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Setting up OS X for Data Science

I had to reinstall my laptop and at the same time I had new team member joining to the team. Therefore I started to write this as a tutorial or check list on how to setup a new MacBook Pro OS X for typical data science development. This is geared towards Scala based development and Spark as that's what we do at the moment. However, I'll start slightly more generally and will add some other things too. Let's start from the basics...

OS X

OS X is great for data science. However, it's missing configurations and apps that you need. Let's get started.

We need a good package manager, text editor, github source control, code editors and so on. But first will look at the command line, Terminal.

Terminal

Open up Terminal. If you don't know where to find it, open Spotlight search and type Terminal into it. Now, right click on it's icon in the Dock. Select Options - Keep in Dock. This way, it's always there when you need it. And you'll need it.

How to map GPS locations to Grid Database from Statistics Finland

Keywords: Tilastokeskus, Ruututietokanta, GPS, WGS84, EUREF-FIN, ETRS89-TM35FIN

The grid of the DB

The Grid database contains 250m x 250m squares. The square is definied by the x- and y-koordinates of the lower left corner of the grid. This corner defines the square. In the database, they are even meters without decimals.

Matching GPS point to Grid DB

This example is using Scala and the Sanoma-CDA / maxmind-geoip2-scala library. To use that library, you should doanload it and publish either locally or to your artifactory.

	import com.twitter.algebird._
	import com.twitter.algebird.Operators._

	// generate 2 lists
	val A = (1 to 300).toList
	val B = (201 to 400).toList

	// Generate a Bloomfilter
	val NUM_HASHES = 6
	val WIDTH = 6000 // bits