R: many nested loops to remove rows in multiple data frames -


i have 18 data frames called regular55, regular56, regular57, collar55, collar56, etc. in each data frame, want delete first row of each nest.

each data frame looks this:

   nest interval 1    17    -8005 2    17      183 3    17      186 4    17      221 5    17      141 6    17       30 7    17      158 8    17       23 9    17      199 10   17       51 11   17      169 12   17      176 13   31      905 14   31      478 15   31       40 16   31      488 17   31       16 18   31      203 19   31       54 20   31      341 21   31       54 22   50   -14164 23   50       98 24   50     1438 25   71      240 26   71      725 27   71      819 28   85   -13935 29   85       45 30   85      589 31   85       47 32   85      161 33   85       67

the solution came avoid writing out function each 1 of 18 data frames includes many nested loops:

for (i in 5:7){   (j in 5:7) {     (k in c("regular","collar")){       (l in c(unique(paste0(k,i,j,"$nest")))){         paste0(k,i,j)=paste0(k,i,j)[(-c(which((paste0(k,i,j,"$nest")) == l ) [1])),] }}}}

i'm selecting first value @ "which" there "unique" value of nest. however, get:

error in paste0(k, i, j)[(-c(which((paste0(k, i, j, "$nest")) == l)[1])),  :  incorrect number of dimensions

it might because "paste0(k,i,j)" considered character , not recognized name data frame.

any ideas on how fix this? or other ways delete first rows each nest in every data frame?

thanks comments, problem solved.

originally, divided data frame using loop , grouped 1 list:

for (i in 5:7) {   (j in 5:7) {     (k in c("regular","collar")){     assign(paste0(k,i,j),            df[df$x == & df$y == j & df$z == k,]) }}}  df.list=mget(ls(pattern=("[regular,collar][5-7][5-7]")))

i later found way split data frame directly list based on multiple columns (r subsetting data frame multiple data frames based on multiple column values):

df.list= split(df, with(df, interaction(df$x, df$y, df$z)), drop = true)

finally, able apply function remove first rows of each nest:

df.list.updated = lapply(df.list, function(d) d %>% group_by(nest) %>%  slice(2:n()))

it easier work list of data frames.


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