Python Program - Maximum Value of Numpy Array - numpy.max()

Numpy - Maximum Value in Array

Given a numpy array, you can find the maximum value of all elements in the array.

To get the maximum value of a NumPy Array, you can use numpy.max() function.

Syntax

The syntax of max() function is as follows:

max_value = numpy.max(arr)

Pass the numpy array as an argument to numpy.max(), and this function will return the maximum value.

Examples

1. Maximum value of numpy array

In this example, we will take a numpy array with random integers and then find the maximum of the array using numpy.max() function.

Python Program

import numpy as np

arr = np.random.randint(10, size=(4,5))
print('array\n', arr)
#find maximum value
max_value = np.max(arr)
print('Maximum value in array\n', max_value)

Explanation:

  1. The np.random.randint() generates a 4x5 matrix with random integers between 0 and 9.
  2. The numpy.max() function is used to find the largest value in the array.
  3. The print() function displays the original array and the maximum value.

Output

[[8 8 5 3 0]
 [2 0 4 5 1]
 [4 7 0 1 5]
 [5 2 1 5 8]]
Maximum value in array
 8

2. Maximum value of numpy array with float values

In this example, we will take a numpy array with random float values and then find the maximum of the array using numpy.max() function.

Python Program

import numpy as np

arr = np.random.rand(6).reshape(2,3)
print('array\n', arr)
#find maximum value
max_value = np.max(arr)
print('Maximum value in array\n', max_value)

Explanation:

  1. The np.random.rand() generates a 1D array of 6 random float values between 0 and 1, which is reshaped into a 2x3 array using reshape().
  2. The numpy.max() function identifies the maximum value in this array of float numbers.
  3. The result is printed to show the maximum value in the array.

Output

array
 [[0.45733784 0.70319461 0.65038256]
 [0.77489769 0.71777846 0.89612105]]
Maximum value in array
 0.8961210501172747

3. Maximum Value Along Specific Axis

You can also find the maximum value along a specific axis (row-wise or column-wise) in a 2D array.

Python Program

import numpy as np

arr = np.random.randint(10, size=(3,4))
print('array\n', arr)
# find maximum value along each column
max_value_col = np.max(arr, axis=0)
# find maximum value along each row
max_value_row = np.max(arr, axis=1)
print('Maximum value in each column\n', max_value_col)
print('Maximum value in each row\n', max_value_row)

Explanation:

  1. The array is created using np.random.randint() to generate random integers between 0 and 9 in a 3x4 matrix.
  2. np.max(arr, axis=0) calculates the maximum value along each column (vertically).
  3. np.max(arr, axis=1) calculates the maximum value along each row (horizontally).
  4. The results are printed for both row and column-wise maximum values.

Output

array
 [[8 3 1 7]
 [0 6 4 8]
 [5 2 6 9]]
Maximum value in each column
 [8 6 6 9]
Maximum value in each row
 [8 8 9]

Summary

In this Numpy Tutorial, we learned how to find the maximum value in a Numpy Array using the numpy.max() function, with detailed examples covering integer and float arrays, as well as finding maximum values along specific axes.

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