Python averaging with ndarrays, csvfile data
I think you're certainly on the right track (because python together with numpy is a great combination for this task), but in order to do what you want to do, you do need some basic programming skills. I'll assume you at least know a little about working in an interactive python shell and how to import modules etc. :-)
Then probably the easiest approach is to only have a single numpy array: one that contains the sum of the data in your files. After that it's just a matter of dividing by the number of files that you have.
So for example you could follow the following approach:

loop over all files in a folder with a for-loop and the os.listdir method
check if the file belongs to the data collection, for example by using something like str.endswith('.csv')
convert the filename to a full path by using os.path.join
read the data to a numpy array with numpy.loadtxt
add this data to the array containing the sums, which is initialized with np.zeros before the loop
keep a count of how many files you processed
after the loop, calculate the means by dividing the sums by the number of files processed
In a folder, I have a number of .csv files (count varies) each of which has 5 rows and 1200 columns of numerical data(float). 
Now I want to average the data in these files (i.e. R1C1 of files gives one averaged value in a resulting file, and so on for every position (R2C2 of all files gives one value in the same position of resulting file etc.).
How do I sequentially input all files in that folder into a couple of arrays; what functions in numpy can be used to just find the mean among the files (now arrays) that have been read into these arrays. Is there a better way to this? New to computing, appreciate any help.