On Oct 23, 2011, at 1:29 PM, Giovanni Azua wrote:
Hello,
This is one problem at the time :)
I have a data frame df that looks like this:
> df <-read.table(textConnection(" 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"))
>
> df$throughput <- ave(df$time, list(df$time, df$partitioning_mode),
FUN=length)
> df
time partitioning_mode workload runtime throughput
1 1 sharding query 607 11
2 1 sharding query 85 11
3 1 sharding query 52 11
4 1 sharding query 79 11
5 1 sharding query 77 11
6 1 sharding query 67 11
7 1 sharding query 98 11
8 1 sharding refresh 2932 11
9 1 sharding refresh 2870 11
10 1 sharding refresh 2877 11
11 1 sharding refresh 2868 11
12 1 replication query 2891 4
13 1 replication query 2907 4
14 1 replication query 2922 4
15 1 replication query 2937 4
and if I could use SQL ... omg! I really wish I could! I would do
exactly this:
You can of, course use package sqldf, which would undoubtedly be good
practice for me, but this seemed like a typical situation for using
'ave'. You do need to use the FUN= construction in 'ave' because that
argument appears after the triple dots in the argument list.
insert into throughput
select time, partitioning_mode, count(*)
from data.frame
group by time, partitioning_mode
My attempted R versions are wrong and produce very cryptic error
message:
throughput <- aggregate(x=df[,c("time", "partitioning_mode")],
by=list(df$time,df$partitioning_mode), count)
Error in `[.default`(df2, u_id, , drop = FALSE) :
incorrect number of dimensions
throughput <- aggregate(x=df, by=list(df$time,df
$partitioning_mode), count)
Error in `[.default`(df2, u_id, , drop = FALSE) :
incorrect number of dimensions
throughput <- tapply(X=df$time, INDEX=list(df$time,df
$partitioning), FUN=count)
I cant comprehend what comes out from this one ... :(
and I thought C++ template errors were the most cryptic ;P
Many many thanks in advance,
Best regards,
Giovanni
______________________________________________
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.
David Winsemius, MD
West Hartford, CT
______________________________________________
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.
