*Frequency* (an objective metric) is not the same as *pitch* (a subjective quantity). In general, pitch detection is a very tricky problem.

Assuming you just want to graph the frequency response for now, you have little choice but to use the FFT, as it is *THE* method to obtain the frequency response of time-domain data. (Well, there are other methods, such as the discrete cosine transform, but they’re just as tricky to implement, and more tricky to interpret).

If you’re struggling with the implementation of the FFT, note that it’s really just an efficient algorithm for calculating the discrete Fourier transform (DFT); see http://en.wikipedia.org/wiki/Discrete_Fourier_transform. The basic DFT algorithm is much easier (just two nested loops), but runs a *lot* slower (O(N^2) rather than O(N log N)).

If you wish to do anything more complex than simply plotting frequency content (like pitch detection, or windowing (as others have suggested)), I’m afraid you are going to have learn what the maths means.