By Graham Wills
Art, or technological know-how? Which of those is the best way to consider the sphere of visualization? this isn't a simple query to respond to, even in case you have decades adventure in making graphical depictions of information in an effort to support humans are aware of it and take motion. during this e-book, Graham Wills bridges the distance among the paintings and the technological know-how of visually representing information. He doesn't easily provide principles and recommendation, yet bases those on basic ideas and supply a transparent course among them
This publication is anxious with the graphical illustration of time facts and is written to hide more than a few diverse clients. A visualization specialist designing instruments for exhibiting time will locate it helpful, yet so additionally should still a financier assembling a document in a spreadsheet, or a scientific researcher attempting to exhibit gene sequences utilizing a advertisement statistical package.
Read or Download Visualizing Time: Designing Graphical Representations for Statistical Data PDF
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Extra resources for Visualizing Time: Designing Graphical Representations for Statistical Data
It does a reasonable job of showing that the leagues are pretty similar in any given decade, but rather than focusing on the heights and widths of the symbols, the immediate impression is of the changing aspect ratio of the rectangles, from short and wide to tall and narrow, indicating that as time progresses, we have fewer hits overall but more big hits. If that was the message to be conveyed, then the chart does work, but if it was to show changes in each variable individually, then the chart is a failure.
If the data are irregularly spaced on the x dimension, this allows the window to adapt to the relative density, so that sharp changes are possible in high-density regions, but low-density regions, for which less information is available, do not exhibit such variability. Window centered or not: Generally, if we want to predict at a given location, we choose a window of values centered on the value we want to predict. ” A more advisable plan is to use a window that only calculates values to the left of the location where we want to predict.
On the left we highlight cases where players average more than one home run every ten games using a color aesthetic where red indicates a high home run rate. 5 runs per game using shape. Seasons generating lots of runs are shown as circles, the others as crosses Size is a composite aesthetic that can be expressed as a mixture of interrelated nonorthogonal aesthetics – width, height, depth, aspect, area, volume – and if you try to use one parameterization (in this example, width and height), then you may end up with a visualization for which another parameterization is most visually prominent – aspect in the example.