![]() ![]() the resulting chart, in a commercial environment? What is covered by the license is just the re-use of the javascript library in a website, not the resulting chart. Now what if we only need the end-product, i.e. there is a commercial license for any other website.there is a first Creative Commons Attribution-NonCommercial 3.0 License: you can use the library for your non-profit website (see details on the licensing page).The only negative point imho is that it is dual-licensed and all cases deprive you from your freedom: ![]() This library can produce beautiful charts of various types with some Ajax interaction. In one of his buzz, Cédric Bonhomme drew my attention on the Highcharts javascript library. But I find this presentation really more appealing and meaningful than the stacked bar graph. Of course, if your criteria for “sexiness” is that there shouldn’t be any digit on your chart, then this chart is not sexy. In addition to the graph above, one can notice there isn’t any severity levels A, B, F and G represented and we can quickly grasp the proportions between the different incidences. You still see where the incidence is the highest (in age ranges 4 and 5), what levels of severity are the most important (C, with lower but approximately similar levels of D, E and H). You just format the table nicely and add some colour gradient. Actually everything was already in the table. If one wants to clearly display both the whole and its parts, Steven Few recommends to either use two graphs next to each other or a combination bar and line graph (with two quantitative scales).Īs I’m not really interested in the whole but mainly in the parts and their relative distribution, I suggest another way to present the data. And that this type of graph shouldn’t be used if the distribution changes must be shown more precisely. Inside, on pages 135-136, one can read stacked bar graphs are the right choice only when you must display multiple instances of a whole and its parts, with emphasis primarily on the whole. This reminded me I read a book written by Steven Few, a few years ago: Information Dashboard Design (O’Reilly Media, 2006). And Steven Few also participated in his forum here. Then in a post on Junk Charts, someone mentioned Steven Few who would have said “not to use stacked bar charts because you cannot compare individual values very easily and as a rule avoid stacked bars with more than six or seven divisions”. I looked on the web but couldn’t find much information apart from the fact “ The Economist says they’re so bad at conveying information, that they’re a great way to hide a bad number amongst good ones” (but are still using them in their graphic detail section) or “ a stacked column chart with percentages should always extend to 100%” (this doesn’t really apply here). (it’s even worst when some age ranges don’t have any incidence at all: what is happening?).how can we compare levels C, D and E in age ranges 4 and 5?.what are the different levels of severity in age ranges 1, 2 and 3?.The chart shows that the disease especially affects age ranges 4 and 5, at different severity levels. That incidence is split by 8 severity levels. The chart shows the incidence of disease X in various age ranges. While in the past I may have used graph paper and a ruler, nowadays it only takes a few minutes to extract the information.This afternoon I received a bunch of data accompanied by stacked bar graphs for each dataset. GITIZE HUNDRED GRAPH ENGAUGE DIGITIZER SOFTWAREHere is another reason why I should make the data available: Because it is easy to extract the data from a chart anyhow, thanks to digitizing software like the Java application plot digitizer. ![]() Global property catastrophe rate on line index Screen shot of plot digitizer using Guy Carpenter’s In most cases users don’t want to see and read the code, but having the knowledge that they could provides more credibility. This might be similar to open source software. Pretty pictures give you the attention, but the underlying data will offer you an opportunity to engage with your reader on a different level. I personally believe that when I show a chart I should also make the underlying data available. to generate leads, as potential customers may get in touch with you asking for the underlying data, or technology issues that don’t allow you to upload data, etc. Of course there are perfectly valuable reasons for only displaying a chart and not making the underlying data available, e.g. What I really like about the Guardian’s approach in particular is that they share the data of their articles and encourage readers to use it. I had mentioned the Guardian’s data blog and the need for more data journalism earlier here. ![]()
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