Dear Rami,
I create a new project on my R Server using your GitHub repository. The only change was adding: runtime: shiny in the header of the rmarkdown file.
Maybe it depends on the use of leaflet you used in your code? As: rstudio/leaflet#664 (comment)

Running shiny the first time was ok. With a new session I got this error log:

Loading required package: shiny

Listening on http://127.0.0.1:4566
Warning: Error in value[[3L]]: Couldn't normalize path in addResourcePath, with arguments: prefix = 'leaflet-providers-1.9.0'; directoryPath = '/tmp/Rtmp31Vtod'
108: stop
107: value[[3L]]
106: tryCatchOne
105: tryCatchList
104: tryCatch
103: addResourcePath
102: FUN
101: lapply
100: processDeps
99: transform
98: func
96: f
95: Reduce
86: do
85: hybrid_chain
84: origRenderFunc
83: output$reactivedoc
3:
1: rmarkdown::run

Can you help me to understand where is the “bug”?
Thanks

i want to make a China dash, could you help me, thanks.

Dear Rami,
wonderful job first of all.
Just wanted to give few lines of R code you might attach after line
home_conf_color <- "#FDBBBC"
of your index.Rmd script in order to solve the NA values in the dashboard map of Italian regions.

``

rename region in correct way

italy_region$region_name <- gsub("Puglia", "Apulia",italy_region$region_name)
italy_region$region_name <- gsub("Emilia Romagna","Emilia-Romagna" ,italy_region$region_name)
italy_region$region_name <- gsub("Friuli Venezia Giulia" ,"Friuli-Venezia Giulia",italy_region$region_name)
italy_region$region_name <- gsub("Sicilia" ,"Sicily",italy_region$region_name)

merge Bolzano and Trento subregions in one region called Trentino-Alto Adige

trentino <- italy_region %>%
dplyr::filter(grepl("Bolzano|Trento", italy_region$region_name),
date == max(date)) # take max date

rename

trentino$region_name <- gsub("P.A. Bolzano", "Trentino-Alto Adige", trentino$region_name)
trentino$region_name <- gsub("P.A. Trento", "Trentino-Alto Adige", trentino$region_name)

Input common lat and long

trentino$lat[1] <- 46.4337
trentino$lat[2] <- 46.4337
trentino$long[1] <- 11.1693
trentino$long[2] <- 11.1693

trentino <- trentino %>% group_by(date, region_code, region_name, lat, long) %>%
summarise_all(funs(sum)) # summarise subregions values in ONE region

convert to df before rbind

trentino <- as.data.frame(trentino)
italy_region <- rbind(trentino, italy_region)

filter out old subregions values as now not needed

italy_region <- italy_region %>% dplyr::filter(!grepl("P.A. Bolzano|P.A. Trento", region_name))
``

PS: It requires library(tidyverse) within setup chunk of course as I'm using group_by function
Thanks a lot again and greetings from Italy!
Keep the good job!
Best regards

#Giuseppe

As the many changes occurred since the release of v0.1.0 significant changes in the data structure expected in v0.2.0 (expected to release to CRAN by May 15. Changes are available on the dev-v020 branch

Those changes impact the covid19 Italy dashboard. Please see the following commit with the changes needed to keep the dashboard working.

coronavirus 0.2.0

• Data changes:
  • coronavirus dataset - Change the structure of the US data from March 23rd, 2020 and forward. The US data is now available on an aggregated level. More information about the changes in the raw data available on this issue
  • Changes in the columns names and order:
    • Province.State changed to province
    • Country.Region changed to country
    • Lat changed to lat
    • Long changed to long
  • The covid_south_korea and covid_iran that were avialble on the dev version were removed from the package and moved to new package covid19wiki, for now available only on Github