Omid - Challenge 354

data-challenges
advanced-exercises
🔰 Grouping Starting from the top row, group every two rows and calculate the total sales for each group
Published

March 24, 2026

Illustration for Omid - Challenge 354

Challenge Description

🔰 Grouping Starting from the top row, group every two rows and calculate the total sales for each group

Solutions

library(tidyverse)
library(readxl)

path <- "300-399/354/CH-354 Custom Grouping.xlsx"
input <- read_excel(path, range = "B3:C9")
test <- read_excel(path, range = "F3:G9")

result = input %>%
  transmute(
    IDs = ifelse(row_number() == n(), ID, paste0(ID, ",", lead(ID, 1, ))),
    Sales = ifelse(row_number() == n(), Sales, Sales + lead(Sales, 1))
  )

all.equal(result, test)
# [1] TRUE

  • Logic:

    • Reads the workbook ranges needed for the challenge

  • Strengths:

    • The R solution stays close to the workbook rule and keeps the transformation compact.

  • Areas for Improvement:

    • The code assumes the sheet structure and source ranges remain stable.

  • Gem:

    • The strongest part of the solution is choosing the right intermediate representation before shaping the final output.
import pandas as pd

path = "300-399/354/CH-354 Custom Grouping.xlsx"
input = pd.read_excel(path, usecols="B:C", skiprows=2, nrows=7)
test = pd.read_excel(path, usecols="F:G", skiprows=2, nrows=7).rename(columns=lambda col: col.replace('.1', ''))

def custom_transmute(df):
    result = pd.DataFrame()
    result["IDs"] = df["ID"].astype(str)
    result["Sales"] = df["Sales"]
    result.iloc[:-1, result.columns.get_loc("IDs")] = (
        df["ID"].astype(str).values[:-1] + "," + df["ID"].astype(str).values[1:]
    )
    result.iloc[:-1, result.columns.get_loc("Sales")] = (
        df["Sales"].values[:-1] + df["Sales"].values[1:]
    )
    return result

result = custom_transmute(input)
print(result.equals(test))
# True

  • Logic:

    • Reads the workbook ranges needed for the challenge

  • Strengths:

    • The Python version follows the same rule in a direct dataframe-oriented implementation.

  • Areas for Improvement:

    • The code assumes the workbook layout remains stable, so any sheet redesign would require small adjustments.

  • Gem:

    • The implementation stays close to the original workbook rule instead of adding unnecessary abstraction.

Difficulty Level

This task is moderate:

  • The business rule is readable, but the workbook still requires careful implementation to reach the expected layout.