library(tidyverse)
library(readxl)
path = "files/2025-08-10/Challenge 50.xlsx"
input = read_excel(path, range = "A2:C14")
test = read_excel(path, range = "E2:E6")
param = "National ID"
result = input %>%
nest_by(`Staff No.`) %>%
mutate(has_id = any(data$Identifiers == param)) %>%
filter(!has_id | is.na(has_id)) %>%
select(`Staff No.`)
all.equal(result$`Staff No.`, test$`Staff Without National ID`)
# > [1] TRUECrispo - Excel Challenge 32 2025
excel-challenges
weekly-exercises
Easy Sunday Excel Challenge

Challenge Description
Easy Sunday Excel Challenge
⭐ ⭐Filter staff without National ID
Solutions
Logic:
Reads the workbook range needed for the challenge
Builds the intermediate helper columns that drive the final answer
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/2025-08-10/Challenge 50.xlsx"
param = "National ID"
input = pd.read_excel(path, usecols="A:C", skiprows=1, nrows = 12)
test = pd.read_excel(path, usecols="E", skiprows=1, nrows = 4).squeeze().to_list()
result = (input.groupby('Staff No.')
.filter(lambda g: param not in g['Identifiers'].values)
['Staff No.'].unique().tolist())
print(result == test) # TrueLogic:
Reads the workbook range needed for the challenge
Aggregates or ranks values at the correct grouping level
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.