final?

conversion_upload.R

@@ -15,99 +15,33 @@ library(readxl)
 library(dplyr)
 
 ## -----------------------------------------------------------------------------
-## Data
+## Data file load
 ## -----------------------------------------------------------------------------
 
 setwd("/Volumes/Data/toorisky/")
 
-dta_ls<-list()
+dta<-read_dta("Alle apo Aarhus 2018.dta") %>% # Defined dataset
-dta_ls[1]<-read_dta("Alle apo Aarhus 2018.dta") %>% filter(VaskDiag==1) %>% 
+  filter(VaskDiag==1) %>% 
-    mutate(treatment=factor(case_when(trombolyse!=2&trombektomi!=2 ~ 0,
+  mutate(treatment=factor(case_when(trombolyse!=2&trombektomi!=2 ~ 0,
-                                      trombolyse==2|trombektomi==2 ~ 1)),
+                                    trombolyse==2|trombektomi==2 ~ 1)),
-           sex.n=factor(ifelse(as.integer(substr(cpr, start = 10, stop = 10)) %%2 == 0, 
+         sex.n=factor(ifelse(as.integer(substr(cpr, start = 10, stop = 10)) %%2 == 0, 
-                               "female", "male"))) %>%
+                             "female", "male"))) %>%
-    left_join(.,read_excel("2022-02-08_ddsc_dataexport.xlsx", sheet = "Patienter"),
+  left_join(.,read_excel("2022-02-08_ddsc_dataexport.xlsx", sheet = "Patienter"),
-              by=c("ForloebID"="forloebid","cpr"="cpr"))
+            by=c("ForloebID"="forloebid"))%>%
+  left_join(.,read_excel("2022-02-08_ddsc_dataexport.xlsx", sheet = "3 mdr. opf."),
+            by=c("ForloebID"="ForloebID"))%>%
+  mutate(cpr=cpr.x,
+         ID=ID.x)%>%
+  dplyr::select(-starts_with("cpr."))%>%
+  dplyr::select(-starts_with("ID."))
 
-
+colnames(dta)<-tolower(colnames(dta))
-
-dta_ls[2]<-read_excel("2022-02-08_ddsc_dataexport.xlsx", sheet = "3 mdr. opf.") # This excludes patients not treated and not candidates, but included by mistake in the register. Manually adjusted.
-## Her mangler filter for kun at inkludere dem, fra baseline
-
-setwd("/Users/au301842/nottreated/")
     
 ## -----------------------------------------------------------------------------
-## Data dictionary
+## Fix missing record_id's for upload
-## -----------------------------------------------------------------------------
-
-icname<-colnames(read.csv("examlpe instrument.csv"))
-dd<-data.frame(matrix(ncol = length(icname))) ## Data frame to collect all
-colnames(dd)<-icname
-
-## Tilpasses
-## -----------------------------------------------------------------------------
-## -----------------------------------------------------------------------------
-
-for (i in 1:length(r_lup)){
-  dd_i<-data.frame(matrix(ncol = length(icname),nrow = ncol("[["(r_lup,i)))) ## Data frame to collect all
-  
-  colnames(dd_i)<-icname ## for easier reading
-  
-  ## Variable names
-  dd_i[1]<-colnames("[["(r_lup,i))
-  
-  ## Form Name
-  dd_i[2]<-names(r_lup)[i]
-  
-  ## Field Type
-  # dd_i[4]<-ifelse(sapply(r_lup[[i]], class)=="factor","radio","text")
-  dd_i[4]<-"text"
-  
-  ## Field Label
-  ## Using original attributes as field labels
-  fl<-lapply(r_lup[[i]], attr, "label")
-  for (j in 1:length(fl)){
-    fl[[j]]<-ifelse(is.null(fl[[j]]),
-                    names(fl)[[j]],
-                    fl[[j]])
-    ##  If no attributes, variable name is used as "placeholder"
-  }
-  dd_i[5]<-unlist(fl)
-  
-  ## Choices
-  # for (j in 1:ncol(r_lup[[i]])){
-  #   if (is.factor(r_lup[[i]][[j]])){
-  #     lvl<-levels(r_lup[[i]][[j]])
-  #     lvl_ch<-paste("1,",lvl[1])
-  #     for (k in 2:length(lvl)){
-  #       lvl_ch<-c(paste0(lvl_ch," | ",k,", ",lvl[k]))
-  #     }
-  #     dd_i[j,6]<-lvl_ch
-  #   }
-  # }
-  
-  ## Text Validation
-  ## Only used for date and time data
-  # for (j in 1:ncol(r_lup[[i]])){
-  #   dd_i[j,8]<-case_when(class(r_lup[[i]][[j]])[1]%in%c("POSIXct","POSIXt") ~"datetime_seconds_ymd",
-  #                        class(r_lup[[i]][[j]])[1]%in%c("Date") ~"date_ymd")
-  # }
-  
-  ## Merge all
-  dd<-rbind(dd,dd_i)
-  
-  if (exp_out){
-    # dir.create(file.path("/Volumes/Data/REDCap/data",names(r_lup)[[i]]))
-    write.csv(r_lup[[i]],paste0("/Volumes/Data/REDCap/data/",names(r_lup)[[i]],".csv"),row.names = FALSE)
-  }
-  
-}
-
-
-## -----------------------------------------------------------------------------
-## REDCap pull
 ## -----------------------------------------------------------------------------
 
+## REDCap pull with minimum data
 token=names(suppressWarnings(read.csv("/Users/au301842/nottreated_redcap_token.csv",colClasses = "character")))
 uri="https://redcap.au.dk/api/"
 
@@ -115,11 +49,51 @@ library(REDCapR)
 
 redcap <- redcap_read_oneshot(
   redcap_uri   = uri,
-  token        = token
+  token        = token,
+  fields = c("record_id","forloebid")
 )$data
 
+
+## Joining and adding record_id's
+dta<-full_join(dta,redcap)
+
+n_na<-length(dta$record_id[is.na(dta$record_id)])
+n_id<-max(dta$record_id,na.rm=T)
+# filter(!is.na(akut_ind))%>%
+dta$record_id[is.na(dta$record_id)]<-(n_id+1):(n_id+n_na) # Simple math
+
 ## -----------------------------------------------------------------------------
-## Data preparation
+## Data dictionary
 ## -----------------------------------------------------------------------------
 
+setwd("/Users/au301842/nottreated/")
 
+icname<-colnames(read.csv("examlpe instrument.csv"))
+dd<-data.frame(matrix(ncol = length(icname),
+                      nrow=ncol(dta))) ## Data frame to collect all
+colnames(dd)<-icname
+
+## Variable names
+dd[1]<-colnames(dta)
+
+## Form Name
+dd[2]<-"ddsc"
+
+## Field Type
+# dd_i[4]<-ifelse(sapply(r_lup[[i]], class)=="factor","radio","text")
+dd[4]<-"text"
+
+dd[5]<-colnames(dta)
+
+
+## -----------------------------------------------------------------------------
+## Instrument file
+## -----------------------------------------------------------------------------
+
+write.csv(dd,"ddsc_instrument.csv",row.names = FALSE,na="")
+
+## -----------------------------------------------------------------------------
+## Dataset export
+## -----------------------------------------------------------------------------
+
+write.csv(dta,"ddsc_dataset.csv",row.names = FALSE)