Mike Hansen on The Carpentries

Purdue

Wed, 10 Oct 2012 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Here's the feedback we received for our workshop in Purdue this week. We discussed the shell and Python on day 1, and then git and debugging/testing/documentation on day 2.

Good

Interactivity (technology and people)
Day 2 topics (version control, testing and documentation)
Hints about what's out there
Overall breadth
Hands-on
VirtualBox and using a Virtual Machine
Topics — git and shell
Online materials, breadth
Testing
Python
Good depth, overview
Documenting the bootcamp online
Interesting content
Good for beginners
Examples on day 1 (shell, Python)
Organization
Tips about what not to do

Bad

Too basic for some
Jump up in difficulty on day 2
VirtualBox problems
Wanted Windows-specific examples
Wanted C++ examples
Wanted advantages/disadvantages of Python data structures
Python subtleties not covered for beginners (when to use a colon)
Too fast to follow sometimes (need to pause before executing commands)
Wanted specific skills (i.e., Python)
Wanted to know more about Valgrind
Version control (too in depth — branches)
git command-line was overwhelming (Github was good)
More exercises, homework?
Detailed schedule (so we can cherry-pick topics)
Too fast sometimes
Slides
No printed documentation for notes
What about SVN users?

An Exercise With Matplotlib and Numpy

Mon, 21 May 2012 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

For this tutorial, we'll be plotting some weather data from a site call Weather Underground. You can download temperature readings and weather events for your local area in a comma-separated file.

I've put weather data for Bloomington, IN in a file called weather.csv. Each row is one day, and there are columns for min/mean/max temperature, dew point, wind speed, etc. We'll be plotting temperature and weather event data (e.g., rain, snow).

An Exercise With Functions and Plotting

Sun, 06 May 2012 00:00:00 +0000

This post originally appeared on the Software Carpentry website.

Let's say you have a text file called workout.csv that contains information about your workouts for the month of March:

# date, kind of workout, distance (miles), time (min)
"2012, Mar-01", run, 2, 25
"2012, Mar-03", bike, 10, 55
"2012, Mar-06", bike, 5, 20
"2012, Mar-09", run, 3, 42
"2012, Mar-10", skateboarding, 2, 10

# Broke my leg :(

"2012, Mar-11", Wii, 0, 60
"2012, Mar-12", Wii, 0, 60
"2012, Mar-13", Wii, 0, 60
"2012, Mar-14", Wii, 0, 60

It's a common-separated value (CSV) file, but contains comments and blank lines. The first line (a comment) describes the fields in this file, which are (from left to right) the date of your workout, the kind of workout, how many miles you traveled, and how many minutes you spent.