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new data viz and py 2 or 3 resources
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content/pages/01-introduction/04-python-2-or-3.markdown

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progress so the engineers could better estimate the scope of work when
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the transition from 2 to 3 became critical to their development toolchain.
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* [Zato: A successful Python 3 migration story](https://zato.io/blog/posts/python-3-migration-success-story.html)
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examines the background, preparation, execution and testing of moving
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an existing Python 2 code base over to Python 3.
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* [Why Python 3?](http://whypy3.com/) randomly outputs valid reasons to
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use Python 3 over 2.x.
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content/pages/02-development-environments/10-powershell.markdown

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* [PowerShellBuild](https://github.com/psake/PowerShellBuild) provides common
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reusable tasks for building PowerShell modules.
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* [Invoke-Build](https://github.com/nightroman/Invoke-Build) is a build
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automation tool. There is also extensive documentation on their
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[wiki](https://github.com/nightroman/Invoke-Build/wiki).

content/pages/03-data/18-data-visualization.markdown

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and scroll through to learn a ton about the details you can think about
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when creating these types of data visuals.
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* [Optimized Brewery Road Trip, With Genetic Algorithm](https://flowingdata.com/2019/02/08/optimized-brewery-road-trip-with-genetic-algorithm/)
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shows how a heuristic solving approach such as a genetic algorithm can be
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used to handle a version of the Traveling Salesman Problem (TSP), but
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with the more fun Top 100 American brewery locations.
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### Data visualization resources
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* [Data visualization, from 1987 to today](https://medium.economist.com/data-visualisation-from-1987-to-today-65d0609c6017)
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and the output they created along the way, including the open source
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tools [react-vis](https://uber.github.io/react-vis/) and
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[react-map-gl](https://uber.github.io/react-map-gl/).
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