Tukukkk

I need to create multiple 2x2 tables across many variables.

sample data:

Month <- c("Jan", "Feb", "March", "April")

Quiz1 <- c("90", "80", "100", "70")

Quiz2 <- c("100", "70", "50", "20")

Quiz3 <- c("60", "35", "26", "80")



df <- data.frame(Month, Quiz1, Quiz2, Quiz3)

What I would like to do is get a 2x2 of each of each quiz by month and then save it in a csv so that I can create bar graphs - pie charts, etc in excel and they need to be distributed with non R users. It can be the same CSV or multiple ones, that does not matter. This is how I have been doing it (there are close to 20 quizes) but I know there has got to be a more efficient way.

Quiz1 <- table(df$Month, df$Quiz1)

Quiz2 <- table(df$Month, df$Quiz2)

Quiz3 <- table(df$Month, df$Quiz3)



write.csv(Quiz1, "filepath...")

write.csv(Quiz2, "filepath...")

write.csv(Quiz3, "filepath...")

I found this answer: loop for tabulation of variables in data frame and it would work great except it is just for frequency tables and I'm not sure how to adapt it for this scenario and I don't have enough points to leave a comment.

Thank you in advance for any help!

We can use lapply to loop through the columns except the 'Month' column, then get the table of the 'Month' with the looped column. The output will be a list of tables

lst <- lapply(df[-1], function(x) table(df$Month, x))

names(lst) <- paste0("Quiz", seq_along(lst))

Instead of creating several global variables, a single list would serve the purpose. After the transformations, then use write.csv to write into different files

lapply(names(lst), function(x) write.csv(lst[[x]], file = paste0(x, ".csv"))