Would appreciate help with generating a 2D histogram of frequencies, where frequencies are calculated within a column. My main issue: converting from counts to column based frequency. Here's my starting code: # expected packages library(ggplot2) library(plyr) # generate example data corresponding to expected data input x_data = sample(101:200,10000, replace = TRUE) y_data = sample(1:100,10000, replace = TRUE) my_set = data.frame(x_data,y_data) # define x and y interval cut points x_seq = seq(100,200,10) y_seq = seq(0,100,10) # label samples as belonging within x and y intervals my_set$x_interval = cut(my_set$x_data,x_seq) my_set$y_interval = cut(my_set$y_data,y_seq) # determine count for each x,y block xy_df = ddply(my_set, c("x_interval","y_interval"),"nrow") # still need to convert for use with dplyr # convert from count to frequency based on formula: freq = count/sum(count in given x interval) ################ TRYING TO FIGURE OUT ################# # plot results fig_count <- ggplot(xy_df, aes(x = x_interval, y = y_interval)) + geom_tile(aes(fill = nrow)) # count fig_freq <- ggplot(xy_df, aes(x = x_interval, y = y_interval)) + geom_tile(aes(fill = freq)) # frequency I would appreciate any help in how to calculate the frequency within a column. Thanks! jac EDIT: I think the solution will require the following steps 1) Calculate and store overall counts for each x-interval factor 2) Divide the individual bin count by its corresponding x-interval factor count to obtain frequency. Not sure how to carry this out though. .