Category Archives: Links

How an internet mapping glitch turned a random Kansas farm into a digital hell →

Interesting read about what can happen if you use a technology – IP addresses in this case – for something completely different than it was meant to:

For the last decade, Taylor and her renters have been visited by all kinds of mysterious trouble. They’ve been accused of being identity thieves, spammers, scammers and fraudsters. They’ve gotten visited by FBI agents, federal marshals, IRS collectors, ambulances searching for suicidal veterans, and police officers searching for runaway children. They’ve found people scrounging around in their barn. The renters have been doxxed, their names and addresses posted on the internet by vigilantes. Once, someone left a broken toilet in the driveway as a strange, indefinite threat.

The title is a little bit misleading – it’s not really a mapping glitch, but I can see how using IP-based geocoding in the title would turn most readers away without even reading the first sentence of the article.

How to Build a Robot That Will Feed You Breakfast →

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This is the most funny thing you will read this weekend:

The plan: get a robot arm, have it pour cereal and milk into a bowl and feed it to me with a spoon. The only catch was that I had to learn how to program a robot arm and code a pretty complicated sequence to have it serve me breakfast. But I was up for the challenge, because the best way to avoid real problems is to deal with fake ones.

[via wirres.net]

Manipulating and mapping US Census data in R →

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The US Census provides an incredible wealth of data but it’s not always easy to work with it. In the past, working with the tabular and spatial census data generally meant downloading a table from FactFinder and a shapefile from the boundary files site and joining the two, perhaps in a GIS system. These files could also be handled in R but getting the data, reading it into R and, in particular, merging tabular and spatial data can be a chore. Working with slots and all the different classes of data and functions can be challenging.

recent interesting post on stackoverflow by Claire Salloum prompted me to revisit this issue in R and I’ve definitely found some valuable new packages for capturing and manipulating Census data in R.

Great post explaining how to wrangle and map census data in R.