you can do find.clusters with the data frame object (without converting to gen..ind)

basically, it will call kmeans from the stats package.

check if that works first.

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this is from the adegenet manual (pdf)

http://adegenet.r-forge.r-project.org/

## S3 method for class 'data.frame'

find.clusters(x, clust=NULL, n.pca=NULL,

n.clust=NULL, stat=c("BIC","AIC", "WSS"),

choose.n.clust=TRUE,criterion=c("diffNgroup",

"min","goesup", "smoothNgoesup", "goodfit"),

max.n.clust=round(nrow(x)/10), n.iter=1e5, n.start=10,

center=TRUE, scale=TRUE, pca.select=c("nbEig","percVar"),

perc.pca=NULL, ..., dudi=NULL)

## S3 method for class 'matrix'

find.clusters(x, ...)

## S3 method for class 'genind'

find.clusters(x, clust=NULL, n.pca=NULL, n.clust=NULL,

stat=c("BIC","AIC", "WSS"), choose.n.clust=TRUE,

criterion=c("diffNgroup", "min","goesup", "smoothNgoesup",

"goodfit"), max.n.clust=round(nrow(x@tab)/10), n.iter=1e5,

n.start=10, scale=FALSE, truenames=TRUE, ...)

Thank you Vikas!

@Adelina Larsen while u type the df2 genind command, the population column in your original dataframe should not be mentioned. You can subset the dataframe using square brackets. After it gets converted to genind, you can add population to the object using@ operator