Prefix Sum Array in Python using Accumulate Function Last Updated : 17 Jan, 2025 Summarize Comments Improve Suggest changes Share Like Article Like Report A prefix sum array is an array where each element is the cumulative sum of all the previous elements up to that point in the original array. For example, given an array [1, 2, 3, 4], its prefix sum array would be [1, 3, 6, 10]. Let us explore various methods to achieve this.Using accumulate from itertoolsThis method utilizes the accumulate() function from the itertools module, which is specifically designed to calculate cumulative results like prefix sums. Python # Import accumulate from itertools from itertools import accumulate # Input array a = [1, 2, 3, 4] # Calculate prefix sum array prefix_sum = list(accumulate(a)) print(prefix_sum) Output[1, 3, 6, 10] Explanation:accumulate() function computes the cumulative sum of elements in the array.We convert the result into a list to display the prefix sum array.Let's explore some more methods and see how we can calculate prefix sum array in Python using accumulate function.Table of ContentUsing list comprehensionUsing numpyUsing for loopUsing reduce from functoolsUsing list comprehensionThis method uses list comprehension along with a running total to create the prefix sum array in a concise manner. Python # Input array a = [1, 2, 3, 4] # Initialize a running total total = 0 # Calculate prefix sum using list comprehension prefix_sum = [total := total + num for num in a] print(prefix_sum) Output[1, 3, 6, 10] Explanation:We use the walrus operator (:=) to update the total while iterating over the array.The prefix sum is constructed as a list directly.This approach combines the functionality of a loop and inline calculation into a single line.Using numpyFor numerical data, numpy provides an efficient way to compute prefix sums using its cumsum function for calculating prefix sums. Python # Import numpy import numpy as np # Input array a = [1, 2, 3, 4] # Calculate prefix sum using numpy prefix_sum = np.cumsum(a) print(prefix_sum.tolist()) Output[1, 3, 6, 10] Explanation:cumsum function from numpy computes the cumulative sum efficiently.The resulting array is converted to a list for easier readability.Using for loopA simple approach is to use a for loop to calculate the prefix sum by iterating through the array and maintaining a running total. Python # Input array a = [1, 2, 3, 4] # Initialize an empty prefix sum array and a running total p_sum = [] total = 0 # Calculate prefix sum using a loop for num in a: total += num p_sum.append(total) print(p_sum) Output[1, 3, 6, 10] Explanation:We maintain a running total using a variable, which is updated with each element of the array.Each element is added to total, and the result is appended to the prefix sum array.Using reduce from functoolsThis method uses the reduce() function to calculate the prefix sum array step by step. Python # Import reduce from functools from functools import reduce # Input array a = [1, 2, 3, 4] # Calculate prefix sum using reduce p_sum = [reduce(lambda x, y: x + y, a[:i+1]) for i in range(len(a))] print(p_sum) Output[1, 3, 6, 10] Explanation:reduce() function is used to calculate the cumulative sum for each slice of the array.Although functional, this method is less efficient than the others due to repeated slicing. 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