Excel BI - Excel Challenge 783

excel-challenges
excel-formulas
🔰 List the top 3 orgs by total revenue.
Published

March 24, 2026

Illustration for Excel BI - Excel Challenge 783

Challenge Description

🔰 List the top 3 orgs by total revenue.

Solutions

library(tidyverse)
library(readxl)

path = "Excel/700-799/783/783 Top 3 by Revenue.xlsx"
input = read_excel(path, range = "A2:B31")
test  = read_excel(path, range = "D2:E6")

result = input %>%
  summarise(Revenue = sum(Revenue, na.rm = TRUE), .by = Org) %>%
  mutate(Rank = dense_rank(desc(Revenue))) %>%
  arrange(Rank, desc(Org)) %>%
  filter(Rank <= 3) %>%
  select(Org, Revenue)

all.equal(result, test)
# > [1] TRUE
  • Logic: Read the workbook ranges needed for the challenge; Derive the required intermediate columns; Aggregate or rank the data at the required grouping level.
  • Strengths: The code maps the workbook rule into a compact, reproducible pipeline.
  • Areas for Improvement: The solution assumes the workbook layout and selected ranges remain stable, so any structural change in the sheet would require small adjustments.
  • Gem: The elegant part is how little code is needed once the correct intermediate representation is chosen.
import pandas as pd

path = "700-799/783/783 Top 3 by Revenue.xlsx"
input = pd.read_excel(path, usecols="A:B", skiprows=1, nrows=30)
test = pd.read_excel(path, usecols="D:E", skiprows=1, nrows=4).rename(columns=lambda c: c.replace('.1', ''))

revenue_sum = input.groupby('Org', as_index=False)['Revenue'].sum()
result = (
    revenue_sum[
        revenue_sum['Revenue'] >= revenue_sum['Revenue'].nlargest(3).min()
    ]
    .sort_values('Revenue', ascending=False)
    .reset_index(drop=True)
)

print(result.equals(test)) # True

The Python version follows the same grouped logic and keeps the transformation explicit in a dataframe pipeline.

Difficulty Level

Easy / Medium

The business rule is clear, though the workbook still needs a few transformation steps to reach the expected output.