(This article was first published on

**DiffusePrioR » R**, and kindly contributed to R-bloggers)Most R functions used in econometrics convert factor variables into a set of dummy/binary variables automatically. This is useful when estimating a linear model, saving the user from the laborious activity of manually including the dummy variables as regressors. However, what if you want to reshape your dataframe so that it contains such dummy variables?

The following function, datdum(.), is a simple workaround. The first argument is the factor variable (which can also be a character), the second is the dataframe and the third is the name you want to call these dummy variables.

datdum <- function(x, data, name){ data$rv <- rnorm(dim(data)[1],1,1) mm <- data.frame(model.matrix(lm(data$rv~-1+factor(data[,x])))) names(mm) <- paste(name,1:dim(mm)[2],sep=".") data$rv <- NULL data <- cbind(data,mm) return(data) } # simple example dat <- c("A","B","C") dat <- data.frame(dat) datdum(x="dat",data=dat,name="category") ######################### # output ######################### > dat dat 1 A 2 B 3 C > datdum(x="dat",data=dat,name="category") dat category.1 category.2 category.3 1 A 1 0 0 2 B 0 1 0 3 C 0 0 1

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