library(tidyverse)
library(readxl)
path <- "300-399/351/CH-351 Filter.xlsx"
input <- read_excel(path, range = "B3:B10")
test <- read_excel(path, range = "F3:F6")
result = input %>%
filter(str_detect(ID, "M.*N.*M.*"))
all.equal(result, test)
# [1] TRUEOmid - Challenge 351
data-challenges
advanced-exercises
🔰 Challenge 351: Filter!

Challenge Description
🔰 Challenge 351: Filter!
Solutions
Logic:
Reads the workbook ranges needed for the challenge
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 = "300-399/351/CH-351 Filter.xlsx"
input_data = pd.read_excel(path, usecols="B", skiprows=2, nrows=8)
test_data = pd.read_excel(path, usecols="F", skiprows=2, nrows=3).rename(columns=lambda x: x.rstrip('.1'))
result = input_data[input_data.iloc[:, 0].str.contains(r"M.*N.*M.*", na=False)].reset_index(drop=True)
print(result.equals(test_data)) # TrueLogic:
- 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.