Data Extraction - benchmark()

Hi Berend,

I see you are one of the contributors to the rbecnhmark package. 

I am sorry that I am bothering you again.  I have tried to run your  code (slightly tweaked)  involving the benchmark function, and I am getting the following error message. What am I doing wrong?


Error in benchmark(d1 <- s1(df), d2 <- s2(df), d3 <- s3(df), d4 <- s4(df),  : 
  could not find function "s1"

identical (d1,d2), identical (d1,d3), identical (d1,d4), identical (d1,d5), identical (d1,d6)

Error: unexpected ',' in "identical (d1,d2),"

sessionInfo ()

R version 2.15.1 (2012-06-22)
Platform: i386-pc-mingw32/i386 (32-bit)

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] rbenchmark_1.0.0

loaded via a namespace (and not attached):
[1] tools_2.15.1



I would appreciate receiving your help if your time permits ..


Thanks and regards,

Pradip Muhuri

#####  Berend's code extended
N <- 100000
set.seed(13)
df<-data.frame(matrix(sample(c(1:10,NA),N, replace=TRUE),ncol=50))
s1 <- df[complete.cases(df),]
s2 <- na.omit(df)
s3 <- df[apply(df, 1, function(x)all(!is.na(x))), ]
s4 <- function(df) {df[apply(df, 1, function(x)all(!is.na(x))),][,1:ncol(df)]}
s5 <- function(df) {df[!is.na(rowSums(df)),][1:ncol(df)]}
s6 <- function(df) {df[complete.cases(df),][1:ncol(df)]}

require(rbenchmark)
 
benchmark( d1 <- s1(df), d2 <- s2(df), d3 <- s3(df), d4 <- s4(df), d5 <- s5(df), d6 <- s6(df),
                    columns=c("test","elapsed", "relative", "replications") )

identical (d1,d2), identical (d1,d3), identical (d1,d4), identical (d1,d5), identical (d1,d6)

On 22-11-2012, at 16:50, Muhuri, Pradip (SAMHSA/CBHSQ) wrote:

> Hi Berend,
>
> You have compared all 3 ways.  ... very nicely evaluated.
>

Bert's solution is indeed nice and simple. But Petr's solution is still the quickest:

>N <- 100000
> set.seed(13)
> df <- data.frame(matrix(sample(c(1:10,NA),N,replace=TRUE),ncol=50))
> library(rbenchmark)
>
> f1 <- function(df) {df[apply(df, 1, function(x)all(!is.na(x))),]}
> f2 <- function(df) {df[!is.na(rowSums(df)),]}
> f3 <- function(df) {df[complete.cases(df),]}
> f4 <- function(df) {data.frame(na.omit(df))}
> benchmark(d1 <- f1(df), d2 <- f2(df), d3 <- f3(df), d4 <- f4(df), columns=c("test","elapsed", "relative", "replications"))
          test elapsed relative replications
1 d1 <- f1(df)   3.588   14.888          100
2 d2 <- f2(df)   0.403    1.672          100
3 d3 <- f3(df)   0.241    1.000          100
4 d4 <- f4(df)   0.557    2.311          100
>
> identical(d1,d2)
[1] TRUE
> identical(d1,d3)
[1] TRUE
> identical(d1,d4)
[1] TRUE

Berend