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Oh so i should calculate it county wise. Before I was sorting both the list from lowest to greatest irrespective of the counties and then doing the calculations.
Thank You for your answer but why would you remove the data from the real distribution. I understand that the scipy method would only work with equal datasets but which elements of the data to remove or why? Here i see you removed the last ones. Also isn't there anyway to make it work on unequal datasets?
@edmund Hello, the problem is simple. I have a real data set and simulated data sets which I am obtaining from a simulation. My goal is to find which of the simulated data set is the closest to the real data?
@edmund ok can you guide me through that ? Like how would you encounter that? And yes it is very computationally expensive to do this. But I am still not sure what distribution we would be fitting here!
@Edmund I think you are correct, those values are the variable observation and I am plotting the values on y-axis over some standard x-axis. x_points=np.asarray(list(range(0,len(data_a)))) >>> x_points=x_points/len(data_a) >>> plt.plot(x_points,data_a) >>> x_points=np.asarray(list(range(0,len(data_b)))) >>> x_points=np.asarray(list(range(0,len(data_c)))) >>> x_points=x_points/len(data_c) >>> plt.plot(x_points,data_c) This is the code. But my question is how one can find the closeness between the two datasets
