Convert cell to blank based on time condition

I have a dataframe that looks like this:

> dput(df)
structure(list(Person_ID = c(123L, 123L), Disease_Name = c("Heart Disease", 
"Lung Disease"), Disease_start = c("4/11/17", "4/11/17"), Procedure_start = c("4/11/18", 
"4/11/16")), class = "data.frame", row.names = c(NA, -2L))

I want to restructure the dataframe so that:

• If the Disease_start is BEFORE Procedure_start, then convert Disease_Name to a blank/NA cell
• If the Disease_start is AFTER Procedure_start, then leave Disease_Name (don’t change anything)

The output dataset should look like this:

> dput(df2)
structure(list(Person_ID = c(123L, 123L), Disease_Name = c("", 
"Lung Disease"), Disease_start = c("4/11/17", "4/11/17"), Procedure_start = c("4/11/18", 
"4/11/16")), class = "data.frame", row.names = c(NA, -2L))

Thank you!

>Solution :

Use an ifelse or case_when

library(dplyr)
df %>% 
  mutate(Disease_Name = case_when(Disease_start < Procedure_start ~"", 
      TRUE ~ Disease_Name))

-output

  Person_ID Disease_Name Disease_start Procedure_start
1       123                    4/11/17         4/11/18
2       123 Lung Disease       4/11/17         4/11/16