0 0 0 0 0 ...
#> $ recovered : num 0 0 0 0 0 0 1 0 0 0 ...
#> $ death : num 0 0 0 0 0 0 0 0 6 0 ...
#> $ positive_clinical_activity: chr "" "" "" "" ...
#> $ positive_surveys_tests : chr "" "" "" "" ...
#> $ cumulative_cases : num 0 0 0 0 18 0 3 0 172 0 ...
#> $ total_tests : num 5 0 1 10 148 ...
#> $ total_people_tested : chr "" "" "" "" ...
#> $ new_intensive_care : chr "" "" "" "" ...
#> $ total_positive_tests : chr "" "" "" "" ...
#> $ total_fast_tests : chr "" "" "" "" ...
#> $ daily_positive_tests : chr "" "" "" "" ...
#> $ daily_fast_tests : chr "" "" "" "" ...
#> $ nuts_code_1 : chr "" "" "" "" ...
#> $ nuts_code_2 : chr "" "" "" "" ...
#> $ region_spatial : chr "Abruzzo" "Basilicata" "Calabria" "Campania" ...
head(italy_region)
#> date region_code region_name lat long
#> 1 2020-02-24 13 Abruzzo 42.35122 13.39844
#> 2 2020-02-24 17 Basilicata 40.63947 15.80515
#> 3 2020-02-24 18 Calabria 38.90598 16.59440
#> 4 2020-02-24 15 Campania 40.83957 14.25085
#> 5 2020-02-24 08 Emilia-Romagna 44.49437 11.34172
#> 6 2020-02-24 06 Friuli Venezia Giulia 45.64944 13.76814
#> hospitalized_with_symptoms intensive_care total_hospitalized home_confinement
#> 1 0 0 0 0
#> 2 0 0 0 0
#> 3 0 0 0 0
#> 4 0 0 0 0
#> 5 10 2 12 6
#> 6 0 0 0 0
#> cumulative_positive_cases daily_positive_cases recovered death
#> 1 0 0 0 0
#> 2 0 0 0 0
#> 3 0 0 0 0
#> 4 0 0 0 0
#> 5 18 0 0 0
#> 6 0 0 0 0
#> positive_clinical_activity positive_surveys_tests cumulative_cases
#> 1 0
#> 2 0
#> 3 0
#> 4 0
#> 5 18
#> 6 0
#> total_tests total_people_tested new_intensive_care total_positive_tests
#> 1 5
#> 2 0
#> 3 1
#> 4 10
#> 5 148
#> 6 58
#> total_fast_tests daily_positive_tests daily_fast_tests nuts_code_1
#> 1
#> 2
#> 3
#> 4
#> 5
#> 6
#> nuts_code_2 region_spatial
#> 1 Abruzzo
#> 2 Basilicata
#> 3 Calabria
#> 4 Campania
#> 5 Emilia-Romagna
#> 6 Friuli-Venezia GiuliaThe italy_region dataset provides an overall summary of the cases in Italy’s regions. The dataset contains the following fields:
date - timestamp, a Date objectregion_code - the region coderegion_name - the region nameprovince_code - the province codeprovince_name - the province nameprovince_abb - the province abbreviationlat - province latitude coordinatelong - province longitude coordinatetotal_cases - total number of positive cases (cumulative)new_tests - daily number of positive casesprovince_spatial - the spatial province names as in the output of the ne_states function from the rnaturalearth packagedata(italy_province)
str(italy_province)
#> Classes 'tbl_df', 'tbl' and 'data.frame': 74918 obs. of 14 variables:
#> $ date : Date, format: "2020-02-24" "2020-02-24" ...
#> $ region_name : chr "Abruzzo" "Abruzzo" "Abruzzo" "Abruzzo" ...
#> $ region_code : chr "13" "13" "13" "13" ...
#> $ province_name : chr "L'Aquila" "Teramo" "Pescara" "Chieti" ...
#> $ province_spatial: chr "L'Aquila" "Teramo" "Pescara" "Chieti" ...
#> $ province_abb : chr "AQ" "TE" "PE" "CH" ...
#> $ province_code : chr "066" "067" "068" "069" ...
#> $ lat : num 42.4 42.7 42.5 42.4 NA ...
#> $ long : num 13.4 13.7 14.2 14.2 NA ...
#> $ new_cases : num 0 0 0 0 0 0 0 0 0 0 ...
#> $ total_cases : num 0 0 0 0 0 0 0 0 0 0 ...
#> $ nuts_code_1 : chr "" "" "" "" ...
#> $ nuts_code_2 : chr "" "" "" "" ...
#> $ nuts_code_3 : chr "" "" "" "" ...
head(italy_province)
#> date region_name region_code province_name
#> 1 2020-02-24 Abruzzo 13 L'Aquila
#> 2 2020-02-24 Abruzzo 13 Teramo
#> 3 2020-02-24 Abruzzo 13 Pescara
#> 4 2020-02-24 Abruzzo 13 Chieti
#> 5 2020-02-24 Abruzzo 13 In fase di definizione/aggiornamento
#> 6 2020-02-24 Basilicata 17 Potenza
#> province_spatial province_abb province_code lat
#> 1 L'Aquila AQ 066 42.35122
#> 2 Teramo TE 067 42.65892
#> 3 Pescara PE 068 42.46458
#> 4 Chieti CH 069 42.35103
#> 5 In fase di definizione/aggiornamento 979 NA
#> 6 Potenza PZ 076 40.63947
#> long new_cases total_cases nuts_code_1 nuts_code_2 nuts_code_3
#> 1 13.39844 0 0
#> 2 13.70440 0 0
#> 3 14.21365 0 0
#> 4 14.16755 0 0
#> 5 NA 0 0
#> 6 15.80515 0 0These 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.
Health stats visible at Monitor.