Data analysis with friends (Part 1)

What: ISU Graphics group will host a 1 hour data-a-thon in which we will all analyze a dataset together.

When: Nov. 5th at 1:10pm

Where: In Snedecor 2113 (remote participants also encouraged to participate)

Why: For the fun of it.

Today we will discuss how this will be accomplished.

Rich architecture for interactive computing with:

• Powerful Python shells (terminal and Qt-based).
• A web-based notebook with the same core features but support for code, text, mathematical expressions, inline plots and other rich media.
• Support for interactive data visualization and use of GUI toolkits.
• Flexible, embeddable interpreters to load into your own projects.
• Easy to use, high performance tools for parallel computing.

[Source]

Created in Summer 2014 by the IPython development team to carry forward a vision of reproducible interactive computing for all programming languages:

• Python
• Julia
• R
• Ruby, Haskell, Scala, Go, etc.

A home for the language independent parts of the architecture:

• A network protocol for applications to talk to kernels that run code for interactive computations.
• A set of applications that enable users to write and run code on those kernels.
• Notebook file format and conversion tools (nbconvert).
• Notebook sharing service (https://nbviewer.jupyter.org/).

[Source]

Create and store notebooks in Google Drive and allow for collaborative editing of notebooks using

1. The CoLaboratory Chrome App.
2. CoLaboratory with Classic Jupyter Kernels.

Requirements

• Chrome Beta or Dev version
• IPython version 2.x (Not 3.0!)

• IRKernel is a package that allows us to run a CoLaboratory (Jupyter) notebook with an R kernel.
• Your turn: Let's get CoLaboratory up and running so we can all play!

1. cd /path/to/colaboratory
   python -m colaboratory --profile R
   

2. Log in with your google drive account

3. E-mail your google drive account name to andee.kaplan@gmail.com

4. Open the document we share with you …