PyJanitor
What it is: Pandas extension library inspired by R's janitor. Adds convenient methods for common data cleaning tasks. Clean API with method chaining for readable data pipelines.
What It Does Best
Clean column names. One method call to standardize: lowercase, remove spaces, strip special characters. .clean_names() handles messy Excel columns instantly.
Method chaining. Readable data pipelines: df.clean_names().remove_empty().drop_duplicates(). Cleaner than nested function calls.
Common operations simplified. Remove empty rows/columns, encode categoricals, add columns with calculations. Does what you always wished pandas did out of the box.
Pricing
Free. Open source, MIT license.
When to Use It
✅ Working with messy Excel/CSV files
✅ Want cleaner pandas code
✅ Repeating same cleaning steps across projects
✅ Like method chaining style
When NOT to Use It
❌ Team unfamiliar with it (adds dependency)
❌ Need maximum performance (small overhead)
❌ Very simple one-off scripts
Bottom line: Makes pandas code cleaner and more readable. If you're tired of writing the same cleaning code, pyjanitor has helpers for it. Small learning curve, big payoff in code clarity.