Hi all,
I want to calculate the number of unique observations of y in each level
of x from my data frame df.
this does the job but it is very slow for this big data frame (159503 rows,
11 columns).
group.list - split(df$y,df$x)
count - function(x) length(unique(na.omit(x)))
Maybe:
with(df, tapply(y, x, count))
On Fri, Jan 16, 2009 at 8:10 AM, Simon Pickett simon.pick...@bto.orgwrote:
Hi all,
I want to calculate the number of unique observations of y in each level
of x from my data frame df.
this does the job but it is very slow for this big data frame
df = data.frame(x = sample(7:9, 100, rep = T), y = sample(1:5, 100, rep
= T))
fun = function(x){length(unique(x))}
by(df$x, df$y, fun)
Simon Pickett wrote:
Hi all,
I want to calculate the number of unique observations of y in each
level of x from my data frame df.
this does the job but it
-
Fra: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] På
vegne af Simon Pickett
Sendt: 16. januar 2009 11:10
Til: R help
Emne: [R] faster version of split()?
Hi all,
I want to calculate the number of unique observations of y in each level of
x from my data frame df.
this does
Henrique's solution seems sensible. Another might be:
df = data.frame(x = sample(7:9, 10, rep = T), y = sample(1:5, 10,
rep = T))
table(df)
y
x 1 2 3 4 5
7 1 0 1 0 2
8 0 1 0 0 1
9 0 1 1 2 0
rowSums(table(df) 0)
7 8 9
3 2 3
#-same as Henrique's
count -
Simon Pickett wrote:
Hi all,
I want to calculate the number of unique observations of y in each
level of x from my data frame df.
this does the job but it is very slow for this big data frame (159503
rows, 11 columns).
group.list - split(df$y,df$x)
count - function(x)
6 matches
Mail list logo
