Below are 5 more selections from the 28 projects that I worked on as part of my Python Engineering class at The Iron Yard, Durham.

ATUS Analysis

IPython Notebook containing analysis of the American Time Use Survey data.

This assignment was largely unguided, with the aim of exploring an unknown data source for ourselves. Getting my initial bearings was a challenge, as there were many files and a huge number of data points (not to mention the coded field names!). I focused on normal activities to ensure the data set was large enough to have relevance.

PROJECT DETAILS

Time: 3.5 days

Python Tools: pandas, NumPy, Matplotlib, IPython Notebook, datetime

IPython Notebook: ATUS ipynb

GitHub: American Time Use Survey Analysis

Programming Language Classifier

IPython Notebook loading and executing custom featurizers.

The challenge of this assignment was two-fold: (1) collect and access a corpus of snippets of programming languages and (2) use Scikit-Learn tools to classify the test snippets as accurately as possible. I manually built extensive featurizers and accompanying tests to be used with the DecisionTreeClassifier because the Naive Bayes classifier gave poor results for my data set.

PROJECT DETAILS

Time: 3.5 days

Python Tools: sklearn, nose, Matplotlib, IPython Notebook

IPython Notebook: Programming Language Classifier ipynb

GitHub: Programming Language Classifier

Road Rage

IPython Notebook presenting traffic simulation.

The goal of this assignment was to use a Monte Carlo simulation to determine the ideal speed limit for a 1 km stretch of road. I put a lot of effort into a version of hard mode that, although working, needed just a bit more troubleshooting.

PROJECT DETAILS

Time: 3.5 days

Python Tools: random, math, NumPy, Matplotlib, IPython Notebook

IPython Notebook: Road Rage ipynb

GitHub: Road Rage

What to Watch

Command-line program to provide meaningful access to data in the MovieLens 100k database.

The purpose of this project was to make effective use of classes, list comprehensions, the csv module to read in data. I built a Django app later in the class that has similar functionality for the MovieLens 1M data set.

PROJECT DETAILS

Time: 3.5 days

Python Tools: csv, math, os, sys

GitHub: What to Watch

Mystery Word / Evil Mystery Word

Command-line “hangman”-style game.

This was the very first weekend project and was a lot of fun to put together. I was able to finish the normal mode on Saturday afternoon, so was able to fully tackle the “Evil” version of the game—just try to beat it!

PROJECT DETAILS

Time: 3.5 days

Python Tools: deepcopy, os, random, unittest

GitHub: Mystery Word / Evil Mystery Word