library(tidyverse)
library(readxl)
path <- "300-399/385/CH-385 Replacement.xlsx"
input <- read_excel(path, range = "B3:E10")
test <- read_excel(path, range = "G3:J10")
result <- input |>
mutate(
`Customer ID` = if_else(
Date >= as.POSIXct("2024-08-14"),
str_replace(`Customer ID`, "X", "C"),
`Customer ID`
)
)
all.equal(result, test)
## [1] TRUEOmid - Challenge 385
data-challenges
advanced-exercises
🔰 Result Question Total Sales Product ID Date Customer ID XNM-13 XNM-07

Challenge Description
🔰 Result Question Total Sales Product ID Date Customer ID XNM-13 XNM-07
Solutions
Logic:
Reads the workbook ranges needed for the challenge
Builds the intermediate columns that drive the final result
Parses the text patterns directly instead of relying on manual cleanup
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 = "300-399/385/CH-385 Replacement.xlsx"
input = pd.read_excel(path, usecols="B:E", skiprows=2, nrows=7)
test = pd.read_excel(path, usecols="G:J", skiprows=2, nrows=7).rename(columns=lambda c: __import__("re").sub(r"\.\d+$", "", c))
result = input.copy()
mask = result["Date"] >= pd.Timestamp("2024-08-14")
result.loc[mask, "Customer ID"] = result.loc[mask, "Customer ID"].str.replace("X", "C", n=1)
print((result == test).all().all())
## Output: TrueLogic:
- 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 core logic is clear, but the correct transformation pattern is not obvious from the raw input.
The challenge combines multiple reshaping, grouping, or parsing steps.