Omid - Challenge 367

data-challenges
advanced-exercises
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Published

March 24, 2026

Illustration for Omid - Challenge 367

Challenge Description

πŸ”° 🧩 Adding Explanations If you want to include explanations or extra notes: 🌐 Sharing External Content πŸ—£ Feedback I always appreciate your feedback β€” feel free to share an…

Solutions

library(tidyverse)
library(readxl)

path <- "300-399/367/CH-367 Text Cleaning.xlsx"
input <- read_excel(path, range = "B3:B9")
test <- read_excel(path, range = "E3:E9")

result <- input %>%
  mutate(ID = str_replace(ID, "(.+)\\1+", "\\1"))

all.equal(result$ID, test$ID)
# [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
import re

path = "300-399/367/CH-367 Text Cleaning.xlsx"
input = pd.read_excel(path, usecols="B", nrows = 7, skiprows = 2)
test = pd.read_excel(path, usecols="E", nrows=7, skiprows=2).rename(columns=lambda x: x.replace(".1", ""))

input['ID'] = input['ID'].apply(lambda x: re.sub(r'(.+)\1+', r'\1', x))

print(input.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.