Dataset buying guide · October 20, 2026
Unknown is not zero
An empty fee cell does not mean an event is free. An empty capacity cell does not mean a venue has no seats. Before calculating totals or filtering a purchased CSV, check how missing values are represented.
Four states worth keeping separate
- Known value: a source supports the number, including an explicit zero.
- Unknown: the fact has not been established.
- Not applicable: the field does not apply to this record.
- Conflicting: checked sources disagree; do not silently pick a value.
A worked example
These are fictional records, not event listings. Event A has a confirmed $50 booth fee and a confirmed $0 application fee. Event B has a confirmed $50 booth fee but an unknown application fee. Event C has a confirmed $50 booth fee and a $10 application fee.
A costs $50 in these two fee categories, B costs at least $50, with total unknown, and C costs $60. Replacing B’s missing application fee with zero falsely makes A and B equally priced. Other expenses are outside this example’s scope.
Ask for a field dictionary
Prefer separate value and status columns, such as application_fee_usd and application_fee_status. Leave an unknown numeric value empty; put its meaning in the status field. Document the unit, currency, source and check date. A blank alone cannot tell a buyer why information is absent.
Never use zero as a universal missing-value marker. Avoid placing strings such as “unknown” in an otherwise numeric column unless your import process explicitly supports them. Spreadsheet and CSV readers handle blanks differently: test your actual import rather than assuming a default.
Audit before computing
- Count records in each status, not just nonempty cells.
- Calculate a full total only when every required component is known.
- Label partial sums as lower bounds only when all omitted costs are nonnegative.
- Keep conflicts visible until resolved against a dated original source.
Download the fictional CSV example. For provenance, rights and coverage checks, use the six-question dataset buyer checklist.
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