library(tidyverse)
library(readxl)
path = "Excel/700-799/713/713 Split and Extract.xlsx"
input = read_excel(path, range = "A2:B6")
test = read_excel(path, range = "D2:E12")
result = input %>%
mutate(rn = row_number()) %>%
separate_rows(Data, sep = ", ") %>%
mutate(Value = Value * row_number(), .by = rn) %>%
select(-rn)
all.equal(result, test, check.attributes = FALSE)
#> [1] TRUEExcel BI - Excel Challenge 713
excel-challenges
excel-formulas
🔰 Split the data, stack and multiply the values by 1, 2, 3….for each split.

Challenge Description
🔰 Split the data, stack and multiply the values by 1, 2, 3….for each split.
Solutions
- Logic: Read the workbook ranges needed for the challenge; Derive the required intermediate columns; Parse the packed text or string structure; 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 = "700-799/713/713 Split and Extract.xlsx"
input = pd.read_excel(path, usecols="A:B", skiprows=1, nrows=4)
test = pd.read_excel(path, usecols="D:E", skiprows=1, nrows=10).rename(columns=lambda x: x.rstrip('.1'))
input = (input.assign(Group=lambda x: x.index + 1,
Data=lambda x: x['Data'].str.split(', '))
.explode('Data')
.assign(Position=lambda x: x.groupby('Group').cumcount() + 1,
Value=lambda x: x['Position'] * x['Value']))
result = input[['Data', 'Value']].reset_index(drop=True)
print(result.equals(test))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.