library(tidyverse)
library(readxl)
path = "files/CH-079 Remove Blank Columns.xlsx"
input = read_excel(path, range = "B2:I6")
test = read_excel(path, range = "K2:N6")
result = input %>%
select(-where(~all(is.na(.))))
identical(result, test)
# [1] TRUEOmid - Challenge 79
data-challenges
advanced-exercises
🔰 Question Result Column 1 Column 2 Column 3 Column 4 Column 5 Column 6

Challenge Description
🔰 Question Result Column 1 Column 2 Column 3 Column 4 Column 5 Column 6
Solutions
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 = "CH-079 Remove Blank Columns.xlsx"
input = pd.read_excel(path, usecols="B:I", skiprows=1)
test = pd.read_excel(path, usecols="K:N", skiprows=1)
test.columns = test.columns.str.replace('.1', '')
result = input.loc[:, input.columns[~input.isnull().all()]]
print(result.equals(test)) # 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 business rule is readable, but the workbook still requires careful implementation to reach the expected layout.