Excel BI - PowerQuery Challenge 237

excel-challenges
power-query
Names English Science Maths Arts Smith
Published

March 24, 2026

Illustration for Excel BI - PowerQuery Challenge 237

Challenge Description

Names English Science Maths Arts Smith

Solutions

library(tidyverse)
library(readxl)
library(glue)

path = "Power Query/PQ_Challenge_237.xlsx"
input = read_excel(path, range = "A1:E11")
test  = read_excel(path, range = "G1:K11")

result = input %>%
  mutate(across(everything(), ~ {
    empty_index = row_number()[is.na(.)]
    ifelse(is.na(.),
           glue("{cur_column()}_{match(row_number(), empty_index)}"),
           as.character(.))}))

all.equal(result, test, check.attributes = FALSE)
# [1] TRUE

  • Logic:

    • Reads the workbook range needed for the challenge

    • Builds helper columns that drive the final output

  • Strengths:

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

  • Areas for Improvement:

    • The code assumes the workbook layout and selected ranges remain stable.

  • Gem:

    • The best part of the solution is choosing the right intermediate shape before formatting the final output.
import pandas as pd
import numpy as np
path = "PQ_Challenge_237.xlsx"

input = pd.read_excel(path, usecols="A:E", nrows=11)
test = pd.read_excel(path, usecols="G:K", nrows=11).rename(columns=lambda x: x.split('.')[0])

result = input.apply(lambda col: col.where(
col.notna(), 
[f"{col.name}_{sum(pd.isna(col[:i]))+1}" if pd.isna(val) else val for i, val in enumerate(col)]
))

result = result.map(lambda x: np.int64(x) if isinstance(x, (int, float)) and not np.isnan(x) else x)
test = test.map(lambda x: np.int64(x) if isinstance(x, (int, float)) and not np.isnan(x) else x)

print(result.equals(test)) # True

  • Logic:

    • Reads the workbook range needed for the challenge

    • Applies the rule iteratively until the output is complete

  • Strengths:

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

  • Areas for Improvement:

    • As with the R version, any workbook layout change would require small adjustments.

  • Gem:

    • The implementation stays close to the source challenge instead of adding unnecessary abstraction.

Difficulty Level

This task is easy to moderate:

  • The transformation rule is readable, but the final layout still requires a careful implementation.