# Tricks I learned today #1: as.integer() on factor levels

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I normally work with full numerical data, not categorical data. R, when using **chem-bla-ics**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

*read.csv()*seems to recognize such categories and marks the column as to have factor levels. This is useful indeed. However, I wanted to make a PCA biplot on this data, so was looking for ways to convert this to class numbers. After some googling we, Anna and me, ran into

*as.integer()*which can be used on the factor levels. So, today I learned this trick:

> a = as.factor(c(“A”, “B”, “A”, “C”))

> b = as.integer(factor(a))

Well, probably basic to many, it was new to me 🙂

Now, wondering if it is equally easy to convert it into a multi-column matrix where each column indicates class membership (thus, resulting in three columns for the above…). That’s another trick I need to learn…

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