Hi, I have a dataset in which there are in all 250 variables and for each variable the data is entered over the months. I need to calculate the percentage of missing values for each variable over each month and then plot a graph for that. I am running the following code for doing the same
*ds <- read.csv(file="filepath", header=TRUE) attach(ds) may <- length(variable1[variable1==""]) / length(dos[dos=="May-06"]) * 100 jun <- length(variable1[variable1==""]) / length(dos[dos=="June-06"]) * 100 . . . var1 <- c(may, jun, ...........) x <- seq(as.Date("2006-01-01"), as.Date("2007-03-31"), by="months") plot(var1~x)* So likewise I am calculating the percentage of missing values for each variable for each month using different variables and storing the values in those variables and then combining those variables in one object for plotting the graph. I need to know, whether can I combine all the variables from that dataset in one object and calculate the missing values percentage over months together, instead of creating different variables for each month and then combining them. Also, after doing that, I need to plot the graph for each variable and combine it in a single pdf file. I highly appreciate all your help. Thanks, Shreyasee [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.