Hi Michael,
Thank you so much for that valuable idea!
I will try first to clump or remove SNPs in LD and maybe the situation
would improve.
But this procedure of yours is definitely something that would come
handy in future!
Cheers,
Ana
On Wed, Nov 13, 2019 at 5:47 AM Michael Dewey wrote:
>
> D
Hello,
Try which.max?
Hope this helps,
Rui Barradas
Às 14:10 de 13/11/19, ani jaya escreveu:
Thank you very much Mr. Rui, but for delete the duplicated row I use:
...
library(tidyverse)
alldata<-data.frame(Reduce(rbind, pon1))
c<-(which(duplicated(alldata$Tanggal))) #duplicate
alldata<-allda
Thank you very much Mr. Rui, but for delete the duplicated row I use:
...
library(tidyverse)
alldata<-data.frame(Reduce(rbind, pon1))
c<-(which(duplicated(alldata$Tanggal))) #duplicate
alldata<-alldata[-c,]
attach(alldata)
because not every last row from every df is bad one.
Another problem
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Dear Ana
As others have commented this is getting a bit off-topic but here are
some hints.
It is helpful to distinguish two sorts of plot: archival plots and
impact plots. If you want to have an impact plot which gives you a
picture but possibly at the cost of completeness and accuracy then
Hello,
Maybe the following will get you close to what you want.
# remove the last row from every df
pon1 <- lapply(pon1, function(DF){
DF[[1]] <- as.Date(DF[["Tanggal"]], "%d-%m-%Y")
DF[-nrow(DF), ]
})
# order the list by year-month
inx_ym <- sapply(pon1, function(DF){
format(DF[["Tangg
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