Omid - Challenge 335

data-challenges
advanced-exercises
🔰 Challenge 335: Table Transformation!
Published

March 24, 2026

Illustration for Omid - Challenge 335

Challenge Description

🔰 Challenge 335: Table Transformation!

Solutions

library(tidyverse)
library(readxl)

path <- "300-399/335/CH-335 Table Transformation.xlsx"
input <- read_excel(path, range = "B2:C7")
test <- read_excel(path, range = "G2:H11")

result = input %>%
  mutate(
    prefix = str_extract(Level, "^[^0-9]+"),
    nums = str_extract(Level, "[0-9,]+")
  ) %>%
  separate_rows(nums, sep = ",") %>%
  mutate(Level = str_c(prefix, nums)) %>%
  select(`Issue ID`, Level)

all.equal(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
import re

path = "300-399/335/CH-335 Table Transformation.xlsx"
df = pd.read_excel(path, usecols="B:C", skiprows=1, nrows=6)
test_df = pd.read_excel(path, usecols="G:H", skiprows=1, nrows=10).rename(columns=lambda c: c.replace('.1', ''))

result = pd.DataFrame(
    [{"Issue ID": r["Issue ID"], "Level": re.match(r"^[^0-9]+", r["Level"]).group(0) + n}
     for _, r in df.iterrows()
     if isinstance(r["Level"], str)
     for n in re.findall(r"\d+", r["Level"])]
)

print(result.equals(test_df))

  • Logic:

    • Reads the workbook ranges needed for the challenge

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

    • 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 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.