Crispo - Excel Challenge 21 2025

excel-challenges
weekly-exercises
Easy Sunday Excel Challenge
Published

May 25, 2025

Illustration for Crispo - Excel Challenge 21 2025

Challenge Description

Easy Sunday Excel Challenge

⭐ Problem Solution Words Easy Sunday Excel Challenge gy mnop

Solutions

library(tidyverse)
library(readxl)

path = "files/2025-05-25/Challenge25.xlsx"
input = read_excel(path, range = "B3:B12")
test = read_excel(path, range = "D3:D6")

letters2 = rep(letters, 2) %>% paste0(collapse = "")
sequences = map(1:26, ~ substr(letters2, .x, .x + 3)) %>% unlist()

result = input %>%
  mutate(
    contains_sequence = map_lgl(Words, ~ any(str_detect(.x, sequences)))
  ) %>%
  filter(contains_sequence) %>%
  select(Words)

all.equal(result$Words, test$Words)
# [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
import string

path = "files/2025-05-25/Challenge25.xlsx"
input = pd.read_excel(path, usecols="B", skiprows=2, nrows=10)
test = pd.read_excel(path, usecols="D", skiprows=2, nrows=3).rename(columns=lambda col: col.replace('.1', ''))

seqs = [string.ascii_lowercase * 2][0]
seqs = [seqs[i:i+4] for i in range(26)]

def has_seq(word):
    return any(re.search(seq, word) for seq in seqs)

result = input[input['Words'].apply(has_seq)][['Words']].reset_index(drop=True)

print(result.equals(test))

  • Logic:

    • Reads the workbook range needed for the challenge

    • Uses direct text-pattern extraction instead of manual cleanup

    • Applies the rule iteratively until the output is complete

  • 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.