Minor additions to include cpr and forloeabid for new entries

conversion_upload.R

@@ -63,8 +63,40 @@ for (i in 1:length(r_lup)){
   cnames<-c(cnames,colnames(r_lup[[i]]))
 }
 
+## -----------------------------------------------------------------------------
+## Fix missing record_id's for upload
+## -----------------------------------------------------------------------------
 
+## REDCap pull with minimum data
+token=names(suppressWarnings(read.csv("/Users/au301842/nottreated_redcap_token.csv",colClasses = "character")))
+uri="https://redcap.au.dk/api/"
+
+library(REDCapR)
+
+redcap <- redcap_read_oneshot(
+  redcap_uri   = uri,
+  token        = token,
+  # forms = "ID",
+  fields = c("record_id","forloebid")
+)$data|>
+  filter(record_id %in% 1:204) # Selecting only the first 204
+
+## Adding and creating record_id's
+ids_r<-full_join(ids,redcap)
+
+n_na<-length(ids_r$record_id[is.na(ids_r$record_id)])
+n_id<-max(ids_r$record_id,na.rm=T)
+# filter(!is.na(akut_ind))%>%
+ids_r$record_id[is.na(ids_r$record_id)]<-(n_id+1):(n_id+n_na) # Simple math
+
+for (i in 1:length(r_lup)){
+  r_lup[[i]]<-left_join(r_lup[[i]],ids_r)
+}
+
+## -----------------------------------------------------------------------------
 ## Appending suffix for duplicated colnames from different sheets
+## -----------------------------------------------------------------------------
+
 dup_names<-unique(cnames[duplicated(cnames)])[-1] # omit the first, "forloebid"
 
 for (i in 1:length(r_lup)){
@@ -82,32 +114,14 @@ for (i in 1:length(r_lup)){
 }
 
 ## -----------------------------------------------------------------------------
-## Fix missing record_id's for upload
+## Creating ID instrument data - fidly!
 ## -----------------------------------------------------------------------------
 
-## REDCap pull with minimum data
+id_data<-read_excel("/Volumes/Data/toorisky/2022-02-08_ddsc_dataexport.xlsx", sheet = "Patienter")|>
-token=names(suppressWarnings(read.csv("/Users/au301842/nottreated_redcap_token.csv",colClasses = "character")))
+  select(c("cpr","forloebid"))|>
-uri="https://redcap.au.dk/api/"
+  filter(forloebid %in% r_lup$Patienter$forloebid)|>
+  full_join(ids_r)
 
-library(REDCapR)
-
-redcap <- redcap_read_oneshot(
-  redcap_uri   = uri,
-  token        = token,
-  fields = c("record_id","forloebid")
-)$data
-
-## Adding and creating record_id's
-ids_r<-full_join(ids,redcap)
-
-n_na<-length(ids_r$record_id[is.na(ids_r$record_id)])
-n_id<-max(ids_r$record_id,na.rm=T)
-# filter(!is.na(akut_ind))%>%
-ids_r$record_id[is.na(ids_r$record_id)]<-(n_id+1):(n_id+n_na) # Simple math
-
-for (i in 1:length(r_lup)){
-  r_lup[[i]]<-left_join(r_lup[[i]],ids_r)
-}
 
 ## -----------------------------------------------------------------------------
 ## Data dictionary
@@ -198,22 +212,8 @@ for (i in 1:length(inst_names)){
 exp<-r_lup|>
   purrr::reduce(full_join)|>
   select(-matches("forloebid"))|>
-  select(record_id,everything()) # To arrange "record_id" as first column
+  select(record_id,everything())|> # To arrange "record_id" as first column
+  full_join(id_data) # Adding cpr and forloebid to the newly added
 
 write.csv(exp,"ddsc_dataset.csv",row.names = FALSE,na="")
 
-
-## -----------------------------------------------------------------------------
-## Dataset export of remaing
-## -----------------------------------------------------------------------------
-
-## REDCap faces troubles importing too large data sets. Apparently.
-
-ups <- redcap_read_oneshot(
-  redcap_uri   = uri,
-  token        = token,
-  fields = "record_id"
-)$data
-
-write.csv(exp|>
-            filter(!record_id %in% ups$record_id),"ddsc_dataset_remain.csv",row.names = FALSE,na="")