Python – Mean of Consecutive Sublist

When working with lists in Python, calculating the mean of consecutive sublists is a common task in data analysis. This involves dividing a list into fixed-size chunks and computing the average of each chunk. Python offers several approaches to accomplish this efficiently.

What is Mean of Consecutive Sublists?

Given a list and a sublist size, we divide the original list into consecutive sublists of that size and calculate the mean (average) of each sublist. For example, if we have [1, 2, 3, 4, 5, 6] and sublist size is 3, we get sublists [1, 2, 3] and [4, 5, 6] with means 2.0 and 5.0 respectively.

Method 1: Using List Comprehension

List comprehension provides a concise way to create lists and calculate means in a single line ?

# Initialize the list and sublist size
input_list = [1, 2, 3, 4, 5, 6, 7, 8, 9]
sublist_size = 3

# Calculate means using list comprehension
result_list = [sum(input_list[i:i+sublist_size]) / sublist_size 
               for i in range(0, len(input_list), sublist_size)]

print("Original list:", input_list)
print("Sublist size:", sublist_size)
print("Means of consecutive sublists:", result_list)

Original list: [1, 2, 3, 4, 5, 6, 7, 8, 9]
Sublist size: 3
Means of consecutive sublists: [2.0, 5.0, 8.0]

How It Works

The list comprehension iterates through the list with steps equal to the sublist size. For each position i, it extracts a slice input_list[i:i+sublist_size], calculates the sum, and divides by the sublist size to get the mean.

Method 2: Using NumPy

NumPy provides efficient numerical operations and can handle array operations more efficiently for large datasets ?

import numpy as np

# Initialize the list and sublist size
input_list = [1, 2, 3, 4, 5, 6, 7, 8, 9]
sublist_size = 3

# Calculate means using NumPy
result_array = [np.mean(input_list[i:i+sublist_size]) 
                for i in range(0, len(input_list), sublist_size)]

print("Original list:", input_list)
print("Sublist size:", sublist_size)
print("Means using NumPy:", result_array)

Original list: [1, 2, 3, 4, 5, 6, 7, 8, 9]
Sublist size: 3
Means using NumPy: [2.0, 5.0, 8.0]

Method 3: Using a Simple Loop

A traditional loop approach provides more control and is easier to understand for beginners ?

# Initialize the list and sublist size
input_list = [1, 2, 3, 4, 5, 6, 7, 8, 9]
sublist_size = 3
result_list = []

# Calculate means using a loop
for i in range(0, len(input_list), sublist_size):
    sublist = input_list[i:i+sublist_size]
    mean_value = sum(sublist) / len(sublist)
    result_list.append(mean_value)

print("Original list:", input_list)
print("Sublist size:", sublist_size) 
print("Means using loop:", result_list)

Original list: [1, 2, 3, 4, 5, 6, 7, 8, 9]
Sublist size: 3
Means using loop: [2.0, 5.0, 8.0]

Comparison

Conclusion

All three methods effectively calculate the mean of consecutive sublists. Use list comprehension for concise code, NumPy for numerical performance, or simple loops for clarity and learning purposes.