This video is available to students only

Types of data

We talk about the different types of data: the main buckets of qualitative and quantitative metrics, and their sub-categorizations.

Types of data#

Given a dataset, the first task is to determine the structure of the available metrics. Let's look at the first item of our weather dataset.

Our dataset

There are many different values here, but two basic types: strings and numbers. These two types can roughly be split (respectively) into two basic types of data: qualitative and quantitative.

Qualitative data (our strings) does not have a numerical value, but it can be put into categories. For example, precipType can either have a value of "rain" or "snow".

data type - qualitative

Quantitative data (our numbers) is numerical and can be measured objectively. For example, temperatureMax has values ranging from 10°F to 100°F.

data type - quantitative

Both of these types of data can be broken down even further.


This page is a preview of Fullstack D3 Masterclass

No discussions yet