r - Is there a simple way to subset unique values and their associated datum? -

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• split data.frame based on levels of factor new data.frames 1 answer

i have large data set contains ~300,000 rows , 60 columns. if want subset unique characteristics within 1 variable use unique() function create data.frame list of unique values in variable. match master data frame associated data master file.

this process little cumbersome, wondering if there faster way same thing? example, there function use select unique fields , associated data connected values?

for example: make new data frame contains unique surveyid_block id , associated island code , abundances.

 structure(list(surveyid_block = c("62003713_2", "62003087_2",  "62003713_2", "62003713_2", "62003713_1", "62003713_2", "62003713_1",  "62003713_2", "62003713_2", "62003087_1", "62003713_1", "62003713_1",  "62003713_2", "62003713_2", "62003713_1", "62003087_1", "62003087_2",  "62003713_2", "62003713_2", "62003713_2", "62003087_2", "62003713_2",  "62003713_1", "62003713_1", "62003713_1", "62003713_1", "62003713_2",  "62003713_1", "62003713_2", "62003087_1", "62003713_2", "62003087_1",  "62003713_1", "62003087_2", "62003087_2", "62003713_2", "62003713_1",  "62003087_1", "62003713_1", "62003713_1", "62003713_1", "62003087_2",  "62003087_2", "62003713_2", "62003713_2", "62003713_2", "62003713_1",  "62003087_1", "62003713_2", "62003087_2", "62003713_1", "62003713_1",  "62003713_2", "62003713_1", "62003713_2", "62003087_2", "62003087_2",  "62003087_1", "62003087_1", "62003713_1", "62003087_1", "62003087_1",  "62003087_2", "62003087_2", "62003713_2", "62003713_1", "62003713_2",  "62003713_2", "62003713_2", "62003713_1", "62003713_2", "62003087_1",  "62003713_1", "62003713_1", "62003087_1", "62003087_1", "62003713_1",  "62003087_2", "62003087_1", "62003087_2", "62003087_2", "62003087_1",  "62003087_1", "62003087_1", "62003713_2", "62003087_2", "62003713_2",  "62003087_2", "62003713_1", "62003713_1", "62003087_2", "62003087_1",  "62003087_1", "62003087_1", "62003713_2", "62003713_2", "62003087_1",  "62003713_1", "62003087_1", "62003087_2"), islandcode = c(1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l,  1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l, 1391l ), totalabun = c(667l, 174l, 667l, 667l, 715l, 667l, 715l, 667l,  667l, 1365l, 715l, 715l, 667l, 667l, 715l, 1365l, 174l, 667l,  667l, 667l, 174l, 667l, 715l, 715l, 715l, 715l, 667l, 715l, 667l,  1365l, 667l, 1365l, 715l, 174l, 174l, 667l, 715l, 1365l, 715l,  715l, 715l, 174l, 174l, 667l, 667l, 667l, 715l, 1365l, 667l,  174l, 715l, 715l, 667l, 715l, 667l, 174l, 174l, 1365l, 1365l,  715l, 1365l, 1365l, 174l, 174l, 667l, 715l, 667l, 667l, 667l,  715l, 667l, 1365l, 715l, 715l, 1365l, 1365l, 715l, 174l, 1365l,  174l, 174l, 1365l, 1365l, 1365l, 667l, 174l, 667l, 174l, 715l,  715l, 174l, 1365l, 1365l, 1365l, 667l, 667l, 1365l, 715l, 1365l,  174l)), .names = c("surveyid_block", "islandcode", "totalabun" ), row.names = c(na, 100l), class = "data.frame") 

we can split dataset 'surveyid_block' create list of data.frames. better keep datasets in list rather creating individual data.frame objects in global environment.

lst <- split(df1, df1$surveyid_block) 

but, if need create individual datasets, can done list2env

list2env(setnames(lst, paste0('dfn', seq_along(lst))),           envir=.globalenv)