In fact you have an ftable, not a multi-way table, but as.data.frame works
for multi-way tables, and here as.data.frame(as.table(ftabc)) works:
as.data.frame(as.table(ftabc))
A B CC Freq
1 1 1 1 20
2 2 1 1 38
3 3 1 1 20
4 1 2 1 22
5 2 2 1 25
6 3 2 1 23
...
It would
Actually I had just meant that because I had some factors I had a
conceptual table. Using ftable() was just my way of getting the factors
into data frame form. But thank you for showing me that as.data.frame()
does exactly what I want.
Murray Jorgensen
Prof Brian Ripley wrote:
In fact you
Suppose that one has several factors, all of the same length. These
define a multi-way contingency table. Now suppose one wants to fit a
Poisson GLM a.k.a. log-linear model to the frequencies in this table.
How may we make the table into a data frame suitable for glm() ?
I have an answer to my
Hi
I have a set of fish lengths (cm) which I'd like to
have divided into bins as specified by myself. I want
to classify my bins as:
0=x0.5
0.5=x1
1=x1.5
1.5=x2
and so on...
I'd like the frequencies to be given as a vector
because I need to use these values for further
analysis.
Please can
See ?hist
For example
hist(rnorm(100),plot=F,breaks=-3:3)$counts
Regards
Wayne
-Original Message-
From: Silvia Kirkman [mailto:[EMAIL PROTECTED]
Sent: 21 June 2004 14:01
To: [EMAIL PROTECTED]
Subject: [R] frequencies
Hi
I have a set of fish lengths (cm) which I'd like to
have
--
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Silvia Kirkman
Sent: Monday, June 21, 2004 4:01 PM
To: [EMAIL PROTECTED]
Subject: [R] frequencies
Hi
I have a set of fish lengths (cm) which I'd like to
have divided
On 21 Jun 2004 at 6:01, Silvia Kirkman wrote:
Hi
I have a set of fish lengths (cm) which I'd like to
have divided into bins as specified by myself. I want
to classify my bins as:
0=x0.5
0.5=x1
1=x1.5
1.5=x2
and so on...
Hallo
?cut and ?table should be what you are looking for
See the example in help(cut). You will require the option right=FALSE
in cut() or you can try hist.
x - abs(rnorm(100))
table( cut(x, seq(0, max(ceiling(x)), by=0.5), right=FALSE ))
hist(x, breaks=seq(0, max(ceiling(x)), by=0.5), plot=FALSE)
On Mon, 2004-06-21 at 14:01, Silvia Kirkman wrote:
