I have been given a list of data points (time vs amplitude) which I used to plot a noisy sine curve using matplotlib.
I now have to estimate the frequency of the noisy wave and I think that I am supposed to do this by using a Fourier transform from numpy's functions (np.fft).
I don't know what I am supposed to do to perform the Fourier transform and once I have done it, how I determine which frequency is dominant.
I don't know what I am supposed to do to perform the Fourier transform
...but you do. You said it yourself - use numpy's fft function, or more exactly one of the functions in numpy's fft library (e.g. numpy.fft.fft). That's the easy part.
The hard part is indeed what to do when you get the frequencies. That's not a trivial question. One place to start from is to take the lowest peak in the frequency power spectrum (i.e. square of abs of fft), what's called the fundamental frequency.
Also, this question might fit better in Signal Processing.
[Edited:] this question was marked as a duplicate of Understanding FFT output. There's a lot to read there, but I would direct you to this note at the end of the accepted answer:
Note: You may also want to read up what autocorrelation is, and how it is used to find the fundamental frequency of a signal. I have a feeling that this is what you really want.
