Crispo - Excel Challenge 01 2025

excel-challenges
weekly-exercises
Easy Sunday Excel Challenge
Published

January 5, 2025

Illustration for Crispo - Excel Challenge 01 2025

Challenge Description

Easy Sunday Excel Challenge

⭐ Invoice Posted Dept Value INV-001 JSMITH

Solutions

library(tidyverse)
library(readxl)

path = "files/Ex-Challenge 01 2025.xlsx"
input = read_excel(path, range = "B2:E14")
test  = read_excel(path, range = "G2:J8")

result = input %>%
  mutate(across(c(Invoice, Posted, Dept), ~trimws(.))) %>%
  unite("name", c("Invoice", "Posted", "Dept"), sep = "_") %>%
  group_by(name) %>%
  filter(n() == 1 | (n() == 2 & sum(Value) != 0)) %>%
  separate("name", c("Invoice", "Posted", "Dept"), sep = "_")

all.equal(result, test)
#> [1] TRUE

  • Logic:

    • Reads the workbook range needed for the challenge

    • Aggregates or ranks values at the correct grouping level

    • 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/Ex-Challenge 01 2025.xlsx"
input = pd.read_excel(path, usecols="B:E", skiprows=1, nrows=12)
test = pd.read_excel(path, usecols="G:J", skiprows=1, nrows=6)\
    .rename(columns=lambda x: x.replace('.1', ''))\
    .apply(lambda x: x.str.strip() if x.name == 'Invoice' else x)

input['name'] = input[['Invoice', 'Posted', 'Dept']]\
    .apply(lambda x: x.str.strip()).astype(str)\
    .agg('_'.join, axis=1)

grouped = input.groupby('name')\
    .filter(lambda x: len(x) == 1 or (len(x) == 2 and x['Value'].sum() != 0))

result = grouped.copy().assign(**grouped['name'].str.split('_', expand=True).rename(columns={0: 'Invoice', 1: 'Posted', 2: 'Dept'}))\
    .drop(columns=['name']).reset_index(drop=True)

print(result.equals(test)) # True

  • Logic:

    • Reads the workbook range needed for the challenge

    • Aggregates or ranks values at the correct grouping level

    • Builds the intermediate helper columns that drive the final answer

  • 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 moderate:

  • It combines familiar Excel-style logic with at least one non-trivial reshape, grouping, or parsing step.

  • The answer depends on getting the output layout exactly right.