Finding the Maximum, Minimum, and Sum of NumPy Array

In NumPy, we can find maximum, minimum elements in a Ndarray and also sum of Ndarray by using following function.

ndarray.max():

This function of ndarray.numpy returns the maximum value of ndarray object.

Syntax:

numpy.max(input_array)

Example:

# import numpy library
import numpy as np
  
# create numpy array 
a = np.array([10,20,30,40,50])
  
# find the maximum element in the array
b = np.max(a)
print(b)

Output: 50

ndarray.min():

This function of ndarray.numpy returns the minimum value of ndarray object.

Syntax:

numpy.min(input_array)

Example:

# import numpy library
import numpy as np
  
# create numpy array 
a=np.array([10,20,30,40,50])
  
# find the minimum element in the array
b=np.min(a)
print(b)

Output: 10

numpy.sum():

This function is used to return the sum of all elements of an array over specified axis. It is possible to add rows and column elements of an array.

Syntax:

numpy.sum(array, axis=None, dtype=None, out=None, keepdims=<no value>, initial=<no value>)

Parameters:

  1. array: It is the array whose elements are used as the source for sum.
  2. axis: It describe the axis along which a sum is performed.
  3. dtype: It is used to specify the type of return array.
  4. out: It is used to specify the array to place the result.
  5. keepdims: It defines the boolean value.If the parameter is set to True, the axis which are reduced are left t in the result as dimensions with size one.
  6. initial: It specifies the starting value of sum.

Example:

import numpy as np
a=np.array([1,2,3,4,5])
b=np.sum(a)
print(b)

Output: 15