Moving data from right to left column in a tibble

Question

I have a tibble with information about diagnoses:

data <- tibble(
  id = c(1:10),
  diagnosis_1 = c("F32", "F431", "R58", "S32", "F11", NA, NA, "Y67", "F32", "Z032"),
  diagnosis_2 = c(NA, NA, NA, NA, NA, NA, "G35", NA, NA, NA),
  diagnosis_3 = c("F40", NA, "R67", "F431", NA, "F60", "S58", "R68", "F11", NA),
  diagnosis_4 = c(NA, NA, "F65", NA, "F19", NA, NA, "F32", NA, NA)
)

As a part of the cleaning process, I have removed all diagnoses not fulfilling certain criteria (i.e. not starting with the letter F, G, or Z). With the following code:

data$diagnosis_1[str_sub(data$diagnosis_1, 1,1) %in% c("R", "S", "Y")] <- NA
data$diagnosis_2[str_sub(data$diagnosis_2, 1,1) %in% c("R", "S", "Y")] <- NA
data$diagnosis_3[str_sub(data$diagnosis_3, 1,1) %in% c("R", "S", "Y")] <- NA
data$diagnosis_4[str_sub(data$diagnosis_4, 1,1) %in% c("R", "S", "Y")] <- NA

Ending up with this tibble:

I now need to move the data to the left to fill the columns from left to right (i.e diagnosis_1 not being empty if diagnosis_2, diagnosis_3 or diagnosis_4 has data). I have tried using ifelse() as it is vectorized but I can`t seem to get it to work with several nested ifelse().

ifelse(is.na(data$diagnosis_1), data$diagnosis_2, data$diagnosis_1))

All suggestions are much appreciated.

Edit: adding expected output:

Answer 1

Using dplyr and tidyr. Reshape from wide to long, exclude "^RSY" and NA diagnosis, reshape long to wide.

library(dplyr)
library(tidyr)

gather(data, key = "k", value = "v", -id) %>% 
  filter(!(grepl("^[R|S|Y]", v) | is.na(v))) %>% 
  group_by(id) %>% 
  mutate(diagN = paste0("diagnosis_", row_number())) %>% 
  select(-k) %>% 
  spread(key = "diagN", value = "v") %>% 
  ungroup()

# # A tibble: 10 x 3
#       id diagnosis_1 diagnosis_2
#    <int> <chr>       <chr>      
#  1     1 F32         F40        
#  2     2 F431        NA         
#  3     3 F65         NA         
#  4     4 F431        NA         
#  5     5 F11         F19        
#  6     6 F60         NA         
#  7     7 G35         NA         
#  8     8 F32         NA         
#  9     9 F32         F11        
# 10    10 Z032        NA  

Answer 2

We first replace values which start with either "R", "S" or "Y" to NA and then left shift the non-NA values.

data[-1] <- lapply(data[-1], function(x) replace(x, grepl("^[R|S|Y]", x), NA))  
data[] <- t(apply(data, 1, function(x) `length<-`(na.omit(x), length(x))))

data
# A tibble: 10 x 5
#     id diagnosis_1 diagnosis_2 diagnosis_3 diagnosis_4
#   <chr> <chr>       <chr>       <chr>       <chr>      
# 1 " 1"  F32         F40         NA          NA         
# 2 " 2"  F431        NA          NA          NA         
# 3 " 3"  F65         NA          NA          NA         
# 4 " 4"  F431        NA          NA          NA         
# 5 " 5"  F11         F19         NA          NA         
# 6 " 6"  F60         NA          NA          NA         
# 7 " 7"  G35         NA          NA          NA         
# 8 " 8"  F32         NA          NA          NA         
# 9 " 9"  F32         F11         NA          NA         
#10  10   Z032        NA          NA          NA    

Shifting the non-NA value to left has been taken from David's answer from here. You can try any other approach to shift values from the same question as well.