Python Program to print a specific number of rows with Maximum Sum

When working with a list of lists, you often need to find the rows with the highest sum values. Python provides an elegant solution using the sorted() method combined with a lambda function to sort rows by their sum in descending order.

Example

Below is a demonstration of finding the top 3 rows with maximum sum ?

my_list = [[2, 4, 6, 7], [2, 4, 8], [45], [1, 3, 5, 6], [8, 2, 1]]

print("The list is:")
print(my_list)

my_key = 3
print("The number of top rows to select:")
print(my_key)

my_result = sorted(my_list, key=lambda row: sum(row), reverse=True)[:my_key]

print("The resultant list is:")
print(my_result)

The list is:
[[2, 4, 6, 7], [2, 4, 8], [45], [1, 3, 5, 6], [8, 2, 1]]
The number of top rows to select:
3
The resultant list is:
[[45], [2, 4, 6, 7], [1, 3, 5, 6]]

How It Works

The solution uses the following approach:

• The sorted() method sorts the list of lists based on a custom key function

• The lambda row: sum(row) function calculates the sum of each row

• The reverse=True parameter sorts in descending order (highest sum first)

• The slice [:my_key] selects only the first 3 rows from the sorted result

Row Sum Breakdown

Let's analyze the sum of each row in our example:

my_list = [[2, 4, 6, 7], [2, 4, 8], [45], [1, 3, 5, 6], [8, 2, 1]]

print("Row sums:")
for i, row in enumerate(my_list):
    print(f"Row {i}: {row} ? Sum = {sum(row)}")

print("\nSorted by sum (descending):")
sorted_rows = sorted(my_list, key=lambda row: sum(row), reverse=True)
for i, row in enumerate(sorted_rows):
    print(f"Rank {i+1}: {row} ? Sum = {sum(row)}")

Row sums:
Row 0: [2, 4, 6, 7] ? Sum = 19
Row 1: [2, 4, 8] ? Sum = 14
Row 2: [45] ? Sum = 45
Row 3: [1, 3, 5, 6] ? Sum = 15
Row 4: [8, 2, 1] ? Sum = 11

Sorted by sum (descending):
Rank 1: [45] ? Sum = 45
Rank 2: [2, 4, 6, 7] ? Sum = 19
Rank 3: [1, 3, 5, 6] ? Sum = 15

Alternative Approach Using heapq

For large datasets, you can use heapq.nlargest() for better performance ?

import heapq

my_list = [[2, 4, 6, 7], [2, 4, 8], [45], [1, 3, 5, 6], [8, 2, 1]]
my_key = 3

result = heapq.nlargest(my_key, my_list, key=sum)
print("Top 3 rows with maximum sum:")
print(result)

Top 3 rows with maximum sum:
[[45], [2, 4, 6, 7], [1, 3, 5, 6]]

Conclusion

Use sorted() with lambda for readable code when finding rows with maximum sum. For large datasets, consider heapq.nlargest() for better performance when you only need the top N rows.