Create a Python code to estimate the Autocorrelation Function. Note: You need to implement the provided equation for ACF shown below: Hint: ACF plot must be double-sided from negative # of lags to positive # of lags with highlighted insignificant region. An example of the ACF function is shown below: Magnitu 10 0.8 0.6 0.4 02- 0.0 Ry(T): Autocomrolation Function of White noise -15 = -10 -5 Lags 10 Er+1(Yt-Y) (Yt-T Y) t 1(Yt-y) a.Plot the ACF of the make-up dataset and compare the result with the manual calculation. # of lags = 4. b.Plot the ACF of the generated data. The ACF needs to be plotted using the "stem" command. # of lags = 20. c.Write down your observations about the ACF plot of the stationary dataset.