NumPy: Count the frequency of unique values in numpy array

Last update on April 26 2025 12:38:41 (UTC/GMT +8 hours)

Frequency of Distinct Values in Array

Write a NumPy program to count the frequency of distinct values in a NumPy array.

Pictorial Presentation:

Sample Solution:

Python Code:

# Importing the NumPy library and aliasing it as 'np'
import numpy as np

# Creating a NumPy array 'a' containing integers
a = np.array([10, 10, 20, 10, 20, 20, 20, 30, 30, 50, 40, 40])

# Printing a message indicating the original array will be displayed
print("Original array:")

# Printing the original array 'a' with its elements
print(a)

# Finding unique elements and their counts in the array 'a' using np.unique() with return_counts=True
unique_elements, counts_elements = np.unique(a, return_counts=True)

# Printing a message indicating the frequency of unique values in the array
print("Frequency of unique values of the said array:")

# Creating a NumPy array from the unique elements and their respective counts
# Converting the resulting arrays into a 2D NumPy array using np.asarray()
result = np.asarray((unique_elements, counts_elements))

# Printing the array containing unique elements and their frequencies
print(result) 

Sample Output:

Original array:                                                        
[10 10 20 10 20 20 20 30 30 50 40 40]                                  
Frequency of unique values of the said array:                          
[[10 20 30 40 50]                                                      
 [ 3  4  2  2  1]]

Explanation:

In the above code –

• a = np.array(...): Create a NumPy array 'a' containing the given integer values.
• np.unique(a, return_counts=True): Find the unique elements in the array 'a' and their counts using the np.unique function. The return_counts parameter is set to True, so the function returns two arrays: one containing the unique elements and another containing the corresponding counts of those unique elements.
• unique_elements, counts_elements = ...: Assign the returned unique elements and their counts to the variables unique_elements and counts_elements, respectively.
• np.asarray((unique_elements, counts_elements)): Combine the unique elements and their counts into a single 2D NumPy array.
• print(...): Print the resulting 2D NumPy array.

For more Practice: Solve these Related Problems:

• Write a NumPy program to count the frequency of unique elements in an array using np.unique with return_counts.
• Create a function that returns both the unique values and their corresponding frequencies from a given array.
• Test the frequency count on an array with repeated elements and verify the ordering of the output.
• Compare the results of np.bincount on an integer array with the output from np.unique to validate consistency.

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