def data_processing(data, n):
    catgories = data[0].shape[0]
    samples = data[0].shape[1]
    final = np.zeros((catgories, samples))
    for c in range(catgories):
        for s in range(samples):
            final[c][s] = outlier_filter([data[i][c][s] for i in range(n)]).mean()
    return final
def data_processing(data, n):
    catgories = data[0].shape[0]
    samples = data[0].shape[1]
    final = np.zeros((catgories, samples))
    for c in range(catgories):
        for s in range(samples):
            final[c][s] = outlier_filter([data[i][c][s] for i in range(n)]).mean()
    return final