library(tidyverse)
library(readxl)
path = "files/CH-221 Combining the columns.xlsx"
input = read_excel(path, range = "B2:B7")
test = read_excel(path, range = "E2:E7")
result = input %>%
mutate(Text = str_remove_all(Text, "[a-z]"))
all.equal(result, test)
#> [1] TRUEOmid - Challenge 221
data-challenges
advanced-exercises
🔰 Extract the upper case characters

Challenge Description
🔰 Extract the upper case characters
Solutions
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 = "CH-221 Combining the columns.xlsx"
input_data = pd.read_excel(path, usecols="B", skiprows=1, nrows=6)
test = pd.read_excel(path, usecols="E", skiprows=1, nrows=6).rename(columns=lambda col: col.replace('.1', ''))
input_data['Text'] = input_data['Text'].str.replace(r'[a-z]', '', regex=True)
print(input_data.equals(test)) # TrueLogic:
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.