Crispo - Excel Challenge 07 2026

excel-challenges
weekly-exercises
Easy Sunday Excel Challenge
Published

February 15, 2026

Illustration for Crispo - Excel Challenge 07 2026

Challenge Description

Easy Sunday Excel Challenge

⭐ ⭐Suffix include Invoice “D” + Invoice digit + Duplicate Count

Solutions

library(tidyverse)
library(readxl)

path <- "2026-02-15/Challenge 103.xlsx"
input <- read_excel(path, range = "B2:B13")
test <- read_excel(path, range = "D2:D13")

result <- input %>%
  mutate(
    n = row_number() - 1,
    .by = Invoice,
    `Suffixed Invoice` = if_else(
      n == 0,
      Invoice,
      paste0(Invoice, "_D", str_extract(Invoice, "\\d+"), "-", n)
    )
  ) %>%
  select(`Suffixed Invoice`)

all.equal(result$`Suffixed Invoice`, test$`Suffixed Invoice`)
# Inconsitent second delim in test data, but otherwise correct.

  • Logic:

    • Reads the workbook range needed for the challenge

    • Builds the intermediate helper columns that drive the final answer

    • Uses direct text-pattern extraction instead of manual cleanup

  • 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 = "2026-02-15/Challenge 103.xlsx"
input = pd.read_excel(path, usecols="B", skiprows=1, nrows=12)
test = pd.read_excel(path, usecols="D", skiprows=1, nrows=12)

c = input.groupby("Invoice").cumcount()
result = pd.DataFrame({
    "Suffixed Invoice": input["Invoice"].where(
        c.eq(0),
        input["Invoice"] + "_D" +
        input["Invoice"].str.extract(r"(\d+)")[0] +
        "-" + c.astype(str)
    )
})

print(result.equals(test))
# Inconsitent second delim in test data, but otherwise correct.

  • Logic:

    • 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 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.