postMay 22, 2026

Clean null values from a list — Python

#python#data-cleaning#challenge

Easy⏱️ Logic Challenge

Given a list with mixed values: [1, None, 2, "", 3, None, 0, 4], return only the truthy non-None values. Expected: [1, 2, 3, 4]

Ver solución

values = [1, None, 2, "", 3, None, 0, 4]

# Keep only truthy values (drops None, "", 0)
clean = [v for v in values if v]

print(clean)  # [1, 2, 3, 4]

# If you only want to drop None (keep 0 and ""):
not_null = [v for v in values if v is not None]
print(not_null)  # [1, 2, '', 3, 0, 4]

Real-world data is messy. Sources return None where you expected a value, empty strings where you expected text, and zero where you expected a date. Before you can transform or aggregate, you have to filter the noise.

This challenge teaches the most common cleaning pattern: filter a list to keep only valid items. The same logic applies whether you are using a list comprehension, Pandas dropna(), or SQL WHERE column IS NOT NULL.