How to Pick the Right Chart for Your Data
Lesson 23 from: Data Storytelling: Deliver Insights via Compelling StoriesBill Shander
How to Pick the Right Chart for Your Data
Lesson 23 from: Data Storytelling: Deliver Insights via Compelling StoriesBill Shander
Lessons
Introduction
1Class Introduction
03:29 2Do The Exercises
00:37 3Communication Challenges and Solutions
05:20 4Exercise: 4X4 Model
04:31 5Exercise Solution: 4X4 Model
03:25 6Introduction - Quiz
Thinking Like a Communicator
The Power of Story
06:48 8Six Ways to Tap Into Your Inner Storyteller
12:32 9The Importance of Understanding Your Audience
03:42 10How to Understand Your Audience
04:35 11How to Embrace Emotion (to review)
04:38 12How to Tap Into Your Inherent Creativity
05:55 13Exercise: An Emotional Story
01:29 14Exercise Solution: An Emotional Story
01:12 15Thinking Like a Communicator - Quiz
Telling Data Stories
16Basic Data Analytics Tactics
08:54 17Basic Journalism Tactics
04:56 18Defining Your Story
05:37 19Sketching and Storyboarding
07:05 20Use Your Words
04:20 21Telling Data Stories - Quiz
Essential Design Principles
22The Power of Visuals
07:44 23How to Pick the Right Chart for Your Data
05:19 24Exercise: Chart Selection
06:27 25Exercise: Visualization
02:59 26Basic Chart Designs Principles
08:21 27Research Driven Design Principles
06:27 28Exercise: A Data Story
03:50 29Essential Design Principles - Quiz
And Now What?
30Great Data Stories for Your Inspiration
05:53 31Tips and Tricks
03:53 32How to Sell Data Storytelling Services
03:56 33A Conversation Guide for Talking to Prospects About Data Storytelling Projects
05:30 34Course Summary
02:48Final Quiz
35Final Quiz
Lesson Info
How to Pick the Right Chart for Your Data
data storytelling requires visual storytelling, which is what we think of as charts and graphs. So how do you know what's the right chart for your data? Let me start by saying there is no right chart for your data. There are myriad ways of creating a visual representation of any data and many times it's not clear what is the best or right way. But there are certainly charts and graphs that will do a better job than others at expressing exactly what you're trying to say with your data in the end, the most important thing to consistently come back to is what you're trying to accomplish with your chart. I refer to this as Core wits this is a fundamental idea that I can't believe I haven't mentioned yet. It's usually one of the first things I teach. So please think about this one and tuck it away in your long term memory. Horowitz is a terrible but very important acronym that stands for No what you really want to say, this is the most important thing. You can revisit every step along the w...
ay of any communications project. You can't communicate anything in any way to anybody If you don't know what you're actually trying to say. This is about being strategic in your communications, you have to know your message and then you can formulate your messaging, picking a visual form for your data is all about Core wits, you have to know what aspect of the data you're communicating and why before you can pick your chart, there are a bunch of ways to think about this. I can't possibly summarize every scenario in this lesson but I'll share a few ideas to illustrate what I'm talking about. Say you have three sets of data and let's say its stock price data, it seems like a random collection of numbers. If I were to ask you to tell me the best chart to visualize this data, what would you say I do this exercise in my data storytelling and visualization workshops. And almost invariably people say bar charts or line charts first. Why is that? I think it's because they're the two most common forms of data visualization and yes you can do bar charts of this data for instance a group bar chart showing every value for all three datasets or you can do a line chart of this data as well. But what is each of these telling us and how do we know which one's better and why are people so quick to answer that question? Without pushing back on the question itself. The right answer to my question, demanding how to visualize that data is to ask me for my Corporates. What am I trying to say? What is the point of the data, what needs emphasizing or pointing out? For example, if we wanted to emphasize the volatility of one compared to the others over the entire time period then yes. Line charts might really be a great idea. Line charts by the way are one of the most effective ways to communicate time series data. People are used to looking at data over time this way And in fact research has shown that when people see a line they think about trends, they can see the same data in a series of bars nearly the same idea, but they will think of the bars as revealing individual values whereas the lines reveal trends. But what if the point was about volatility, but I wanted to narrow in on the story a bit. I just want to show you the entire relative price spread over time. Not every data point along the way. I could have shown you the data like this, just the highest and lowest amounts for each of the three datasets. Or maybe the data itself can be thought of as something that can be used to drive some other information. Maybe the story I want to tell is about the long term performance of the stocks without looking at volatility. I'm a broker recommending that you invest and hold. Maybe then I want to share the total returns of the three stocks over the entire time period. That's one number for each. So you can visualize that in a number of ways as bars or even just numbers right? What if I wanted to tell a story about when the three stocks peaked, then maybe it's a line But the line itself is downplayed and it's all about emphasizing those peaks or maybe it's all about when they crossed some magical threshold pricing, in which case the emphasis is made in some other way. As you can see, I'm not just talking about picking the right chart but about how to use that chart, what design methods to employ to bring out the aspects of the data that relate to the story I'm telling. If you constantly push yourself to think about your correlates to avoid thinking about what chart should I use and instead of thinking about what am I trying to say about this data and what will help people make better decisions with this data? The easier it will be to get to a visual approach that will work beyond that. I strongly recommend you look for examples and inspiration out in the wild if you peruse the hashtag data, viz on twitter or check out the subreddit data is beautiful or look at the examples page on d three Js dot org. You'll often quickly find projects where people are sharing data that looks and feels like your data and you can see how they've handled similar challenges, which might lead you to interesting options for your own visualizations for your data story. Once you've figured out how to visualize your data, you have to actually do it in the next video. We'll talk about basic chart design principles
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