Here you go. I acknowledge you specified a loop in your question, but in R I avoid loops wherever possible. This is better. This uses plyr::join_all to join all your data frames by Item and LC, then dplyr::mutate to do the calculations. Note you can put multiple mutations in one mutate() function: library(plyr) library(dplyr) library(tidyr) … Read more
Just use the internal bits from janitor::clean_names(): # #’ ‘Clean’ a character/factor vector like `janitor::clean_names()` does for data frame columns # #’ # #’ Most of the internals are from `janitor::clean_names()` # #’ # #’ @param x a vector of strings or factors # #’ @param refactor if `x` is a factor, return a ref-factored … Read more
One way could be using unique with a for-loop Breed = c( “Sheetland Sheepdog Mix”, “Pit Bull Mix”, “Lhasa Aposo/Miniature”, “Cairn Terrier/Chihuahua Mix”, “American Pitbull”, “Cairn Terrier”, “Pit Bull Mix” ) df=data.frame(Breed) for (i in unique(df$breed)){ df[,paste0(i)]=ifelse(df$Breed==i,1,0) } solved Convert categorical column to multiple binary columns [duplicate]