library(tidyverse)
library(readxl)
path = "files/2025-08-31/Challenge 53.xlsx"
input = read_excel(path, range = "B2:E8")
test = read_excel(path, range = "G2:G4") %>% pull()
result = input %>%
filter(if_all(-Customer, is.na)) %>%
pull(Customer)
all.equal(result, test)Crispo - Excel Challenge 35 2025
excel-challenges
weekly-exercises
Easy Sunday Excel Challenge

Challenge Description
Easy Sunday Excel Challenge
⭐ ⭐Filter Customers Missing all Data
Solutions
Logic:
- Reads the workbook range needed for the challenge
Strengths:
- The R solution stays compact and mirrors the workbook logic closely.
Areas for Improvement:
- The code assumes the workbook layout and named ranges remain stable.
Gem:
- The best part of the solution is choosing a tidy intermediate shape before producing the final answer.
import pandas as pd
path = "files/2025-08-31/Challenge 53.xlsx"
input = pd.read_excel(path, usecols="B:E", skiprows=1, nrows=6)
test = pd.read_excel(path, usecols="G", skiprows=1, nrows=2).squeeze().tolist()
result = input[input.drop('Customer', axis=1).isna().all(axis=1)]['Customer'].tolist()
print(test == result) # TrueLogic:
- Reads the workbook range needed for the challenge
Strengths:
- The Python version keeps the same rule in a direct pandas-oriented workflow.
Areas for Improvement:
- As with the R version, any workbook layout change would require small adjustments.
Gem:
- The implementation stays close to the stated challenge instead of adding unnecessary complexity.
Difficulty Level
This task is easy to moderate:
- The business rule is readable, but the workbook still needs a few careful transformation steps.