Page Comparison

Module Overview

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• The Quartz Guide To Bad Data
• Tidy Data – although the principle of tidy data stems from an R developer and the examples in this document are made in R, "tidy data" is a very valuable standard that you should achieve when working with data. Once your data is "tidy", visualization in R (or in any other language / framework) becomes easier. You can also look at the more formal and less R-heavy scientific paper.
  

Data formats / conversions

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• https://regexr.com/: Interactively test and learn Regex
• This tutorial doesn't look too bad: Learn Regex the Easy Way

Geospatial data

• An overview of common spatial data formats
• QGIS is an open source geographical information system and a good option for working with geodata on a non-regular basis (e.g. to look at some data or to compute areas of some regions). This tutorial collection will introduce you to it.
• https://tools.retorte.ch/map/: Convert coordinates into/from the Swiss projection system.
• Municipal boundaries and districts of Swiss cities by the BFS. Jeremy Stucki (former IAD student) has processed these and other data into TopoJSON (easier to use for web applications).

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• Data Analysis with R: Recent and good introduction, no prior knowledge needed
• rddj.info: Resources for doing data journalism with R

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Calendar

TG: Timo Grossenbacher, BW: Benjamin Wiederkehr, JG: Joël Gähwiler

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