I have a data frame
df<-data.frame(Name=c('H001', 'H002', 'H003', 'H004', 'H005', 'H006',
'H007', 'H008', 'H009', 'H010'),
Var1=c(1:10),
Var2=c(4,6,7,2,3,8,9,3,2,10),
Var3=c(1,0.7,0.5,0.74,0.84,0.8,0.13,0.7,0.34,0.4))
I want to reduce the original value in column Var3 if it is above a given threshold, but keep the original value if it is below said threshold. I have tried this, but this induces NAs:
df %>%
mutate(Var3 = case_when(
Name %in% c("H001", "H002") & Var3 >0.32 ~ 0.32,
Name %in% c("H003", "H004") & Var3 >0.22 ~ 0.32,
Name %in% c("H005", "H006") & Var3 >0.15 ~ 0.15,
Name %in% c("H007", "H008") & Var3 >0.18 ~ 0.18,
Name %in% c("H009", "H010") & Var3 >0.42 ~ 0.32,
))
Is there a way to retain the original value instead of NA? Thanks in advance
CodePudding user response:
You can add a final else
statement at the end of your case_when
, so that if none of the other conditions are met, then it will just return Var3
for a given row. By default, it will return NA
if none of the other conditions are met.
df %>%
mutate(Var3 = case_when(
Name %in% c("H001", "H002") & Var3 >0.32 ~ 0.32,
Name %in% c("H003", "H004") & Var3 >0.22 ~ 0.32,
Name %in% c("H005", "H006") & Var3 >0.15 ~ 0.15,
Name %in% c("H007", "H008") & Var3 >0.18 ~ 0.18,
Name %in% c("H009", "H010") & Var3 >0.42 ~ 0.32,
TRUE ~ Var3
))
Output
Name Var1 Var2 Var3
1 H001 1 4 0.32
2 H002 2 6 0.32
3 H003 3 7 0.32
4 H004 4 2 0.32
5 H005 5 3 0.15
6 H006 6 8 0.15
7 H007 7 9 0.13
8 H008 8 3 0.18
9 H009 9 2 0.34
10 H010 10 10 0.40