Crispo - Excel Challenge 44 2024

excel-challenges
weekly-exercises
Easy Sunday Excel Challenge
Published

November 3, 2024

Illustration for Crispo - Excel Challenge 44 2024

Challenge Description

Easy Sunday Excel Challenge

⭐ Projected HeadCount Accountant ⭐Create a Recruitment plan from the Projected Headcount ⭐1st hire = 1st month of headcount

Solutions

library(tidyverse)
library(readxl)

path = "files/Excel Challenge Nov 3rd.xlsx"
input = read_excel(path, range = "B3:I8")
test  = read_excel(path, range = "K3:M15")

result = input %>%
  pivot_longer(cols = -c(1), names_to = "Month", values_to = "HC") %>%
  replace_na(list(HC = 0)) %>%
  mutate(Month = my(Month)) %>%
  mutate(Hire = HC - lag(HC, default = 0), .by = Position) %>%
  filter(Hire > 0) %>%
  select(-HC)

all.equal(result, test, check.attributes = FALSE) 
# False, one value is different. Mistake in construction of challenge.

  • 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
from pandas.tseries.offsets import MonthEnd

path = "files/Excel Challenge Nov 3rd.xlsx"
input = pd.read_excel(path, usecols="B:I", skiprows=2, nrows=6)
test = pd.read_excel(path, usecols="K:M", skiprows=2, nrows=12).rename(columns=lambda x: x.replace('.1', ''))

input = input.melt(id_vars=input.columns[0], var_name="Month", value_name="HC")
input["HC"] = input["HC"].fillna(0)
input["Month"] = pd.to_datetime(input["Month"], format='%b-%y') + MonthEnd(0)
input["Hire"] = input.groupby("Position")["HC"].diff().fillna(input["HC"]).astype(int)
result = input[input["Hire"] > 0].drop(columns=["HC"]).sort_values(by=["Position", "Month"]).reset_index(drop=True)

print(result.equals(test))  # False, one value mistaken in challenge.

  • Logic:

    • Reads the workbook range needed for the challenge

    • Reshapes the data to the grain required by the task

    • 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.