Understand any dataset
before you write
a single line of code.
Zedda profiles, cleans and validates datasets from a single call. It scales from a 900-row CSV to a terabyte Parquet file — without changing how you use it.
pip install zedda
Ten functions. Zero setup. One import.
C++17 core, constant memory
The engine streams data instead of loading it. A 900-row CSV and a terabyte Parquet file use the same tiny memory footprint.
ML readiness score
Get a 0–100 score flagging the issues that quietly wreck model accuracy.
Drift detection
Compare train vs. production data to catch schema and distribution drift early.
Safe auto-clean with audit trail
Impute, drop sparse columns and encode strings automatically — always with a backup and a JSON audit log so nothing is ever lost.
Discovery should be free
You should be able to look inside any dataset in one line — no boilerplate, no 40-cell notebook, no guessing.
Scale should be invisible
The same call that profiles a 900-row CSV should profile a terabyte of Parquet. You change the file, not your code.
Cleaning should be honest
Every fix is logged, every original is backed up. Automation you can actually trust in production.