Omid - Challenge 115

data-challenges
advanced-exercises
🔰 Result Question Total Sales Product ID Date Customer ID XNM00012 XNM-13
Published

March 24, 2026

Illustration for Omid - Challenge 115

Challenge Description

🔰 Result Question Total Sales Product ID Date Customer ID XNM00012 XNM-13

Solutions

library(tidyverse)
library(readxl)

path = "files/CH-115 Multi Replacement.xlsx"
input = read_excel(path, range = "B2:E9")
test  = read_excel(path, range = "G2:J9")

result = input %>%
  mutate(across(c(`Product ID`, `Customer ID`), ~str_replace(., "0{3}|q", "-")))

identical(result, test)
#> [1] TRUE

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Builds the intermediate columns that drive the final result

    • Parses the text patterns directly instead of relying on manual cleanup

  • 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

path = "CH-115 Multi Replacement.xlsx"
input = pd.read_excel(path, usecols="B:E", skiprows=1)
test = pd.read_excel(path, usecols="G:J", skiprows=1).rename(columns=lambda x: x.replace(".1", ""))

result = input.replace({"0{3}|q": "-"}, regex=True)

print(result.equals(test))  # True

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Parses the text patterns directly instead of relying on manual cleanup

  • 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 core logic is clear, but the correct transformation pattern is not obvious from the raw input.

  • The challenge combines multiple reshaping, grouping, or parsing steps.