Change the dimension of a NumPy array
Let's discuss how to change the dimensions of an array. In NumPy, this can be achieved in many ways. Let's discuss each of them.
Method #1: Using Shape()
Syntax :
array_name.shape()
# importing numpy
import numpy as np
def main():
# initialising array
print('Initialised array')
gfg = np.array([1, 2, 3, 4])
print(gfg)
# checking current shape
print('current shape of the array')
print(gfg.shape)
# modifying array according to new dimensions
print('changing shape to 2,2')
gfg.shape = (2, 2)
print(gfg)
if __name__ == "__main__":
main()
Output:
Initialised array [1 2 3 4] current shape of the array (4,) changing shape to 2,2 [[1 2] [3 4]]
Method #2: Using reshape()
The order parameter of reshape() function is advanced and optional. The output differs when we use C and F because of the difference in the way in which NumPy changes the index of the resulting array. Order A makes NumPy choose the best possible order from C or F according to available size in a memory block.
Syntax :
numpy.reshape(array_name, newshape, order= 'C' or 'F' or 'A')
# importing numpy
import numpy as np
def main():
# initialising array
gfg = np.arange(1, 10)
print('initialised array')
print(gfg)
# reshaping array into a 3x3 with order C
print('3x3 order C array')
print(np.reshape(gfg, (3, 3), order='C'))
# reshaping array into a 3x3 with order F
print('3x3 order F array')
print(np.reshape(gfg, (3, 3), order='F'))
# reshaping array into a 3x3 with order A
print('3x3 order A array')
print(np.reshape(gfg, (3, 3), order='A'))
if __name__ == "__main__":
main()
Output :
initialised array [1 2 3 4 5 6 7 8 9] 3x3 order C array [[1 2 3] [4 5 6] [7 8 9]] 3x3 order F array [[1 4 7] [2 5 8] [3 6 9]] 3x3 order A array [[1 2 3] [4 5 6] [7 8 9]]
Method #3 : Using resize()
The shape of the array can also be changed using the resize() method. If the specified dimension is larger than the actual array, The extra spaces in the new array will be filled with repeated copies of the original array.
Syntax :
numpy.resize(a, new_shape)
# importing numpy
import numpy as np
def main():
# initialise array
gfg = np.arange(1, 10)
print('initialised array')
print(gfg)
# resized array with dimensions in
# range of original array
gfg1=np.resize(gfg, (3, 3))
print('3x3 array')
print(gfg1)
# resized array with dimensions larger than
# original array
gfg2=np.resize(gfg, (4, 4))
# extra spaces will be filled with repeated
# copies of original array
print('4x4 array')
print(gfg2)
# resize array with dimensions larger than
# original array
gfg.resize(5, 5)
# extra spaces will be filled with zeros
print('5x5 array')
print(gfg)
if __name__ == "__main__":
main()
Output :
initialised array [1 2 3 4 5 6 7 8 9] 3x3 array [[1 2 3] [4 5 6] [7 8 9]] 4x4 array [[1 2 3 4] [5 6 7 8] [9 1 2 3] [4 5 6 7]] 5x5 array [[1 2 3 4 5] [6 7 8 9 0] [0 0 0 0 0] [0 0 0 0 0] [0 0 0 0 0]]
