Drop a CSV and get a per-column report: types, completeness, uniqueness, distributions, min/max/mean, standard deviation and outliers — the health check you'd otherwise write in pandas.
Before you trust a dataset, you profile it. This reads every column, classifies it, and reports completeness, uniqueness, distribution and outliers — a one-screen data-quality report.
Types are auto-detected per column; Excel files convert automatically.
Dataset completeness and duplicates up top; a card per column with stats and a mini distribution.
High null rates, outliers and duplicate rows are surfaced so you know what to clean next.
The profiling you'd do in pandas, on any CSV, in your browser — no setup.
Type, completeness, uniqueness, and for numbers: min, max, mean, median, standard deviation.
A mini histogram for numeric columns and top-value bars for categories — see the shape instantly.
Values beyond 2σ are counted per column, and duplicate full rows are flagged for the dataset.
Your data is profiled in the browser. Nothing is uploaded.