Omid - Challenge 36

data-challenges
advanced-exercises
🔰 we want to extracth all non dominant solutions.
Published

March 24, 2026

Illustration for Omid - Challenge 36

Challenge Description

🔰 we want to extracth all non dominant solutions.

Solutions

library(tidyverse)
library(readxl)

input = read_excel("files/CH-036 Pareto Line.xlsx", range = "B2:E14")
test  = read_excel("files/CH-036 Pareto Line.xlsx", range = "H1:H7") %>% na.omit()

result = input %>%
  mutate(row_id = row_number()) %>%
  pmap(., function(...){
    current = tibble(...)
    dominated = any(pmap_lgl(input, function(...){
      other = tibble(...)
      all(other[2:4] > current[2:4])
    }))
    !dominated
  }) %>%
  unlist() %>%
  which() %>%
  tibble(Result = .) %>%
  mutate(Result = as.numeric(Result))

all.equal(result, test, check.attributes = FALSE)
# [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-036 Pareto Line.xlsx", usecols="B:E", nrows = 14, skiprows=1)
test = pd.read_excel("CH-036 Pareto Line.xlsx", usecols="H", nrows=7).dropna().astype(int).reset_index(drop=True)
result = input.assign(row_id=range(1, len(input) + 1)).apply(lambda row: not any((input.iloc[:, 1:4] > row[1:4]).all(axis=1)), axis=1)
result = result[result].index.to_frame(index=False).rename(columns={0: "Result"}) + 1
result["Result"] = result["Result"].astype(int)

print(result.equals(test)) # True

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Builds the intermediate columns that drive the final result

  • 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.