using mutate, paste0 and case_when in iteration; problem with mutating existing variables with paste0

@r2evans For your request, here is a snapshot of the dataframe

and the values for dput(head(as)) is as follows (partial)

# dput(head(as[, c("AS1_WEIGHT", "AS2_WEIGHT", "AS3_WEIGHT", "AS4_WEIGHT", "AS5_WEIGHT", "AS6_WEIGHT", "AS7_WEIGHT", "AS8_WEIGHT", "AS9_WEIGHT")]))
structure(list(AS1_WEIGHT = c(72, 59, 50, 55.2, 82.1, 50.4), 
    AS2_WEIGHT = c(74.8, NA, NA, 54.8, 84.5, 52.5), AS3_WEIGHT = c(75.2, 
    NA, NA, 55.9, 81.7, 54.6), AS4_WEIGHT = c(75, NA, NA, 55.1, 
    80.6, NA), AS5_WEIGHT = c(75.4, NA, NA, 58.8, 89.5, NA), 
    AS6_WEIGHT = c(77.3, NA, NA, NA, NA, NA), AS7_WEIGHT = c(70.7, 
    NA, NA, 56, NA, NA), AS8_WEIGHT = c(73.8, NA, NA, 55.5, NA, 
    NA), AS9_WEIGHT = c(74.5, NA, NA, 54.8, NA, 52)), class = "data.frame", row.names = c(NA, 
-6L))

I want to mutate existing variables in a loop using paste0, but I keep having error messages:

Error: unexpected symbol in:
" dplyr::mutate(AS1_WEIGHT = case_when(as$AS1_WEIGHT == '99999' & as$AS2_WEIGHT == '99999' ~ as$AS3_WEIGHT
as"


MRE:
as is a dataframe, code looks a bit complicated, but these are cohort datas gathered at 9 different timelines.

library(dplyr)
library(plyr)
library(magrittr)
library(stringr) 
library(ExclusionTable)
library(lubridate)
library(tidyverse)
library(janitor)
library(survival)
library(ggsurvfit)
library(gtsummary)
library(zoo)
library(tidycmprsk)

# AA cohort (2 of 3)
## as

num_fu = c(1,2,3,4,5,6,7,8,9)
as <- data.frame()
df <- data.frame()
dfs <- data.frame()
data_dir <- 'C:/Users/thepr/Documents/data/as'

i=1;
assign(paste0("flnames", i), list.files(path = paste0(data_dir, i), pattern = "\\.csv", full.names = TRUE))
assign(paste0("as", i, "_list"), lapply(get(paste0("flnames", i)),
                                        function(x){base::as.data.frame(read.csv(x))}))
nm <- gsub(".csv", "", basename(eval(parse(text = paste0("flnames", i))))) %>% str_sub(., 1,6)
assign(paste0("as", i, "_list"), setNames(get(paste0("as", i, "_list")), nm))
df <- Reduce(full_join, get(paste0("as", i, "_list")))
assign(paste0("as",i), df[!duplicated(base::as.list(df))])
dfs <- df

for (i in 2:length(num_fu)){
      assign(paste0("flnames", i), list.files(path = paste0(data_dir, i), pattern = "\\.csv", full.names = TRUE))
      assign(paste0("as", i, "_list"), lapply(get(paste0("flnames", i)),
                                              function(x){base::as.data.frame(read.csv(x))}))
      nm <- gsub(".csv", "", basename(eval(parse(text = paste0("flnames", i))))) %>% str_sub(., 1,6)
      assign(paste0("as", i, "_list"), setNames(get(paste0("as", i, "_list")), nm))
      df <- Reduce(full_join, get(paste0("as", i, "_list")))
      assign(paste0("as",i), df[!duplicated(base::as.list(df))])
      
      dfs <- merge(dfs, df, by = "RID", all.x = TRUE)
      dfs <- dfs[!duplicated(base::as.list(dfs))]
            if(length(grep(paste0("AS", i, "_AREA"), names(get(paste0("as", i))))) > 0){
              assign(paste0("fu_",i-1), get(paste0("as", i))[as1$RID %in% get(paste0("as", i))$RID, c("RID", paste0("AS", i, "_AREA"))])
              assign(paste0("fu_loss_",i-1), get(paste0("as", i))[!as1$RID %in% get(paste0("as", i))$RID, c("RID", paste0("AS", i, "_AREA"))])
              # FU rate
              assign(paste0("fu_rate_", i-1), round(nrow(get(paste0("as", i)))/nrow(as1), 2))
            }
              else{
                  assign(paste0("fu_",i-1), get(paste0("as", i))[as1$RID %in% get(paste0("as", i))$RID, c("RID", paste0("AS", i, "_DATA_CLASS"))])
                  assign(paste0("fu_loss_",i-1), get(paste0("as", i))[!as1$RID %in% get(paste0("as", i))$RID, c("RID", paste0("AS", i, "_DATA_CLASS"))])
                  # FU rate
                  assign(paste0("fu_rate_", i-1), round(nrow(get(paste0("as", i)))/nrow(as1), 2))
            }
}

as <- dfs
as <- as[!duplicated(base::as.list(as))]
rm(list = intersect(ls(), c("df", "dfs", "i")))

And below is where I am having a trouble (including the parsing error)

i=2
for (i in 2:length(num_fu)-1){
  print(i)
  if(i<length(num_fu)){
    as %<>%
      dplyr::mutate(paste0("AS", i, "_WEIGHT") = case_when(is.na(as[,paste0("AS", i, "_WEIGHT")]) ~ NA_character_
                                                                as[,paste0("AS", i, "_WEIGHT")] == '99999' ~ as[,paste0("AS", i+1, "_WEIGHT")],
                                                                as[,paste0("AS", i, "_WEIGHT")] != '99999' ~ as[,paste0("AS", i, "_WEIGHT")],
                                                                TRUE ~ NA_character_), na.rm = TRUE)
  }
  paste0("D_WEIGHT", i-1) <- round(100*(as[,paste0("AS", i, "_WEIGHT")]-as[,paste0("AS", i-1, "_WEIGHT")])/as[,paste0("AS", i-1, "_WEIGHT")], 1)
}

However,

i=2
as %<>%
   mutate(paste0("AS", i, "_WEIGHT") = 1

spits out the same error message, while

as %<>%
   mutate(AS2_WEIGHT) = 1

works fine.

Expected output would be:
Every column(as$AS1_WEIGHT ... as$AS9_WEIGHT) with value 99999 will be replaced by the value in the same row, but in the adjacent column.

I saw that using !!! might be necessary but I am lost.

Any comments will be helpful. Thank you.

I'm assuming the main task here is to replace 99999 values with the value found in the next column to the right. Here, I pivot longer so that the value to the right is the following value (i.e. lead(value)) within each row group.

Not sure what behavior you want if two adjacent columns both have '99999' values.

library(tidyverse)
as <- as %>%
  mutate(row = row_number()) %>%
  pivot_longer(-row) %>%
  mutate(value = if_else(value == '99999', lead(value), value), .by = row) %>%
  pivot_wider(names_from = name, values_from = value)