Category: Visualization

Andy Kirk spots a few interesting uses of slope graphs:

As somebody who tries to consume as much visualisation work as possible, I always get a little extra joy from seeing clusters of the same techniques emerging. One such recent trend has been the use of simplified slope graphs.

By ‘simplified’ I mean they are stripped right back to a simple function of just showing the direction of change between two points in time, there are no axes and no other chart apparatus, just the trends.

I’m kind of iffy on it. I do like the map showing behavior of states over time, but the first visual had too much going on and the third visual had too much whitespace for my taste.

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Cole Nussbaumer Knaflic has some alternatives to circling an item you want people to notice:

You’ve seen it before: a circle on a slide or graph that is meant to highlight something of note. People tend to be surprised when I express admiration towards this approach. I love that it means someone took the time to consider the data and the viewer and thought, “I’d like people to look here” or “I want to make sure my audience doesn’t miss this.” Then they took an action—adding the circle—to help ensure it.

That said, the circle is a blunt tool. It’s better than nothing: if you are facing such a time constraint that you don’t have a minute to spare for anything beyond quickly adding a circle, do it. If you do have more than a minute, however, there are other eloquent solutions you can employ. This will typically involve making changes to how you design the way the data or supporting elements are formatted.

Cole then lists out several alternatives. When I circle (or wrap with a rectangle), it’s usually one of two scenarios: either I’ve just grabbed a screenshot (or have frozen the screen in ZoomIt) and that’s my primary tool available, or I’m working with a pre-generated image and can’t change it. But when you have a chance to alter the base graph or image, Cole has several excellent techniques to make certain items stand out in contrast to others.

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Alex Velez describes the nature of the scatterplot:

A scatterplot is a niche chart, but it’s one of my favorites! If you are a statistician or work in a technical field, a scatterplot might be your go-to graph type. However, if you don’t perform a lot of statistical analysis, then these charts may be unfamiliar. Regardless of your current comfort level, scatterplots are extremely useful to focus on the relationship between two series—a scenario that is common in both technical and non-technical fields. Let’s explore some of the basics of scatterplots via an example; I’ll also cover tips for designing more effective ones and discuss common variations (bubble charts, connected scatterplots, etc.), too!

Read on for a good explanation of what scatterplots are, variants on the theme, and when they make sense to use.

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Artyom Keydunov takes us through integrating D3.js within Cube.js:

You can check the online demo of this dashboard here and the complete source code of the example app is available on Github.

We are going to use Postgres to store our data. Cube.js will connect to it and act as a middleware between the database and the client, providing API, abstraction, caching, and a lot more. On the frontend, we’ll have React with Material UI and D3 for chart rendering. Below, you can find a schema of the whole architecture of the example app.

D3 is a powerful visualization library in Javascript, though I’ve found that it’s a complex visualization library.

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Elizabeth Ricks dives into the properly-maligned pie chart:

I want to use a pie: how do I make a good one?

When using pie charts, here are a few quick design tips to make them more effective.

The best way to make a good pie chart is not to make a pie chart…

Elizabeth does a good job of being less dogmatic than I am on the topic while still explaining most of why I dislike pie charts so.

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Mike Cisneros has some guidance around color selection when designing visuals:

Regardless of how you select it, this key color will be used to denote the data points, or the data series, on which you feel it is the most important for your audience to focus.

All of the other colors we use will be based on where they are on the color wheel in relation to this key color, how many colors we intend to use, and what kind of relationship the rest of the data has to the data represented by the key color. 

I’ll admit that I just reach for the pre-created palettes which have done the work for me already.

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Shannon Holck gives us several scenarios in which tables are a good choice of visual:

Exact numbers are needed
If your report goes to a customer and you need an exact quantity or price or total, absolutely, a table is likely needed.

Displaying a few discrete values
If you need to display 5-10 things and they all represent unique values, a table may be appropriate.

Need to establish trust in the data
If you don’t trust the data (yet) and want to verify data, you can sometimes compare data at a roll-up level to a known source.  This is a great way to test not only the data but that the calculations are accurate.  

Click through for more reasons, followed by cases in which you want to avoid table visuals, and finally a few ways to improve tables. I’m not the biggest fan of the improved tables (because I want simpler and denser), but this is good food for thought.

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