Tool Install Instructions

These are the tools that you need to install before each lab. If you have problems, Sara can be reached on Skype at: sj.farmer (I get a lot of junk requests: when you connect, add a note that you're doing these sessions).

If you want to install and play with tools ahead of time, please feel free: most of them are a great deal of fun.

Session: Python Basics

1. Make friends with your terminal window

2. Install Python, iPython and Python libraries

3. Install R

4. Install Git

5. Test Git

Session: Acquiring data

1. Install Tabula

Session: Visualisation software

1. Install Tableau

Session: Cleaning and Exploring Data

1. Install OpenRefine

Session: Predicting values from data

Session: Handling text data

Session: Handling geospatial data

1. Get Cartodb and Qgis

2. Install Python GIS libraries

Session: Learning relationships from data

Session: Working with data science teams

Session: Enterprise data tools

Session: learning classes from data

Session: Handling big data

Bonus: things you might want to play with

Session: Python Basics

You need to know where your terminal window is, and install Python, R and iPython. You'll also need to install github to get the latest version of the code examples.  Instructions for all this are below.

1. Make friends with your terminal window

DO THIS:

Mac Users: your terminal commands include:

Windows users: your Terminal commands include:

2. Install Python, iPython and Python libraries

DO THIS:

MAC 10.6 - 10.8 users: you may get the error "Cannot locate working compiler" at this point. Don't panic: we're working on this, and will get a fix to you ASAP.

3. Install R

DO THIS: In the terminal window, type this series of commands:

4. Install Git

DO THIS: Get a Github account at https://github.com/

NB Some Mac users will get a "can't be opened because it is from an unidentified developer" message when you try to run the Git install file. This is happening because your security doesn't like apps that aren't downloaded from the Mac App Store. The answer is to right-click on the file, or to press control when you click on it.

DO THIS: IF YOU HAVE A MAC WITH OSX Snow Leopard: install git version 1.7.5 from https://code.google.com/p/git-osx-installer/downloads/list

DO THIS: IF YOU HAVE A MAC WITHOUT OSX Snow Leopard: Install github from http://git-scm.com/downloads (click on the logo for your operating system (windows, mac etc) under "downloads")

DO THIS: WINDOWS USERS:

There's helpful material at git-scm.com/book/en/Getting-Started-Installing-Git if you get stuck.

5. Test Git

DO THIS:

Session: Acquiring data

You need to:

1. Install Tabula

DO THIS: Go to http://tabula.technology/, click the "download for..." button.

Session: Visualisation software

You need to:

1. Install Tableau

DO THIS:

2. Set up D3

DO THIS:

Session: Cleaning and Exploring Data

You need to:

1. Install OpenRefine

DO THIS: Go to http://openrefine.org/download.html; click on the download for your PC type (Mac, Windows, Linux)

MAC: brew cask install google-refine

Session: Predicting values from data

No installs needed

Session: Handling text data

No installs needed

Session: Handling geospatial data

You need to:

1. Get Cartodb and Qgis

DO THIS: go to https://cartodb.com/, click "sign up"

DO THIS: IF YOU'RE ON WINDOWS: Go to http://www.qgis.org; click “download now”

DO THIS: IF YOU'RE ON A MAC:

2. Install Python GIS libraries

DO THIS: In the terminal window, type

If installing fiona fails because it cannot find the gdal.h file you need two export statements. Enter:

export CPLUS_INCLUDE_PATH=/Library/Frameworks/GDAL.framework/Versions/1.11/Headers

export C_INCLUDE_PATH=/Library/Frameworks/GDAL.framework/Versions/1.11/Headers

This assumes you installed the GDAL 1.11 Complete package listed above. After you enter these export statements in the Terminal, run the pip install fiona again.

Session: Learning relationships from data

No installs needed

Session: Working with data science teams

No installs needed

Session: Enterprise data tools

No installs needed

Session: learning classes from data

No installs needed

Session: Handling big data

No installs needed

Bonus: things you might want to play with

No installs needed