Hi Dennis, Thank you very nice :)
Best regards, Giovanni On Oct 23, 2011, at 6:55 PM, Dennis Murphy wrote: > Hi: > > Here's one approach: > > # Function to process a list component into a data frame > ff <- function(x) { > data.frame(time = x[1], partitioning_mode = x[2], workload = x[3], > runtime = as.numeric(x[4:length(x)]) ) > } > > # Apply it to each element of the list: > do.call(rbind, lapply(data, ff)) > > or equivalently, using the plyr package, > > library('plyr') > ldply(data, ff) > > # Example: > L <- list(c("1", "sharding", "query", "607", "85", "52", "79", "77", > "67", "98"), > c("1", "sharding", "refresh", "2932", "2870", "2877", "2868"), > c("1", "replication", "query", "2891", "2907", "2922", "2937")) > do.call(rbind, lapply(L, ff)) > time partitioning_mode workload runtime > 1 1 sharding query 607 > 2 1 sharding query 85 > 3 1 sharding query 52 > 4 1 sharding query 79 > 5 1 sharding query 77 > 6 1 sharding query 67 > 7 1 sharding query 98 > 8 1 sharding refresh 2932 > 9 1 sharding refresh 2870 > 10 1 sharding refresh 2877 > 11 1 sharding refresh 2868 > 12 1 replication query 2891 > 13 1 replication query 2907 > 14 1 replication query 2922 > 15 1 replication query 2937 > > HTH, > Dennis ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.