Omid - Challenge 57

data-challenges
advanced-exercises
🔰 In the question table, several fuzzy numbers are presented, and we want to calculate the results of adding and subtracting these numbers.
Published

March 24, 2026

Illustration for Omid - Challenge 57

Challenge Description

🔰 In the question table, several fuzzy numbers are presented, and we want to calculate the results of adding and subtracting these numbers.

Solutions

library(tidyverse)
library(readxl)

input = read_excel("files/CH-057 Fuzzy Numbers Calculation.xlsx", range = "B2:C15")
test  = read_excel("files/CH-057 Fuzzy Numbers Calculation.xlsx", range = "G2:H15")

result = input %>%
  separate(A, into = c("A1", "A2", "A3"), sep = ",", convert = TRUE) %>%
  separate(B, into = c("B1", "B2", "B3"), sep = ",", convert = TRUE) %>%
  mutate(
    A = pmap(list(A1, A2, A3), c),
    B = pmap(list(B1, B2, B3), c),
    `A+B` = map2_chr(A, B, ~ paste(.x + .y, collapse = ",")),
    `A-B` = map2_chr(A, map(B, rev), ~ paste(.x - .y, collapse = ","))
  ) %>%
  select(`A+B`, `A-B`)

identical(result, test)
# [1] TRUE

  • 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

input = pd.read_excel("CH-057 Fuzzy Numbers Calculation.xlsx", sheet_name="Sheet1", usecols="B:C", skiprows=1, nrows = 13)
test = pd.read_excel("CH-057 Fuzzy Numbers Calculation.xlsx", sheet_name="Sheet1", usecols="G:H", skiprows=1, nrows = 13)

input[['A1', 'A2', 'A3']] = input['A'].str.split(',', expand=True).astype(int)
input[['B1', 'B2', 'B3']] = input['B'].str.split(',', expand=True).astype(int)

input['A'] = input[['A1', 'A2', 'A3']].values.tolist()
input['B'] = input[['B1', 'B2', 'B3']].values.tolist()

input['A+B'] = input.apply(lambda row: [str(x + y) for x, y in zip(row['A'], row['B'])], axis=1)
input['A-B'] = input.apply(lambda row: [str(x - y) for x, y in zip(row['A'], row['B'][::-1])], axis=1)

result = input[['A+B', 'A-B']]

result['A+B'] = result['A+B'].apply(lambda x: ','.join(x))
result['A-B'] = result['A-B'].apply(lambda x: ','.join(x))

print(result.equals(test)) # True

  • 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.