Autocorrelation - Understanding reduced correlation at periodic time shifts using np.correlate (versus statistical autocorrelation)?
The difference here is that statistical autocorrelation assumes a stationary power signal (so basically an infinite periodic signal) and does a normalisation to $[-1,1]$ and that autocorrelation just takes the finite signal as it is and does the classical convolution of the signal with itself, leading to just one point of perfect overlap and decreasing amplitudes before and after.