Omid - Challenge 204

data-challenges
advanced-exercises
🔰 Group Custom Grouping Group the rows from top which in each group the total cost be lower than 150$ and each group includes up to three rows.
Published

March 24, 2026

Illustration for Omid - Challenge 204

Challenge Description

🔰 Group Custom Grouping Group the rows from top which in each group the total cost be lower than 150$ and each group includes up to three rows.

Solutions

library(tidyverse)
library(readxl)

path = "files/CH-204 Custom Grouping.xlsx"
input = read_excel(path, range = "B2:C19")
test  = read_excel(path, range = "H2:J19")

result = input %>%
  mutate(Group = accumulate(Cost, 
                              ~ if (.x$sum + .y > 150 | .x$count == 3) 
                                list(sum = .y, count = 1, group = .x$group + 1) 
                              else 
                                list(sum = .x$sum + .y, count = .x$count + 1, group = .x$group),
                              .init = list(sum = 0, count = 0, group = 1)
  )[-1] %>% map_int("group"))

# Solution has differences in Cost so Groups are not matching.

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Builds the intermediate columns that drive the final result

  • Strengths:

    • The R solution stays close to the workbook rule and keeps the transformation compact.

  • Areas for Improvement:

    • The code assumes the sheet structure and source ranges remain stable.

  • Gem:

    • The strongest part of the solution is choosing the right intermediate representation before shaping the final output.
import pandas as pd
from itertools import accumulate

path = "CH-204 Custom Grouping.xlsx"
input = pd.read_excel(path, usecols="B:C", skiprows=1, nrows=17)
test = pd.read_excel(path, usecols="H:J", skiprows=1, nrows=17)

def accumulate_groups(costs):
    groups, acc_sum, acc_count, group = [], 0, 0, 1
    for cost in costs:
        if acc_sum + cost > 150 or acc_count == 3:
            group += 1
            acc_sum, acc_count = cost, 1
        else:
            acc_sum += cost
            acc_count += 1
        groups.append(group)
    return groups

input['Group'] = accumulate_groups(input['Cost'])

print(input)

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Applies the rule iteratively until the output stabilizes

  • Strengths:

    • The Python version follows the same rule in a direct dataframe-oriented implementation.

  • Areas for Improvement:

    • The code assumes the workbook layout remains stable, so any sheet redesign would require small adjustments.

  • Gem:

    • The implementation stays close to the original workbook rule instead of adding unnecessary abstraction.

Difficulty Level

This task is moderate:

  • The business rule is readable, but the workbook still requires careful implementation to reach the expected layout.