On Jun 25, 2014, at 1:49 PM, David Winsemius wrote:
>
> On Jun 24, 2014, at 11:18 PM, Abhinaba Roy wrote:
>
>> Hi David,
>>
>> I was thinking something like this:
>>
>> ID Disease
>> 1 A
>> 2 B
>> 3 A
>> 1C
>> 2D
>> 5A
>> 4B
>> 3D
>> 2A
>> ....
>>
>>
On Jun 24, 2014, at 11:18 PM, Abhinaba Roy wrote:
> Hi David,
>
> I was thinking something like this:
>
> ID Disease
> 1 A
> 2 B
> 3 A
> 1C
> 2D
> 5A
> 4B
> 3D
> 2A
> ....
>
> How can this be done?
do.call(rbind, lapply( 1:20, function(pt) {
Also, you can do:
library(dplyr)
dat%>%group_by(ID)%>%filter(length(unique(Disease))>1)%>%arrange(Disease,ID)
A.K.
On Wednesday, June 25, 2014 3:45 AM, arun wrote:
Forgot about:
library(reshape2)
On , arun wrote:
Hi,
Check if this works:
set.seed(495)
dat <- data.frame(ID=sample
Hi,
Check if this works:
set.seed(495)
dat <- data.frame(ID=sample(1:10,20,replace=TRUE),
Disease=sample(LETTERS[1:6], 20, replace=TRUE) )
subset(melt(table(dat)[rowSums(!!table(dat))>1,]), !!value,select=1:2)
ID Disease
1 2 A
3 4 A
4 6 A
6 10 A
8 3
# build off of david's suggestion
x <-
data.frame(
patient= 1:20 ,
disease =
sapply(
pmin( 2 + rpois( 20 , 2 ) , 6 ) ,
function( n ) paste0( sample( c('A','B','C','D','E','F'),
n), collapse="+" )
)
)
# break the diseas
Hi David,
I was thinking something like this:
ID Disease
1 A
2 B
3 A
1C
2D
5A
4B
3D
2A
....
How can this be done?
On Wed, Jun 25, 2014 at 11:34 AM, David Winsemius
wrote:
>
> On Jun 24, 2014, at 10:14 PM, Abhinaba Roy wrote:
>
> > Dear R helpers,
> >
On Jun 24, 2014, at 10:14 PM, Abhinaba Roy wrote:
> Dear R helpers,
>
> I want to generate data for say 1000 patients (i.e., 1000 unique IDs)
> having suffered from various diseases in the past (say diseases
> A,B,C,D,E,F). The only condition imposed is that each patient should've
> suffered fro
Dear R helpers,
I want to generate data for say 1000 patients (i.e., 1000 unique IDs)
having suffered from various diseases in the past (say diseases
A,B,C,D,E,F). The only condition imposed is that each patient should've
suffered from *atleast* two diseases. So my data frame will have two
columns
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