NumPy: Count number of occurrences of each value in a given array of non-negative integers

Last update on March 25 2025 12:19:50 (UTC/GMT +8 hours)

13. Count Occurrences Using bincount

Write a Python program to count number of occurrences of each value in a given array of non-negative integers.

Note: bincount() function count number of occurrences of each value in an array of non-negative integers in the range of the array between the minimum and maximum values including the values that did not occur.

Sample Solution:

Python Code:

# Importing the NumPy library
import numpy as np

# Creating a Python list
array1 = [0, 1, 6, 1, 4, 1, 2, 2, 7] 

# Displaying the original array
print("Original array:")
print(array1)

# Calculating the number of occurrences of each value in the array
print("Number of occurrences of each value in array: ")
print(np.bincount(array1)) 

Sample Output:

Original array:
[0, 1, 6, 1, 4, 1, 2, 2, 7]
Number of occurrences of each value in array: 
[1 3 2 0 1 0 1 1]

Explanation:

In the above exercise –

array1 = [0, 1, 6, 1, 4, 1, 2, 2, 7]: Creates a 1-dimensional Python list array1 containing integer values.

print(np.bincount(array1)): Computes the frequency of occurrences of each integer value in array1. The output of np.bincount() is an array of length k+1, where k is the maximum value in the input array. Each element i in the output array indicates the number of times that i appears in the input array.

For more Practice: Solve these Related Problems:

• Write a function that returns the count of each non-negative integer in an array using np.bincount.
• Create a program that compares the output of np.bincount with a dictionary-based counting method for verification.
• Implement a solution that handles arrays with missing integer values and returns a complete count for the range from minimum to maximum.
• Develop a method that benchmarks np.bincount performance on large arrays and reports the execution time.

Python-Numpy Code Editor:

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