Employed basic Python syntax on Star Wars script data to determine which character speaks most often.

Star Wars Episode IV script. [link]

Use of Python to read/ parse a raw dataset, convert data types, apply IF statements, and apply for loops in order to find which US city has the lowest rate of violent crime.

Number of incidents of 'violent crime' within each US city for 2013. [link]

Application of Python functions to parse data, apply IF statements, and create a dictionary in order to calculate the frequency of different weather conditions in Los Angeles.

Historic daily weather conditions for Los Angeles. [link]

Use of Python functions which tokenize string data, check for syntax and index errors, and normalize data dictionaries in order to provide a check for spelling errors within text data.

Short story text file with a number of spelling mistakes. [link]

Employed modules and classes in Python to determine the number of wins for an American National Football League (NFL) team using data from 2009 to 2013.

National Football League (NFL) win/ loss records for each game from 2009 to 2013

Use of the enumerate function, list comprehensions, try/ except blocks, and the None type in Python, while finding the most common names for US Congressman/ Congresswomen.

Members of the United States Congress (1789-Present) and congressional committees (1973-Present) in YAML. [link]

Application of Python functions to create a 'while' loop, use the 'break' keyword, and add named and optional arguments to a function in order to find which US airlines experience the most delays.

US airline flight delay statistics from the US Department of Transportation's (DOT) Bureau of Transportation Statistics (BTS). [link]

Use of scopes and debugging in Python while analyzing student loan defaults in the US.

Student loan debt data (e.g. number of borrowers and defaulted borrowers) for educational institutions within the US.

Object oriented programming in Python, including writing organized sensible code and implementing comparison operators, to compare the average ages of players on various NBA teams.

NBA players data (e.g. player name, position and points per game) from the 2013-2014 season. [link]

Example exception handling code in Python applied to recorded chopstick 'food pinching efficiency' data.

Recorded 'food pinching efficiency' for 31 male junior college students and 21 primary school pupils who used chopsticks of various lengths.

Advanced string manipulation and anonymous functions in Python in order to assess characteristics of a list of user passwords.

List of 2,151,220 unique ASCII paswords.