Composite Data Types

Building upon scalar data types, we also have composite data types in data science. A composite data type is a logical container used to organize related data. It contains a set of scalar data types organized in a specific way. Composite data types allow us to store and access information effectively. They provide methods for accessing individual scalar values and performing operations on groups of scalar values. In addition, composite data types provide context to related data which (as we discussed previously) is used to create information. You can think of a composite data type as a container that holds a collection of related data in a specific way. There are several types of composite data types that we encounter in data science. They can be grouped together in various ways. However, to keep things simple, we’re going to organize them into the following four groups: – Homogenous data types – which require all data to be of the same data type – Tabular data types – which store data in tables. – Semi-structured data types – which store data as a set of relationships And multi-media data types – which store data for images, audio, video, and more. Let’s take a look at a few of the most common composite data types we encounter in data science.