Reverse 1 dimensional numpy  arrays  using reverse slicing [ : :-1]

Reverse N dimensional numpy arrays row wise using “fliplr” method    

Reverse N dimensional numpy array column wise using “flipud”  method

# Imports
import numpy as np

# Let's create numpy arrays
nparray = np.array([1, 2, 3, 4])
nparraynd = np.array([[1, 2, 4],[0, 3, 5],[8, 9, 7]])

# Reverse 1 dim array
reversedarray = nparray[::-1]

print("Original array: \n{}\n".format(nparray))
print("Reversed 1 dim array: \n{}\n".format(reversedarray))
Original array: 
[1 2 3 4]

Reversed 1 dim array: 
[4 3 2 1]

# Reverse N dim array row wise
rowrevndarray = np.fliplr(nparraynd)

print("Original array: \n{}\n".format(nparraynd))
print("N dim array row reversed: \n{}\n".format(rowrevndarray))
Original array: 
[[1 2 4]
 [0 3 5]
 [8 9 7]]

N dim array row reversed: 
[[4 2 1]
 [5 3 0]
 [7 9 8]]

# Reverse N dim array column wise
colrevndarray = np.flipud(nparraynd)

print("Original array: \n{}\n".format(nparraynd))
print("N dim array column reversed: \n{}\n".format(colrevndarray))
Original array: 
[[1 2 4]
 [0 3 5]
 [8 9 7]]

N dim array column reversed: 
[[8 9 7]
 [0 3 5]
 [1 2 4]]

# Reverse N dim array element wise
elerevndarray = np.fliplr(nparraynd)[::-1]

print("Original array: \n{}\n".format(nparraynd))
print("N dim array element wise reversed: \n{}\n".format(elerevndarray))
Original array: 
[[1 2 4]
 [0 3 5]
 [8 9 7]]

N dim array element wise reversed: 
[[7 9 8]
 [5 3 0]
 [4 2 1]]