Omid - Challenge 316

data-challenges
advanced-exercises
🔰 Challenge 316: Convert Text In the question table, convert lowercase characters to uppercase and vice versa.
Published

March 24, 2026

Illustration for Omid - Challenge 316

Challenge Description

🔰 Challenge 316: Convert Text In the question table, convert lowercase characters to uppercase and vice versa.

Solutions

library(tidyverse)
library(readxl)

path = "files/300-399/316/CH-316 Convert Text.xlsx"
input = read_excel(path, range = "B1:B6")
test  = read_excel(path, range = "C1:C6")

result = input %>%
  mutate(Result = chartr("[a-zA-Z]", "[A-Za-z]", Question))

all.equal(result$Result, test$Result) 
# some result provided are not correct)

# Solution 2 - more expanded
result2 = input %>%
  mutate(Split = strsplit(Question, split = "")) %>%
  unnest(Split) %>%
  mutate(Split = ifelse(Split == str_to_lower(Split), str_to_upper(Split), str_to_lower(Split))) %>%
  summarise(Result = paste0(Split, collapse = ""), .by = Question)

all.equal(result2$Result, test$Result)         
# some result provided are not correct)

  • Logic:

    • Reads the workbook ranges needed for the challenge

    • Aggregates or ranks values at the relevant grouping level

    • 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 = "300-399/316/CH-316 Convert Text.xlsx"

input = pd.read_excel(path, usecols="B", nrows=6)
test = pd.read_excel(path, usecols="C", nrows=6)

result = input.copy()
result['Question'] = input['Question'].str.swapcase()

print(result.equals(test)) #not all answers provided are correct

  • Logic:

    • Reads the workbook ranges needed for the challenge

  • 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.