The covid19tunisia R package provides a tidy format dataset of the 2019 Novel Coronavirus COVID-19 (2019-nCoV) pandemic outbreak in Tunisia. The package covers a daily summary of the outbreak on the national level.
The data was pull from :
Official Facebook page of the Tunisian Ministry of Health through their daily published press releases.
Regional governments in Tunisia.
You can install the released version of covid19tunisia from CRAN with:
The covid19tunisia dataset provides an overall summary
of the cases in Tunisia since the beginning of the covid19 outbreak on
March 2, 2020. The dataset contains the following fields:
▲ date - The date in YYYY-MM-DD form.
▲ location - The name of the government as provided by
the data sources.
▲ location_type - The type of location using the
covid19R controlled vocabulary. In this case, it’s “state”.
▲ location_code - A standardized location code using a
national or international standard. In this case, . See https://www.iso.org/obp/ui/#iso:code:3166:TN for
details.
▲ 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.
Includes cases new : new confirmed Covid-19 cases during on the current
date, recovered_new : new number of patients recovered on the current
date and deaths_new : new deaths on the current date.
▲ value - number of cases of each data type.
library(covid19tunisia)
data <- refresh_covid19tunisia()
#> Downloading raw data from https://raw.githubusercontent.com/MounaBelaid/covid19datatunisia/master/dist/data.csv.
head(data)
#> # A tibble: 6 × 7
#> date location location_type location_code location_code_type data_type
#> <date> <chr> <chr> <chr> <chr> <chr>
#> 1 2020-03-02 Gafsa state TN-71 iso_3166_2 cases_new
#> 2 2020-03-08 Mahdia state TN-53 iso_3166_2 cases_new
#> 3 2020-03-09 Bizerte state TN-23 iso_3166_2 cases_new
#> 4 2020-03-09 Mahdia state TN-53 iso_3166_2 cases_new
#> 5 2020-03-09 Tunis state TN-11 iso_3166_2 cases_new
#> 6 2020-03-10 Mahdia state TN-53 iso_3166_2 cases_new
#> # ℹ 1 more variable: value <dbl>
str(data)
#> spc_tbl_ [5,298 × 7] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
#> $ date : Date[1:5298], format: "2020-03-02" "2020-03-08" ...
#> $ location : chr [1:5298] "Gafsa" "Mahdia" "Bizerte" "Mahdia" ...
#> $ location_type : chr [1:5298] "state" "state" "state" "state" ...
#> $ location_code : chr [1:5298] "TN-71" "TN-53" "TN-23" "TN-53" ...
#> $ location_code_type: chr [1:5298] "iso_3166_2" "iso_3166_2" "iso_3166_2" "iso_3166_2" ...
#> $ data_type : chr [1:5298] "cases_new" "cases_new" "cases_new" "cases_new" ...
#> $ value : num [1:5298] 1 1 1 1 1 1 1 3 3 1 ...
#> - attr(*, "spec")=
#> .. cols(
#> .. date = col_date(format = ""),
#> .. location = col_character(),
#> .. location_type = col_character(),
#> .. location_code = col_character(),
#> .. location_code_type = col_character(),
#> .. data_type = col_character(),
#> .. value = col_double()
#> .. )
#> - attr(*, "problems")=<externalptr># Transform the data
library(dplyr)
library(tidyr)
library(plotly)
data_transformed <- data %>% group_by(date,data_type) %>% summarise(value=sum(value)) %>%
spread(data_type,value)
head(data_transformed)
# A tibble: 6 x 4
# Groups: date [6]
date cases_new deaths_new recovered_new
<date> <dbl> <dbl> <dbl>
1 2020-03-02 1 0 0
2 2020-03-08 1 0 0
3 2020-03-09 3 0 0
4 2020-03-10 1 0 0
5 2020-03-11 1 0 0
6 2020-03-12 6 0 0
data_transformed %>%
ungroup() %>% plot_ly(type = 'scatter',
mode = 'lines+markers')%>%
add_trace(x = ~date, y = ~cumsum(cases_new),
name = 'Confirmed cases',
marker = list(color = '#fec44f'),
line = list(color = '#fec44f'),
hoverinfo = "text",
text = ~paste(cases_new, "New confirmed cases\n",cumsum(cases_new), 'Total number of infected cases on', date)) %>%
add_trace(x = ~date, y = ~cumsum(deaths_new),
name = 'Deaths',
marker = list(color = 'red'),
line = list(color = 'red'),
hoverinfo = "text",
text = ~paste(deaths_new, "New deaths\n",cumsum(deaths_new), 'Total number of deaths on', date)) %>%
add_trace(x = ~date, y = ~cumsum(recovered_new),
name = 'Recovered cases',
marker = list(color = 'green'),
line = list(color = 'green'),
hoverinfo = "text",
text = ~paste(recovered_new, "New recovered cases\n",cumsum(recovered_new), 'Total number of recovered cases on', date)) %>%
layout(title = 'Tunisia - Daily Evolution of Active COVID19 Cases',
legend = list(x = 0.1, y = 0.9,
font = list(family = "sans-serif", size = 14, color = "#000"), bgcolor = "",
bordercolor = "#FFFFFF", borderwidth = 2),
xaxis = list(title = ""),
yaxis = list(side = 'left', title = 'Daily evolution', showgrid = TRUE, zeroline = TRUE))