O'Reilly logo

Data Wrangling with Python by Katharine Jarmul, Jacqueline Kazil

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Chapter 3. Data Meant to Be Read by Machines

Data can be stored in many different formats and file types. Some formats store data in a way easily handled by machines, while others store data in a way meant to be easily readable by a human. Microsoft Word documents are an example of the latter, while CSV, JSON, and XML are examples of the former. In this chapter, we will cover how to read files easily handled by machines, and in Chapters 4 and Chapter 5 we will cover files made for human consumption.

Note

File formats that store data in a way easily understood by machines are commonly referred to as machine readable. Common machine-readable formats include the following:

  • Comma-Separated Values (CSV)

  • JavaScript Object Notation (JSON)

  • Extensible Markup Language (XML)

In spoken and written language, these data formats are typically referred to by their shorter names (e.g., CSV). We will be using these acronyms.

When looking for data or requesting data from an organization or agency, the formats described in this chapter are your best available resource. They are more easily used and ingested by your Python scripts than human-readable formats, and are usually easy to find on data websites.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required