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Reading a dataset card

The questions to answer before you download anything.

10 min 3-question quiz 3 guides to read next

A dataset card is the documentation that comes with a dataset. Every dataset on this hub has one, and reading it first saves hours later. Open the Adult census income card and look for answers to these questions:

  1. What is one row? Here, one person from the 1994 US Census.
  2. Where did it come from, and when? Data from 1994 describes 1994. A model trained on it knows nothing about incomes today.
  3. What does each column mean, and in what units? Is fnlwgt a weight in kilograms? (No — it is a census sampling weight.)
  4. How are missing values written? In this dataset, as ?. Elsewhere you will see blanks, NA, -999 or ***.
  5. Are there quirks? The card warns that adult.test starts with a comment line and that its labels end in a full stop.
  6. What is the licence? CC BY 4.0: you can reuse it, including commercially, as long as you credit the source.

Look before you load

Use the Data viewer tab to see the first rows of a file. You will spot things no documentation mentions: the wine quality CSVs are separated by semicolons, not commas, and the GISTEMP file has a title line above the header.

If a dataset has no card, no licence or no clear source, treat that as a warning sign rather than an inconvenience.

Check your understanding

3 questions · pass with 2 correct

1. The Adult census data is from 1994. What does that tell you?
2. How are missing values written in the Adult dataset?
3. A dataset has no card, no licence and no clear source. What should you do?

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Further reading

Guides that go deeper on this lesson.

  • How to Read a Dataset Card

    The questions a dataset card should answer — what one row is, where the data came from, its licence and its quirks — before you use it.

    1 min read

  • Datasheets for Datasets

    A structured way to document how a dataset was created, what it contains and how it should be used.

    2 min read

  • Finding Open Datasets

    Where to find reliable public datasets for learning and projects, and how to judge whether a dataset is suitable.

    1 min read