ifelse & grepl commands when using dplyr for SQL in-db operations

Question

In dplyr running on R data frames, it is easy to run

df <- df %>% 
    mutate(income_topcoded = ifelse(income > topcode, income, topcode)

Answer 1

I had a similar problem. The best I could do was to use an in-db operation as you suggest:

topcode <- 10000
queryString <- sprintf("UPDATE db.table SET income_topcoded = %s WHERE income_topcoded > %s",topcode,topcode)
dbGetQuery(con, queryString)

In my case, I was using MySQL with dplyr, but it wasn't able to translate my ifelse() into valid SQL.

Answer 2

Based on @hadley's reply on this thread, you can use an SQL-style if() statement inside mutate() on dplyr's in-db dataframes:

df <- df %>% 
    mutate( income_topcoded = if (income > topcode) income else topcode)

As far as using grepl() goes...well, you can't. But you can use the SQL like operator:

df  <- df %>%
    filter( topcode %like% "ABC%" )