Excel BI - PowerQuery Challenge 242

excel-challenges
power-query
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Published

March 24, 2026

Illustration for Excel BI - PowerQuery Challenge 242

Challenge Description

Hall Date Guest1 Guest2 Guest3 Guest4

Solutions

library(tidyverse)
library(readxl)

path = "Power Query/PQ_Challenge_242.xlsx"
input = read_excel(path, range = "A1:F5")
test  = read_excel(path, range = "H1:I16") 

result = input %>%
  mutate(across(everything(), as.character)) %>%
  mutate(no = row_number() %>% as.character(), .by = Hall) %>%
  unite(Hall, Hall, no, sep = "_") %>%
  pivot_longer(everything(), names_to = "name", values_to = "value") %>%
  filter(!is.na(value), !str_ends(value, "_2")) %>%
  mutate(value = str_remove(value, "_1"))

colnames(result) = colnames(test)

all.equal(result, test, check.attributes = FALSE)         
# not equal because of wrong formating of dates in equipment.

  • Logic:

    • Reads the workbook range needed for the challenge

    • Reshapes the data into the structure required by the result table

    • Builds helper columns that drive the final output

    • Uses direct pattern parsing where the workbook encodes logic in text

  • 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

path = "PQ_Challenge_242.xlsx"
input = pd.read_excel(path, usecols="A:F", nrows=4)
test = pd.read_excel(path, usecols="H:I", nrows=16).astype(str)
test['Column2'] = test['Column2'].str.replace(' 00:00:00', '')

input = input.astype(str)
input['Hall'] = input.groupby('Hall').cumcount().add(1).astype(str).radd(input['Hall'] + "_")

result = input.stack().reset_index()
result = result[~result[0].str.endswith('_2') & (result[0] != "nan")]
result.columns = ['Row', 'Column1', 'Column2']
result.drop(columns=['Row'], inplace=True)
result['Column2'] = result['Column2'].str.replace('_1', '')
result.reset_index(drop=True, inplace=True)


print(result.equals(test)) # True

  • Logic:

    • Reads the workbook range needed for the challenge

    • Aggregates or ranks values at the relevant grouping level

  • 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 moderate:

  • It combines reshaping, grouping, or parsing steps that are common in Power Query style problems.

  • The main challenge is reproducing the workbook output structure exactly.