library(tidyverse)
library(readxl)
path = "files/200-299/292/CH-292 Advanced Filtering.xlsx"
input = read_excel(path, range = "B2:E9")
test = read_excel(path, range = "G2:G6")
result = input %>%
rowwise() %>%
filter(n_distinct(c_across(-ID)) == ncol(across(-ID))) %>%
ungroup() %>%
select(ID)
all.equal(result$ID, test$`Selected IDs`) # TRUEOmid - Challenge 292
data-challenges
advanced-exercises
🔰 : Advanced Filtering!

Challenge Description
🔰 : Advanced Filtering!
Solutions
Logic:
- Reads the workbook ranges needed for the challenge
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 = "200-299/292/CH-292 Advanced Filtering.xlsx"
input = pd.read_excel(path, usecols="B:E", skiprows=1, nrows=8)
test = pd.read_excel(path, usecols="G", skiprows=1, nrows=4)
result = input[input.drop('ID', axis=1).apply(lambda row: len(set(row)) == len(row), axis=1)][['ID']].reset_index(drop=True)
print(result['ID'].equals(test['Selected IDs'])) # 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 business rule is readable, but the workbook still requires careful implementation to reach the expected layout.