LoadJapan.R

LoadJapan <- function(){
data <- read_json('https://raw.githubusercontent.com/reustle/covid19japan-data/master/docs/summary/latest.json', encoding ='UTF-8')
# get updated date:
date <- as.Date(data$updated)
## PREFECTURE = COUNTY
# in data, there are 4 layers
# take the prefecture layer to get necessary data
dataSet <- data$prefectures 
# List the name of prefectures:
vec <- data.frame(Prefecture = as.character(), Difference = as.numeric())
getData <- function(i){
  info <- unlist(dataSet[i]) 
  fields <- names(unlist(dataSet[i])) # get the column names
  daily <- info[startsWith(fields, 'dailyConfirmedCount')] # find any column start with dailyConfirmedCount
  lenOfdaily <- length(daily) # get the index for the latest date
  past_id <- lenOfdaily - 14 # get the index for 14 days ago
  sum <- sum(as.numeric(daily[past_id:lenOfdaily])) ## get the total cases for 14 days
  difference <- round(sum*10/14) # remodified
  # get the name for this prefecture
  len <- length(unlist(unlist(dataSet[i])))
  name <- as.character(unlist(as.data.frame(unlist(dataSet[i])[len])))
  temp <- c(name,difference)
  return(temp)
}
# get data table
for (i in 1:49){
  dataVec <- getData(i)
  vec <- rbind(vec,dataVec)
}
names(vec) <- c('Prefecture','Difference')

## Geojson file
geomJap <- st_read('https://raw.githubusercontent.com/deldersveld/topojson/master/countries/japan/jp-prefectures.json')
geomJap <- geomJap[c('NAME_1','geometry')]
geomJap[geomJap$NAME_1 == 'Naoasaki',1] <- "Nagasaki"
geomJap = st_set_crs(geomJap,4326)


## Population
pop <- read.csv('JapPopulation.csv')
japandf <- inner_join(vec,pop, by = 'Prefecture')
japandf$Difference <- as.numeric(japandf$Difference)

JapanMap <- inner_join(geomJap, japandf, by = c("NAME_1" = "Prefecture"))
JapanMap$RegionName = paste0(JapanMap$NAME_1,", Japan")
JapanMap$DateReport = as.character(date) 
JapanMap$pInf = JapanMap$Difference/JapanMap$Population

JAPAN_DATA = subset(JapanMap,select=c("DateReport","RegionName","pInf","geometry"))
return(JAPAN_DATA)
}