Improving performance of moving arrays into an array

I am loading a bunch of arrays and putting them into a single array. The loading of the data is negligible, but putting it into combinedArray takes significant time (as in this code).

import time import numpy as np start_time = time.time()     st,en = 0,0    combinedArray = np.empty(shape = (30000*30000))    #Get the array that each process wrote to    for i in range(10):        #load the array        #ex loading         X_np = np.empty(shape = (30000*30000)/10)        st = en        en += np.shape(X_np[:])[0]        #add to the array list        combinedArray[st:en] = X_np[:]     print("Array Calc:",time.time()-start_time)   

What I have found is often someone talking about not using append, so I tried with creating the array first, but just moving it is time consuming. Any advice on how to optimize this is appreciated.