Merging data from many files and plot them

Question

I have written application that is analyzing data and writing results in CSV file. It contains three columns: id, diff and count.
1. id is t

Answer 1

I am not familiar with the background of your question, but I hope I can understand your request.

Your command:

ggplot(data = data) + geom_point(aes(x= id, y=sqrt(diff/count)))

is doing the xyplot for the relationship of normalized difference ~ cycle. You mentioned that "in theory the greater id, the lower diff should be". So this plot is validating the assumption. Actually there is another way to do this with a number: spearman correlation coefficient, which can be computed with cor(x, y, method='spearman').

You mentioned that "plot content of my files in order to let me decide, which value of K is the best (for which in general the diff is the lowest". So probably you need to load all these files with sth like "sapply(read.csv(...), simplify=T)" to load all the data, and after that you should convert all loaded file into some format with FOUR columns include K, Id, diff and count. Then you can visualize the dataset in a three dimension with functions (levelplot) within latticeExtra package (sorry, I don't know how to do this with ggplot2), or you can use a color-coded way to do this in 2-d using geom_tile function of ggplot2, or, you can use facet to visualize the data in a grid way.