library(xlsx)
library(openxlsx)
library(lubridate)
library(stringi)
library(readxl)
library(httr)
library(naniar)
library(viridis)
library(RColorBrewer)
cumHospNumbers <-  data.frame(matrix(ncol=2,nrow=0))
colnames(cumHospNumbers) <- c("runID", "hospNumbers")
runs <- c(162,0,9,81,171,10,11,12,15,63,36,14,17,38,41,42,44)
run <- 162
runs <- c(162,0,9,81,171,10,11,12,15,63,36,14,17,38,41,42,44)
run <- 162
setwd("/Users/syd/IdeaProjects/public-svn/matsim/scenarios/countries/de/episim/battery/jakob/2022-10-18/3-meas/summaries")
runData <- read_delim(unz(paste0(run,".zip"), paste0(run,".post.hospital.tsv")))
setwd("/Users/jakob/git/public-svn/matsim/scenarios/countries/de/episim/battery/jakob/2022-10-18/3-meas/summaries")
runData <- read_delim(unz(paste0(run,".zip"), paste0(run,".post.hospital.tsv")))
library(xlsx)
runData <- read_delim(unz(paste0(run,".zip"), paste0(run,".post.hospital.tsv")))
library(tidyverse)
library(xlsx)
library(openxlsx)
library(lubridate)
library(stringi)
library(readxl)
library(httr)
library(naniar)
library(viridis)
library(RColorBrewer)
runData <- read_delim(unz(paste0(run,".zip"), paste0(run,".post.hospital.tsv")))
runData <- filter(runData, date > "2022-10-31" & date < "2023-04-01")
runData <- filter(runData, severity == "Delta")
runData <- filter(runData, measurement == "intakesHosp")
cumHospNumbers[nrow(cumHospNumbers)+1,1] <- run
cumHospNumbers[nrow(cumHospNumbers),2] <- sum(runData$n)
View(runData)
View(runData)
sum(runData$n)
DSJHJKLSD <-sum(runData$n)
DSJHJKLSD <-runData$n
print(DSJHJKLSD)
view(DSJHJKLSD)
writeClipboard(DSJHJKLSD)
View(runData)
runs <- c(162,0,9,81,171,10,11,12,15,63,36,14,17,38,41,42,44)
for(run in runs){
setwd("/Users/jakob/git/public-svn/matsim/scenarios/countries/de/episim/battery/jakob/2022-10-18/3-meas/summaries")
runData <- read_delim(unz(paste0(run,".zip"), paste0(run,".post.hospital.tsv")))
runData <- filter(runData, date > "2022-10-31" & date < "2023-04-01")
runData <- filter(runData, severity == "Delta")
runData <- filter(runData, measurement == "intakesHosp")
cumHospNumbers[nrow(cumHospNumbers)+1,1] <- run
cumHospNumbers[nrow(cumHospNumbers),2] <- sum(runData$n)
}
View(cumHospNumbers)
cumHospNumbers <-  data.frame(matrix(ncol=2,nrow=0))
colnames(cumHospNumbers) <- c("runID", "hospNumbers")
runs <- c(162,0,9,81,171,10,11,12,15,63,36,14,17,38,41,42,44)
run <- 162
for(run in runs){
setwd("/Users/jakob/git/public-svn/matsim/scenarios/countries/de/episim/battery/jakob/2022-10-18/3-meas/summaries")
runData <- read_delim(unz(paste0(run,".zip"), paste0(run,".post.hospital.tsv")))
runData <- filter(runData, date > "2022-10-31" & date < "2023-04-01")
runData <- filter(runData, severity == "Delta")
runData <- filter(runData, measurement == "intakesHosp")
cumHospNumbers[nrow(cumHospNumbers)+1,1] <- run
cumHospNumbers[nrow(cumHospNumbers),2] <- sum(runData$n)
}