Column Statistics Generator
Get descriptive statistics for every numeric column at once. The generator calculates count, missing values, sum, mean, median, mode, minimum and maximum, quartiles, range, interquartile range, sample standard deviation, variance, coefficient of variation, skewness and outliers, draws a histogram per column and exports the statistics as CSV, JSON or a Markdown table.
- Runs in your browser
- No sign-up
- Free to use
Processed entirely in your browser – your data is not uploaded. Files up to 50 MB.
How to use Column Statistics Generator
- Paste data or open a file.
- Choose columns (optional).
- Choose the export format.
- Copy or download the statistics.
Column Statistics Generator features
17 statistics
From count to skewness.
Histograms
Distribution at a glance.
Exports
CSV, JSON or Markdown.
Robust parsing
Thousand separators, missing values ignored.
All columns at once
Or the ones you choose.
Private
Runs in your browser; nothing is uploaded.
When to use Column Statistics Generator
- Quick analysis of exports.
- Reports and dashboards.
- Homework and teaching.
- Checking sensor or sales data.
Column Statistics Generator FAQ
Which standard deviation?
The sample formula (n − 1).
How are quartiles calculated?
Linear interpolation, like Excel’s QUARTILE.INC.
What is skewness?
A measure of asymmetry: positive means a long tail of high values.
Mean and median together
When the mean is far above the median, a few large values dominate – report the median too.
Private by design: your data is read and processed entirely in your browser with JavaScript. Nothing is uploaded to our server, so you can work with customer lists, exports and internal reports safely. Files up to 50 MB are supported; very large files depend on your device’s memory.
Input formats: paste or open CSV (comma, semicolon, tab or pipe – detected automatically), TSV or JSON (an array of objects, an object with a data, items or results array, or JSON Lines). The first CSV row is used as the header; JSON keys become columns, and nested values are kept as JSON text.
Missing values are recognised consistently across the data tools: empty cells and common placeholders such as NULL, N/A, NA, NaN, none, “-” and undefined. Types are inferred from the values – integer, decimal, boolean, date, email, URL, JSON or text – and columns with mixed types are flagged.
Related tools on this site cover the rest of a data workflow: the CSV cleaner, viewer, splitter and merger, converters between CSV, JSON, Excel and SQL, the JSON formatter and validator, and the other profiling, validation and statistics tools in this group.
Who it is for: analysts preparing data for a report, developers checking an API export or a database dump, marketers cleaning contact lists before an import, and students learning data quality. No account, no installation and no spreadsheet formulas are needed.