Reading the summary
- filled — cells that are not empty. Compare with the row count: a column filled at 12% is probably not usable as is.
- distinct_values — number of different values. Equal to the row count: an identifier. Very low: a category you can group by. One: a useless column.
- min_value / max_value — for numbers and year-first dates, the range. A price at -1 or a date in 1900 is an error to fix before analysis.
Go further on one column
Most frequent values:
SELECT status, COUNT(*) AS rows
FROM data
GROUP BY status
ORDER BY rows DESC
LIMIT 20;
Average, total and spread of a numeric column:
SELECT COUNT(amount), AVG(amount), SUM(amount), MIN(amount), MAX(amount)
FROM data;
Rows where a required field is missing:
SELECT * FROM data WHERE customer_id = '' OR customer_id IS NULL;
A note on text columns
For text, minimum and maximum are alphabetical (A before Z). They're still useful: an unexpected value such as a leading space or a number in a name column tends to show up at one end.
Other free CSV tools
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Frequently asked questions
How are column types detected?
From the first 1,000 rows: a column is numeric if every non-empty value is a number. Identifiers longer than 15 digits are kept as text so they don't lose precision.
Can I export the summary?
Yes, the summary is a regular result: download it as CSV or JSON.
Does it work on very wide files?
Yes, one summary row is produced per column; very wide files (hundreds of columns) just take a bit longer.