https://www.r-bloggers.com/7-alternatives-to-word-clouds-for-visualizing-long-lists-of-data/
Creating a meaningful visualization from information alongside long lists tin hold upwardly challenging. While give-and-take clouds are oftentimes the pop choice, they are non ever the best option. This postal service illustrates 7 alternatives to give-and-take clouds that tin hold upwardly used to visualize information from long lists, each has its ain trade-offs. The visualization examples inward this postal service usage the gross domestic product of 185 countries together with are created using R.
The mutual option: Influenza A virus subtype H5N1 give-and-take (phrase) cloud…
This visualization below is a phrase cloud, showing the whole names of countries (i.e., phrases) rather than simply words. The size of each province inward the cloud is inward proportion to its GDP. While give-and-take clouds are oftentimes ridiculed, they produce scale well. Unlike close charts, a give-and-take cloud gets improve alongside the to a greater extent than things that it displays. But give-and-take clouds are far from perfect. The residual of this postal service explores around improve alternatives to give-and-take clouds.
circle packing algorithm to adjust the bubbles. This avoids the occupation that dissimilar give-and-take lengths convey to give-and-take clouds. However, despite their appeal, inward this case, the cure is worse than the illness. The small-scale size of the bubbles prevents writing inward the labels of all the countries. I accept to seat the names into tooltips which seem when you lot hover your mouse over the bubbles (click on the visualization to view). While I honey these plots, I am non a swell fan of tooltips for critical information. You can, no doubt, appreciate this quest if you lot access this from a mobile device or the R-Bloggers website, where the tooltips cannot hold upwardly seen unless you lot click on the visualization. While I honey these plots, I am non a swell fan of tooltips for critical information. You can, no doubt, appreciate this quest if you lot access this from a mobile device or the R-Bloggers website, where the tooltips cannot hold upwardly seen unless you lot click on the visualization.
interactive cartogram). Nevertheless, simply equally alongside including names inward tooltips (as done alongside the circle packing), this is a salvage rather than a cure. The IMF, who provided the information used inward this post, have created a nicer interactive cartogram if you lot desire to run across how to produce this better.
Click the picture for an interactive version
Alternative 6: Influenza A virus subtype H5N1 donut nautical chart (it does a surprisingly practiced job)
As I accept mentioned before, the hate that close numerate people accept of pie charts is non justified. To my mind, the donut chart below outperforms all the non-geographic visualizations examined together with hence far. Notably, it emphasizes aspects of the information non evident inward whatsoever of the other visualizations. For example, it allows us to run across that biggest 4 countries’ gross domestic product exceeds that of the residual of the world. If you lot are wanting to discovery information for 1 of the countries alongside a smaller GDP, you lot can, unfortunately, alone produce together with hence via tooltips.
Alternative 7: Grid of bar charts
I telephone outcry upwardly this concluding visualization a grid of bars. It consists of a serial of bar charts adjacent to each other. I accept created each of these charts using R. Then, I set them out together with added a heading inward Displayr. You tin produce this simply equally easily inward PowerPoint or whatsoever blueprint app. For a description of how I created it, run across my post A Beginners Guide to Using Functions to Create Chart Templates Using R.
This visualization is non pretty, but it is the alone visualization which manages to adequately convey the distribution equally good equally all the detail. Its alone existent technical limitation is that it tin hold upwardly difficult to discovery a specific province (which is less of a occupation inward the before geographic visualizations).
What accept I missed?
In this post, I accept shown 8 dissimilar ways of visualizing long lists of data. Do you lot know of whatsoever improve methods? If so, delight add together a comment.
Explore the visualizations yourself
You tin log into Displayr together with access the document used to create each of these visualizations here (just sign inward first). To run across the R code, click on a visualization together with the await in Properties > R CODE on the correct of the screen.
Acknowledgements
The bubble charts alongside circle packing usage Joe Cheng’s bubbles package. The cartogram, choropleth, horn of plenty, together with grid of bars use plotly. The treemap uses canvasXpress.