if statement - r: when to use if else loops vs. functions -


need resolve loop issue;

example data:

data2 <- structure(list(a = c(101, 102, 103, 104, 105, 106, 107, 108,109,110),                           b = c(1,1,1,1,2,2,3,4,4,4),                          c = c(4, 4, 4, 4, 2, 2, 1, 3,3,3)),            .names = c("id", "band", "group_qty"), row.names = c(na, 10l), class = "data.frame")

example desired output:

output <- structure(list(a = c(101, 102, 103, 104, 105, 106, 107, 108, 109, 110),                            b = c(1,1,1,1,2,2,3,4,4,4),                           c = c(4,4,4,4,2,2,1,3,3,3),                           d = c(102,103,104,103,"class b","class b","class a",109,110,109)),                       .names = c("id", "band", "group_qty","newid"), row.names = c(na, 10l), class = "data.frame")

draft if else statement: note: doesn't work.

data2$newid <-    for(i in 1:length(data2$id))   {     ifelse(data2$[i,3] == 1, "class a", ifelse(data2[i,3] == 2, "class b", ifelse(data2[i,2] == data2[i+1,2], data2[i+1,1], data2[i-1,1])))   }

question:

how create working loop or function can use dplyr. rules:

  1. if group_qty = 1; output = class a

  2. if group_qty = 2; output = class b

  3. else, check see if band match band of next row.

    • if yes, output = next row's id
    • if no, output = previous row's id

  4. once reach last row of loop - not have row+1. in case: output = previous row's id.

  5. can resolved using dplyr & mutate. if yes, love have possible answer.

thanks,

we can use data.table. convert 'data.frame' 'data.table' (setdt(data2)), grouped 'band', if number of elements in group greater 1 (.n >1), use shift type='lead' succeeding 'id' each group or else keep 'id' create 'newid' column. then, based on condition, replace value in 'newid' corresponds 'group_qty' 2 'class b' , 1 'class_a' using ifelse.

library(data.table)  setdt(data2)[, newid:=if(.n>1) shift(id, type='lead',                         fill = id[.n-1]) else id , = .(band)]  data2[, newid:= ifelse(group_qty==2, 'class b',                   ifelse(group_qty==1, 'class a', newid))] data2 #     id band group_qty   newid # 1: 101    1         4     102 # 2: 102    1         4     103 # 3: 103    1         4     104 # 4: 104    1         4     103 # 5: 105    2         2 class b # 6: 106    2         2 class b # 7: 107    3         1 class # 8: 108    4         3     109 # 9: 109    4         3     110 #10: 110    4         3     109

we can use similar approach dplyr

library(dplyr) data2 %>%     group_by(band) %>%      mutate(newid = if(n()==1) id else dplyr::lead(id,                           default= id[n()-1]),             newid= ifelse(group_qty==2, 'class b',                    ifelse(group_qty==1, 'class a',                          as.character(newid)))) #     id  band group_qty   newid #   (dbl) (dbl)     (dbl)   (chr) #1    101     1         4     102 #2    102     1         4     103 #3    103     1         4     104 #4    104     1         4     103 #5    105     2         2 class b #6    106     2         2 class b #7    107     3         1 class #8    108     4         3     109 #9    109     4         3     110 #10   110     4         3     109

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