Excel BI - Excel Challenge 640

excel-challenges
excel-formulas
🔰 Treat the data between two pluses as one group.
Published

March 24, 2026

Illustration for Excel BI - Excel Challenge 640

Challenge Description

🔰 Treat the data between two pluses as one group. Find the sum between two pluses and also give the index number of those groups.

Solutions

library(tidyverse)
library(readxl)

path = "Excel/640 Sum Between Two Pluses.xlsx"
input = read_excel(path, range = "A2:A21")
test  = read_excel(path, range = "C2:D8")

result = input %>%
  mutate(index = cumsum(Data == "+")) %>%
  filter(Data != "+") %>%
  summarise(sum = sum(as.numeric(Data)), .by = index)

all.equal(result$sum, test$Sum)
#> [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 = "640 Sum Between Two Pluses.xlsx"
input = pd.read_excel(path, usecols="A", skiprows=1, nrows=20)
test = pd.read_excel(path, usecols="C:D", skiprows=1, nrows=6)

input['Group'] = (input['Data'] == '+').cumsum().astype('int64')
filtered = input[input['Data'] != '+']
result = filtered.groupby('Group').agg({'Data': lambda x: x.astype(float).sum()}).reset_index()    
result.columns = ['Group', 'Sum']
result['Sum'] = result['Sum'].astype('int64')

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.