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1

"We want to show the improvements in the students who have pre- and post-test data." If that is the ultimate aim of this graph, to show the difference over two tests, then there's no point in graphically showing those who've taken only one part of the test or none of the tests - these can be summarised in a corner/outside the chart with some text (i.e. not ...


0

The best tip about designing graphs that I can provide is to have a very and simple message that you can see from looking at the visual representation of the data, otherwise it defeats the purpose of clarity in communication and becomes a visual design exercise. Having too much information often means you have to look at other graphs anyway because it is ...


2

The problem is that you have to fit 3 series of data within one simple chart. I would suggest something along these lines: You display the number of participants as bars, but the success rate is the filling of a bar. Also you may check ds3.js. They have lot's of ideas on visual representation of complex data.


4

First picky point: Infographics aren't the same as visualisations. https://eagereyes.org/blog/2010/the-difference-between-infographics-and-visualization The point of visualisation is to shift processing from the cognitive to the perceptual - i.e. don't think about it, just see it. There's hundreds of papers that compare different visualisations in user ...


3

It sounds like your question is two-fold. Here's my refinement: "What are best practices for data visualization to optimize for memorability and comprehension?" In short, the two are at odds. Complexity and visual noise typically make data visualizations more memorable but less comprehensible. I've included a more thorough breakdown below. Memorability ...


0

Department stores change floor and fixing colours to subtly change the mood of a shopper, for example when transitioning from clothing to a food department. So I agree in principal, executed with the right subtleties your concept could work. Without seeing the project, maybe keep core background colours so as not to completely throw the users eye… but change ...


4

Use the right visualization Pie charts represent constituents of a whole. As you've discovered, this doesn't work when numbers can go into the red. Use bar or line charts for more flexible (and arguably more informative) visualization.


4

An inner ring showing liabilities and an outer one showing assets with the ratio of their thickness's set by the ratio of the total liabilities to assets. (Don't comment on the ugly colours, just a picture to help explain what is in my head) But I think in general that a pie chart is probably not the best choice for representing such data.


1

If you want to make these statistics visible to motor vehicles I would take a page from the US Forest Service which already implemented a very similar scale for signs warning of risk of forest fires: You can of course include the numbers and labels but what really matters is where the current level is pointing into relation to the scale of values and ...


1

Given that you want people to recognise what it is from vehicles - you need to have one icon that is instantly recognisable as air quality. Then combine it with the colour and number, or possibly easiest to show is the opposite - air pollution. The noun project has lots of icons for pollution Icon credit: Amelia Wattenburger Update - here's another ...


2

I would suggest a series of simple smiley face graphics for the rating. Advantages: Instantly recognizable No problem for color blind people. More likely to stand out as unique in a street setting. Something based on green/yellow/orange/red colors would be competing with many other signs and lights that use these colors to communicate information. If ...


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If you want to get something up and running quickly, include a win/loss percentage to quickly size up the competition.


3

There are a few pre-made category color sets for Datavis, made by Mike Bostock, that go up to 20 colors: However, in my POV they are not very interesting aesthetically, so if you are into a custom or advanced color work, you could try the ColorBrewer by Cynthia Brewer, as @icc97 said.


3

If you want to visualize just the total wins and losses any simple chart or table will do. If you want to visualize the progress throughout the season though, what you have is similar to Edward Tufte's sparklines visualizing wins and losses using simple icons. The stars work ok, but it takes a bit more work to distinguish between wins and losses. Here ...


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You can use green color for the wins and red color for the losses. I think users are most accustomed to this pattern. You can also use win percentage after the number of games has reached certain ammount.


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In that have you tried mega-menu https://s-media-cache-ak0.pinimg.com/originals/3a/29/3d/3a293db3ac85d0facc63b3af77af2a33.jpg


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How about a use of trophies displaying the number of wins and losses?


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No, and in fact most of the default colour palettes of standard applications are not particularly suitable because it is difficult to take into account the number of datasets you are going to plot or display. However, there are a couple of strategies you can consider when you are going to be working with a very large dataset (with many data series): ...


3

The main problem with nested menus is that as UI objects they are somewhat feeble. Their task is to appear for a short period of time and disappear once user made a selection. From this perspective, asking user to select multilayered menus is an awful task as menus tend to disappear on a wrong move of the mouse. I think a better option is to make nested ...


7

color brewer is designed for maps but it will give you colours that are optimised to be as differentiable as possible. It has a maximum of 12 colour classes


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There is no standard list, but there are rules how colors come together or contrast. I use Paletton when I have any questions or doubts about colors. There are plenty of options there to research and experiment. I think it might be a good starting point for your list.


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Consider providing the ability to easily sort the list by either "Invoiced Amount" or "Days Past Due", in addition to providing both data points on each line item. This empowers users to push the items they are most interested in to the top, instead of scanning the entire list searching certain icons, colors, or number ranges. As a starting point, given the ...


1

I think one needs to address the question of what is being conveyed through the graph. If you want to point to certain interesting observations, marking them, or generating separate graphs to highlight the same might be one way to catch the attention. While such graphs look visually appealing, the process of generating insights might prove to be ...


6

Oooh, pretty. Yeah, well, hairballs (this kind of huge graphs you have shown) are pretty much useless because unreadable. Genomicists and bioinformaticians have discovered this early in the days because their datasets are big enough to demonstrate the issue. And no, adding 3D will not help the cause. The solution for hairballs are hive plots. Also ...


2

Disclaimer: Very random ideas from a non-specialist What would you recommend to use to avoid data overload with large graphs? I would look at successful visualizations of large graphs. Here's a few: http://internet-map.net/: it's easy to see the central points and the clusters. Also easy to see individual points. ...


1

Since we're talking about lists the closest analog is folders. Something like this may work:


3

Your choices beyond the existing pan/zooming on the display could be to introduce a local focus+context lens around the mouse pointer, to unclutter/expand the current area of interest. However with the size of datasets you're mentioning you might need to consider aggregating and/or filtering on the data itself - a million node graph on a million-pixel ...


0

Cramming 3 variables into the map is really not the best solution — it will most likely not be readable. This being said, it can still be done. You could combine a bivariate map from Harshit's answer with this, adding a third dimension for one of the variables.



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