December 2017
Beginner to intermediate
168 pages
3h 53m
English
Content preview from Making Data Visual
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Chapter 4. Components of a Visualization
The previous two chapters outlined the process of refining a question into tasks. Chapter 2 broke each task down into components: actions, objects, measures, and partitions. These terms help identify where and how to turn fuzzy tasks into specific, actionable ones. Then, Chapter 3 discussed in more detail how to solicit the use scenarios and user stories that motivate the decisions made about proxies during operationalization.
The process in Chapter 2 concluded with a well-operationalized task and promised that this can lead to a visualization. But it did not discuss how to translate an operationalized task into a visualization. There is one step left before we can start doing visualization: we must understand the data..
This chapter takes the first step to translating these descriptions into visualizations. Understanding the characteristics of the data will make it easier to select an appropriate visualization. Chapter 5 then describes specific visualizations to match the data characteristics outlined here—more specifically, its dimensions and measures, how it is grouped and aggregated. In Chapter 6, we’ll look at how views can be combined to support rich, dynamic analysis of complex tasks and data.
Dimensions and Measures
The attributes of the data serve particular roles in a task. A dimension is an attribute that groups, separates, or filters data items. A measure is an attribute that addresses the question of interest and that the ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.