Color samples in PCA plot

[NailaMez]

Hello,

I am using Rstudio for PCA on geochemical data (quanti.var = elements ) and I want to color my points by the sample they refer to.
Could anyone help me, I saw some tutorials onligne but it doesn't work.

Tkank you

[jrkrideau]

We really need a lot more information. See

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[jrkrideau]

We really need a lot more information. We need some idea of the data and the code you are using to perform the PCA. See

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

[NailaMez]

I see ... here is the script that I used

=> matrice_cor_<-cor(data[,1:10], use = "everything")
=> corrplot(matrice_cor_budget, method = "number", type = "upper")
=> res<-PCA(budget, scale.unit=TRUE, ncp=5, graph = FALSE,quali.sup = c(10:10))
10 being the sample's name column
=> fviz_eig(res, choice = "variance", addlabels = TRUE)
=> corrplot(res[["var"]][["cos2"]],is.corr = FALSE)
[score plot] => plot.PCA(res, axes=c(1, 2), choix="ind", habillage = 10,
label=c("ind", "ind.sup", "quali"),new.plot=TRUE, title="score plot")
here is the probleme , it doesn't take into account the column 10 (samples)
the error displayed ( Error in plot.PCA(res, axes = c(1, 2), choix = "ind", habillage = 1, label = c("ind", :
The variable Echantillon is not quantitative)

My dataset include 9 quantitative variables ( elements : Ca, Fe, Si, Li, Ba ... + Distance from the mineralization) the 10th column represents the sample name for each row ( 400 row by sample).

[jrkrideau]

I am sorry but that is, basically, incomprehensible.

We need clean code, just post the actual code between ```
and supply some sample data

A handy way to supply sample data is to use the dput() function. See ?dput. If you have a very large dataset then something like head(dput(myfile), 100) will likely supply enough data for us to work with.