Thank you!
This is exactly what I was looking for!
Cheers!
On Wed, Feb 12, 2020 at 11:29 PM Jim Lemon wrote:
>
> Hi Stefan,
> How about this:
>
> sddf<-read.table(text="age x
> 45 1
> 45 2
> 46 1
> 47 3
> 47 3",
> header=TRUE)
> library(prettyR)
> sdtab<-xtab(age~x,sddf)
>
Hi Stefan,
How about this:
sddf<-read.table(text="age x
45 1
45 2
46 1
47 3
47 3",
header=TRUE)
library(prettyR)
sdtab<-xtab(age~x,sddf)
sdtab$counts
Jim
On Thu, Feb 13, 2020 at 7:40 AM stefan.d...@gmail.com
wrote:
>
> Dear All,
>
> I have a seemingly standard problem to which I
Thank you, this is already very helpful.
But how do I get it in the form
age var_x=1 var_x=2 var_x=3
45 1 1 0
46 1 00
So it would be a data frame with 4 variables.
Cheers!
On Wed, Feb 12, 2020 at 10:25 PM William Dunlap wrote:
>
>
You didn't say how you wanted to use it as a data.frame, but here is one way
d <- data.frame(
check.names = FALSE,
age = c(45L, 45L, 46L, 47L, 47L),
x = c(1L, 2L, 1L, 3L, 3L))
with(d, as.data.frame(table(age,x)))
which gives:
age x Freq
1 45 11
2 46 11
3 47 10
4 45
well, if I think about, its actually a simple frequency table grouped
by age. but it should be usable a matrix or data frame.
On Wed, Feb 12, 2020 at 9:48 PM wrote:
>
> So a pivot table?
>
> On 12 Feb 2020 20:39, stefan.d...@gmail.com wrote:
>
> Dear All,
>
> I have a seemingly standard problem
Dear All,
I have a seemingly standard problem to which I somehow I do not find
a simple solution. I have individual level data where x is a
categorical variable with 3 categories which I would like to aggregate
by age.
age x
45 1
45 2
46 1
47 3
47 3
and so on.
It should after
6 matches
Mail list logo
