In query editor, ever notice that the column data type menu includes four options for numbers: Decimal Number, Currency, Whole Number and Percentage? In this series, we’ve only talked about one numeric type: type number. Are there types we’ve missed?

Behind the scenes, menu item Decimal Number maps to type number, Currency to Currency.Type, Whole Number to Int64.Type and Percentage to Percentage.Type. If you look at the names defined in your Power Query environment, you’ll likely see a host of other “Type” names, including Int8.Type, Int16.Type, Int32.Type, Single.Type and Double.Type. What are all these “Type” names—even more types we have yet to cover?!

Nope! Introducing type facets.

Power Query’s type system helps us understand the values we works with, allows us to describe the kinds of data expected by functions we write, offers a means to share documentation (which IntelliSense can display) and provides a mechanism to inform consumers about the structure of the data we’re handing them (which the host environment can use—for example, guiding Power BI to correctly set column types).

To sum up M’s approach to types at a high level:

Every value has a type. A type is itself a value. Types are used to classify values.

A simple statement, but with a lot packed into it and behind it—so much, in fact, that we’ll explore Power Query’s type system in over several posts. Today, we’ll start with the basics, centered around what are known as nullable primitive types. Later, as we get deeper in, hold on to your hat—you might find a major puzzling surprise, where the type system doesn’t work the way you’d expect.

Let’s start delving into the type system by examining the summary statement we read a moment ago.

You might be inclined to skip learning about list and record and jump directly to table. After all, as far as types that hold other values go, you mostly work with table. A table’s data is made up of simple values, so it makes since that you learned about them (parts 6, 7, 8 and 9). However, list and record might feel like types you won’t normally use, so why not skip them?

Turns out, a table behaves in ways like both a list and a record. If you want to leverage all that table offers, learning about these types is foundational. Besides, as you work with M, you just might find that list and record are more useful in their own right than you first thought.

Oh, did I mention that there’s a surprising relationship between let expressions and type record? All the more reason not to skip over it!

Time to finish up our exploration of primitive, single-value holding types! We’ll learn about handling true and false, explore the oxymoron of null (a value that represents the absence of a value) and touch on binary.