cleaning the memory and screen then loading the required libraries
rm(list = ls()) # clear environment
cat("\014") # clear console
library(rio)
defingn folder for loading/saving data
platform<-"mac"
#platform<-"windows"
if(platform=="mac"){base_folder<-"/Users/hamid"}else{base_folder<-"C:/Users/hza0020"}
if(platform=="mac"){library(doMC)}
import SAS file and selecting pre surgery associated columns (variables). Finally chosing just heart transplant surgeries (excluding lung)
data<-import(paste(base_folder,"/OneDrive - Auburn University/Transplant Dataset/SAS Dataset/Thoracic/thoracic_data.sas7bdat",sep = ""))
export(data,paste(base_folder,"/OneDrive - Auburn University/Transplant Dataset/SAS Dataset/Thoracic/Heart_before_surgery.csv",sep = ""))
data<-import(paste(base_folder,"/OneDrive - Auburn University/Transplant Dataset/SAS Dataset/Thoracic/Heart_before_surgery.csv",sep = ""))
##
Read 43.9% of 159318 rows
Read 81.6% of 159318 rows
Read 159318 rows and 494 (of 494) columns from 0.145 GB file in 00:00:04
before_surgery<-import(paste(base_folder,"/OneDrive - Auburn University/Transplant/chronical/12-2-2017/before_transplant_patients_donnor_data.xlsx",sep=""))
S0 <- as.character(before_surgery$vars)
data <- data[, which(names(data) %in% S0)]
data<-as.data.frame(data)
data[data == ""] <- NA
gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 764533 40.9 1442291 77.1 1292958 69.1
## Vcells 56148310 428.4 174069491 1328.1 174053899 1328.0
data[data == " "] <- NA
gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 764838 40.9 1442291 77.1 1292958 69.1
## Vcells 56410701 430.4 174069491 1328.1 174053899 1328.0
data[data == "U"] <- NA
gc()
## used (Mb) gc trigger (Mb) max used (Mb)
## Ncells 764941 40.9 1442291 77.1 1292958 69.1
## Vcells 56411204 430.4 174069491 1328.1 174053899 1328.0
data_Heart_HR<-data[which(data$ORGAN=="HR"),]
saving the file for the shiny app
write.csv(data_Heart_HR,paste(base_folder,"/OneDrive - Auburn University/Transplant Dataset/SAS Dataset/Thoracic/data_Heart_HR",sep = ""))