Crispo - Excel Challenge 22 2024

excel-challenges
weekly-exercises
Easy Sunday Excel Challenge
Published

June 2, 2024

Illustration for Crispo - Excel Challenge 22 2024

Challenge Description

Easy Sunday Excel Challenge

⭐ ⭐Extract the LAST Correct Order

Solutions

library(tidyverse)
library(readxl)

input = read_excel("files/Excel Challenge 2nd June.xlsx", range = "C2:C8")
test  = read_excel("files/Excel Challenge 2nd June.xlsx", range = "D2:D8")

result = input %>%
  mutate(last_letter = map_int(str_locate_all(`Customers & Orders`,
                                              "[A-Za-z]"),
                               ~max(.x[,2]))) %>%
  mutate(answer = ifelse(last_letter < nchar(`Customers & Orders`), 
                         str_sub(`Customers & Orders`, last_letter + 1), 
                         NA_character_))
           
identical(result$answer, test$`Last Correct Order`)         
#> [1] TRUE

  • 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
import re

path = "Excel Challenge 2nd June.xlsx"
input_data = pd.read_excel(path, usecols="C", skiprows=1, nrows=7)
test = pd.read_excel(path, usecols="D", skiprows=1, nrows=7)

def tail_after_last_letter(text):
    matches = list(re.finditer(r"[A-Za-z]", str(text)))
    if not matches:
        return None
    last_pos = matches[-1].end()
    return text[last_pos:] if last_pos < len(text) else None

result = input_data.assign(answer=input_data["Customers & Orders"].map(tail_after_last_letter))
print(result["answer"].equals(test["Last Correct Order"]))

  • 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 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.