library(tidyverse)
library(readxl)
path = "Excel/700-799/727/727 Remove Duplicates.xlsx"
input = read_excel(path, range = "A2:C15")
test = read_excel(path, range = "E2:G10")
result = input %>%
summarise(Amount = last(Amount), .by = c("State", "Stock"))
all.equal(result, test)
#> [1] TRUEExcel BI - Excel Challenge 727
excel-challenges
excel-formulas
🔰 Answer Expected State Stock Amount Alaska A B C California Kansas

Challenge Description
🔰 Answer Expected State Stock Amount Alaska A B C California Kansas
Solutions
- Logic: Read the workbook ranges needed for the challenge; 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 = "700-799/727/727 Remove Duplicates.xlsx"
input = pd.read_excel(path, usecols="A:C", skiprows=1, nrows=13)
test = pd.read_excel(path, usecols="E:G", skiprows=1, nrows=8).rename(columns=lambda col: col.replace('.1', ''))
result = input.groupby(['State','Stock'], as_index=False)['Amount'].last()
print(result.equals(test)) # TrueThe 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.