subset a dataframe on multiple conditions in R

Question

My dataset has several variables and I want to build a subset as well as create new variables based on those conditions

dat1 S1 S2 H1 H2 Month1 Year1 Month2 Year2 16 17 81 70 09 2017 07 2017 17 16 80 70 08 2017 08 2016 14 16 81 81 09 2016 05 2016 18 15 70 81 07 2016 09 2017 17 16 80 80 08 2016 05 2016 18 18 81 70 05 2017 04 2016

I want to subset such that if S1=16,17,18 and H1=81,80 then I create a new variable Hist=H1 , date=paste(Month1,Year1) Sip = S1 Same goes for set of S2, H2 . My output should be: [ The first 4 rows comes for sets of S1,H1, Month1,Year2 and last 2 rows comes from S2,H2,Month2,Year2

Hist Sip Date 81 16 09-2017 80 17 08-2017 80 17 08-2016 81 18 05-2017 81 16 05-2016 80 16 05-2016

My Code :

datnew <- dat1 %>% mutate(Date=ifelse((S1==16|S1==17|S1=18)&(H1==80|H1==81),paste(01,Month1,Year1,sep="-"), ifelse((S2==16|S2==17|S2==18)&(H2==80|H2==81),paste(Month2,Year2,sep="-"),"NA")), hist=ifelse((S1==16|S1==17|S1=18)&(H1==80|H1==81),H1, ifelse((S2==16|S2==17|S2==18)&(H2==80|H2==81),H2,"NA")), sip=ifelse((S1==16|S1==17|S1=18)&(H1==80|H1==81),S1, ifelse((S2==16|S2==17|S2==18)&(H2==80|H2==81),S2,"NA")))

In the original data I have 10 sets of such columns ie S1-S10, H1-H10, Month1_-Month10... And for each variable I have lot more conditions of numbers. In this method it is going on and on. Is there any better way to do this?

Thanks in advance

What exactly did your mutate() attempts look like. It's often easier to help you by fixing what you started rather than starting from scratch. — MrFlick
– MrFlick, Commented Nov 4, 2020 at 5:25

Paul · Accepted Answer · 2020-11-04 07:13:32Z

Here is a tidyverse solution. Separate into two data frames and bind the rows together.

library(tidyverse) bind_rows( dat1 %>% select(patientId, ends_with("1")) %>% rename_all(str_remove, "1"), dat1 %>% select(patientId, ends_with("2")) %>% rename_all(str_remove, "2") ) %>% transmute( patientId, Hist = H, Sip = S, date = paste0(Month, "-", Year) ) %>% filter( Sip %in% 16:18, Hist %in% 80:81 ) #> # A tibble: 6 x 4 #> patientId Hist Sip date #> <int> <dbl> <dbl> <chr> #> 1 1 81 16 09-2017 #> 2 2 80 17 08-2017 #> 3 5 80 17 08-2016 #> 4 6 81 18 05-2017 #> 5 3 81 16 05-2016 #> 6 5 80 16 05-2016

Yes - adding patientId to the selects and transmute. I've updated my answer to include this.

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