Excel BI - PowerQuery Challenge 246

excel-challenges
power-query
Deal ID Date Designation Name Mgr GM
Published

March 24, 2026

Illustration for Excel BI - PowerQuery Challenge 246

Challenge Description

Deal ID Date Designation Name Mgr GM

Solutions

library(tidyverse)
library(readxl)

path = "Power Query/PQ_Challenge_246.xlsx"
input = read_excel(path, range = "A1:D14")
test  = read_excel(path, range = "F1:I5")

result = input %>%
  filter(Date == max(Date), .by = `Deal ID`) %>%
  select(-Date) %>%
  pivot_wider(names_from = Designation, values_from = Name, values_fn =  ~ str_c(.x, collapse = ", ")) %>%
  select(`Deal ID`, Mgr, GM, VP)

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

  • Logic:

    • Reads the workbook range needed for the challenge

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

    • 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_246.xlsx"
input = pd.read_excel(path, usecols="A:D", nrows=14)
test = pd.read_excel(path, usecols="F:I", nrows=4).rename(columns=lambda x: x.split('.')[0])

result = input[input['Date'] == input.groupby('Deal ID')['Date'].transform('max')].pivot_table(
    index='Deal ID', columns='Designation', values='Name', aggfunc=', '.join).reset_index()[['Deal ID', 'Mgr', 'GM', 'VP']].rename_axis(None, axis=1)

print(result.equals(test)) # True

  • Logic:

    • Reads the workbook range needed for the challenge

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

    • 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.