Scan barcode
bsweezy's review
3.0
This book is basically a manual for the "Processing" engine for displaying custom graphs and charts. This is helpful for me because it's time I get confortable with breaking away from Excel and friends.
tdrapeau's review
3.0
Visualizing Data explores data visualizations through the Processing Environment, a Java-based IDE used as a sort of visual sketchpad to plot out visualizations without heaps of Java code. The author, Ben Fry, is well schooled - PhD from the Aesthetics + Computation Group at the MIT Media Laboratory, the 2006-2007 Nierenberg Chair of Design for the Carnegie Mellon School of Design, amongst other achievements. Fry stresses the 7 stages of visualizing data:
Acquire -> Parse -> Filter -> Mine -> Represent -> Refine -> Interact
He spends a significant amount of time talking about how each individual data set you might encounter and need to visualize is inherently different than others, or needs to be seen that way in order to grok something truly interesting out of it.
I found the visualizations to be on the simple side, and several chapters to be pretty much irrelevant as I have a programming background. However, I found his approach to be refreshing, really concentrating on the data at hand, and coming up with custom built visualization exercises that showed great attention to the actual data at hand.
There are definitely useful patterns here: Mapping, Time Series, Connections/Correlations, Scatterplot Maps, Trees, Hierarchies, and Recursion, Networks and Graphs. The 2 chapters on bringing in data, "Acquiring" and "Parsing", are decent beginning points, but much more data is needed to build robust visualizations based on disparate internet data sources.
All in all, it was a good read. In today's Web 2.0 world, a book like this brings very interesting possibilities, with the wealth of personal preference/friend/activity data available for free via the internet.
Acquire -> Parse -> Filter -> Mine -> Represent -> Refine -> Interact
He spends a significant amount of time talking about how each individual data set you might encounter and need to visualize is inherently different than others, or needs to be seen that way in order to grok something truly interesting out of it.
I found the visualizations to be on the simple side, and several chapters to be pretty much irrelevant as I have a programming background. However, I found his approach to be refreshing, really concentrating on the data at hand, and coming up with custom built visualization exercises that showed great attention to the actual data at hand.
There are definitely useful patterns here: Mapping, Time Series, Connections/Correlations, Scatterplot Maps, Trees, Hierarchies, and Recursion, Networks and Graphs. The 2 chapters on bringing in data, "Acquiring" and "Parsing", are decent beginning points, but much more data is needed to build robust visualizations based on disparate internet data sources.
All in all, it was a good read. In today's Web 2.0 world, a book like this brings very interesting possibilities, with the wealth of personal preference/friend/activity data available for free via the internet.
More...