Automated data quality alerts (duplicates, multicollinearity, class imbalance, high cardinality, missing values, mixed types)
Interactive Plotly-based HTML reports
CSV / Excel / JSON / Parquet support
Python API + plugin system
Why I built it
Existing tools are powerful, but often heavy, slow on medium datasets, or not CLI-first.
SpeedyEDA is designed for quick inspection, scripts, and daily dev workflows.
The idea is simple: remove EDA boilerplate and make data inspection something you can run in one command, directly from the terminal or CI.
fasteda data.csv --fun
Or generate a standalone interactive HTML report:
fasteda data.csv --html report.html
What it includes
Automatic statistics + detailed quantiles
Multiple correlation methods (Pearson, Spearman, Kendall)
Outlier detection (IQR + Z-score)
Automated data quality alerts (duplicates, multicollinearity, class imbalance, high cardinality, missing values, mixed types)
Interactive Plotly-based HTML reports
CSV / Excel / JSON / Parquet support
Python API + plugin system
Why I built it
Existing tools are powerful, but often heavy, slow on medium datasets, or not CLI-first. SpeedyEDA is designed for quick inspection, scripts, and daily dev workflows.
Links
PyPI: https://pypi.org/project/speedyeda/
GitHub:https://github.com/Dawaman43/fasteda
Would love feedback—especially on performance, missing checks, and real-world edge cases.
Thanks!