rakesh kumar

Posted on

# Explain numpy operation and universal function in django

``````import numpy as np

array1 = np.array([1, 2, 3])
array2 = np.array([4, 5, 6])
result = array1 + array2
print(result)
``````

Output:

``````[5 7 9]
``````

Subtraction of Two NumPy Arrays:

``````array1 = np.array([1, 2, 3])
array2 = np.array([4, 5, 6])
result = array2 - array1
print(result)
``````

Output:

``````[3 3 3]
``````

Element-wise Multiplication of Two NumPy Arrays:

``````array1 = np.array([1, 2, 3])
array2 = np.array([4, 5, 6])
result = array1 * array2
print(result)
``````

Output:

``````[ 4 10 18]
``````

Element-wise Division of Two NumPy Arrays:

``````array1 = np.array([10, 20, 30])
array2 = np.array([2, 5, 3])
result = array1 / array2
print(result)
``````

Output:

``````[ 5.  4. 10.]
``````

Matrix Multiplication of Two NumPy Arrays:

``````array1 = np.array([[1, 2], [3, 4]])
array2 = np.array([[5, 6], [7, 8]])
result = np.dot(array1, array2)
print(result)
``````

Output:

``````[[19 22]
[43 50]]
``````

Transpose of a NumPy Array:

``````
array = np.array([[1, 2, 3], [4, 5, 6]])
transposed_array = array.T
print(transposed_array)
``````

Output:

``````[[1 4]
[2 5]
[3 6]]
``````

Sum of All Elements in a NumPy Array:

``````array = np.array([1, 2, 3, 4, 5])
result = np.sum(array)
print(result)
``````

Output:

Maximum Value in a NumPy Array:

``````array = np.array([10, 5, 8, 12, 3])
result = np.max(array)
print(result)
``````

Output:

``````12
``````

Saving NumPy Array as a CSV File:

``````array = np.array([1, 2, 3, 4, 5])
np.savetxt('output.csv', array, delimiter=',')
``````