A field name is often an abbreviation for a longer idea. Different readers may interpret “active,” “complete,” or “value” differently unless the rule behind the field is written down.

Create a small data dictionary with the meaning, unit, allowed format, and important exclusions for each column. Include an example where it helps. The description should reflect the actual collection process, rather than an ideal definition no one follows.

Update the dictionary when a field’s meaning changes. A historical table may need the earlier definition preserved too. Clear column definitions make analysis, sharing, and future corrections easier to discuss.

Picture this situation.

Consider handing over a table with a special code for unavailable values. Explain that code before someone mistakes it for an ordinary measurement.

A second way to look.

Show a reader how to question the result. A date, an explanation of coverage, or a visible range can make a chart more useful than extra precision.
A few starting points
  1. Define the rule behind each field.
  2. Include units and important exclusions.
  3. Keep earlier definitions when the meaning changes.

Follow a related question

Show a small input and expected result.

Instructions with an example

Separate claims, calculations, and proposed wording.

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Related background to continue exploring this subject.

W3C: a primer for tabular data RFC Editor: the CSV format
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