Scalar Data Types

The most basic building block of data in data science is a scalar data type. Scalar data types store a single unit of data. This can be a letter, a number, a date, a time, or something else. We refer to them as scalar data types because a scalar variable in mathematics can hold one and only one value at a time. Scalar data types are also the most basic unit of storage for data in a computer. Everything from a small text document to a giant distributed database are composed of these single units of storage. Scalar data types provide a set of operations that can be performed on the data they contain. All of the processing that occurs in a computer is essentially the result of these operations being executed on scalar data types. There are several scalar data types commonly used across various computers, programming languages, and data-science tools. The most common data types you will encounter in data science can be divided into three main groups: – categorical data types, – numerical data types, – and Temporal data. Let’s take a look at a few of the most common scalar data types we encounter in data science.