Numpy library 02_ index and sliced

import numpy as np # index listing the same # nparr1 = np.arange (0,10) # print (nparr1) # [0 1 2 3 4 5 6 7 8 9] # nparr1 [1] = 10 # nparr1 [-1 ] = 15 # print (nparr1) # print (nparr1 [-1]) # 9 # print (nparr1 [1]) # 1 # visible, with the same index listing # for i in nparr1: # print (i, end = " ") # nparr2 = np.arange (0,12) .reshape (3,4) # print (nparr2) # print (nparr2 [2] [1]) nparr3 # is equivalent to a two-dimensional array access slice # = # np.arange (0,12) # print (nparr3 [: 5]) # nparr4 = np.arange (0,12) .reshape (3,4) # print (nparr4) # # print (nparr4 [2] [1 : 4]) # multidimensional slice, a list as # print (nparr4 [1:]) # copies the array copy () # nparr5 = np.arange (0,12) # print (nparr5) # nparr6 = nparr5.copy ( ) are not co-memory address # # nparr6 [0] = 20 # print (nparr6) # nparr7 = nparr6 # total memory address, # nparr7 [0] = 30 # print (nparr7) # print (nparr6) # nparr8 = np.arange (0,12) .reshape (4,3) # print (nparr8) # nparr9 = nparr8.copy () # print (nparr9)