r - for loop and applying condition to ignore limited data -

i have data.frame in format

     data.frame':   566171 obs. of  10 variables:      $ id    : factor w/ 120 levels "2200100","2200200",..: 1 1 1 1 1 1 1 1 1 1 ...      $ year  : int  1950 1950 1950 1950 1950 1950 1950 1950 1950 1950 ...      $ yday  : int  1 2 3 4 5 6 7 8 9 10 ...      $ date  : date, format: "1950-01-01" "1950-01-02" ...      $ t_max : atomic  -17.2 -23.9 -25 -22.8 -19.4 -19.4 -11.1 -15.6 -17.8 -20.6 ...      ..- attr(*, "long.name")= chr "daily maximum temperature"      ..- attr(*, "units")= chr "°c"       $ rain  : atomic  0 0 0 0 0 0 0 0 0 0 ...      ..- attr(*, "long.name")= chr "total rainfall"       ..- attr(*, "units")= chr "mm" 

i wrote following loop subset data:

    library (seas)      uniq <- unique(unlist(mdata$id))     (i in 1: length(uniq)){       data_1 <- subset(mdata, id == uniq[i])       d1 <-mksub(data_1)        year.plot(mksub(d1))     } 

it works point, however, loop stops running when station id not have sufficient data. how can tell r within loop ignore station id not have sufficient data apply year.plot function , continue other station until final id?

looks thomas laid out should doing in general. let me see if can put you. going use mscdata seas package, , assume less 2 insufficient

library(seas)  data(mscdata)  uniq <- unique(unlist(mscdata$id))   (i in 1: length(uniq)){   data_1 <- subset(mscdata, id == uniq[i])   try(if(length(data_1) < 2) {     next   } else {     d1 <-mksub(data_1)      year.plot(mksub(d1))   }) } 

this reproducible example should work you.