Crispo - Excel Challenge 01 2026

excel-challenges
weekly-exercises
Easy Sunday Excel Challenge
Published

January 4, 2026

Illustration for Crispo - Excel Challenge 01 2026

Challenge Description

Easy Sunday Excel Challenge

⭐ Problem Solution Chapter Pages Chapter 1 Section 1

Solutions

library(tidyverse)
library(readxl)

path <- "2026-01-04/Challenge 89.xlsx"
input1 <- read_excel(path, range = "B4:C6")
input2 <- read_excel(path, range = "B9:C11")
test <- read_excel(path, range = "F4:G11", col_names = FALSE) %>%
  select(`0` = 1, `1` = 2)

result = crossing(input1, input2) %>%
  mutate(Pages = as.character(Pages)) %>%
  pivot_longer(
    cols = everything(),
    names_to = "type",
    values_to = "value"
  ) %>%
  mutate(id = (row_number() + 1) %% 2, id2 = (row_number() + 1) %/% 2) %>%
  pivot_wider(
    id_cols = id2,
    names_from = id,
    values_from = value
  ) %>%
  select(-id2)

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

  • Logic:

    • Reads the workbook range needed for the challenge

    • Reshapes the data to the grain required by the task

    • 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 = "2026-01-04/Challenge 89.xlsx"

input1 = pd.read_excel(path, usecols="B:C", skiprows=3, nrows=2)
input2 = pd.read_excel(path, usecols="B:C", skiprows=8, nrows=2)
test = pd.read_excel(path, usecols="F:G", skiprows=3, nrows=8, header=None, dtype=str)

test.columns = [0, 1]
input1['Pages'] = input1['Pages'].astype(str)

result = input1.merge(input2, how="cross")[["Chapter", "Pages", "Section", "Part"]].to_numpy().reshape(-1, 2)

out = pd.DataFrame(result, columns=[0, 1]).reset_index(drop=True)
test = test.reset_index(drop=True)

print(out.equals(test))  # True

  • Logic:

    • Reads the workbook range needed for the challenge

  • 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.