Here are the Hackpad presentation notes from Round 22: Wart Warthog.

Speaker #1: Rachel Shorey

Girl Scouts mentioned on the Congressional Record

Who appears in the congressional record more – boy scouts or girl scouts? Rachel created a webapp that can tell you!

Started with http://capitolwords.org/?terma=boy+scouts&termb=girl+scout - but it didn’t quite fit her needs.

Check out the site: http://www.scout-vs-scout.com

Code lives at https://github.com/rshorey/scout-vs-scout

Boy scouts appear 67 times / girl scouts appears 14 times. If you want to see that change, it has a widget to contact your representative.

Helpful resources: unsplash.com for free, high-resolution photos dollarphotoclub.com for high quality royalty-free stock photos.

Speaker #2: Maggie Cirqui

Diners, Drive-Ins, and Dives

Are the restaurants Guy Fieri goes to in Diners, Drive-Ins and Dives actually good? (According to Yelp)

A list of these restaurants exists on Wikipedia, luckily. She ran this list through the Yelp API (lots of data cleaning was required first), and put the results into JSON and color coded the ratings. List of restaurants was helpfully compiled on Wikipedia.

Check out the results at: http://ddd-and-yelp.mybluemix.net

Code lives at: https://github.com/mcriqui/Diners_DriveIns_and_Dives

Speaker #3: Jess Garson

Simple Pandas

Jess put together a collection of short example code projects which implement some capabilities of the Pandas Python library.

Code lives at: https://github.com/JessicaGarson/Simple_Pandas

She was inspired by Code That Only Does One Thing, a collection of simple code examples on github that demonstrate bare-bones functionalities in Python 2.7, Flask, and Django.

Pandas is a library for data cleaning, data wrangling, and analysis (the “R” of Python). Short examples of common tasks in Pandas like merging two data files. The goal of all of this is to make it easier to find out how to do common tasks in Pandas and improve the learning experience for beginners

Speaker #4: Elaine Ayo

Audiolyzer: Listen to your data (Hacking Journalism Hackathon project)

Code lives at: https://github.com/emmjab/audiolization

Live demo at: http://audiolyzr.pythonanywhere.com/test

How do you generate sound based on data? Elaine created a webapp that takes in a dataset, normalizes it onto a 0-1 scale and translates that into frequencies.

She used shark attack data and turned it into music! This software uses the tones.js library to generate the musical tones.

This project was a collaboration with Rowan, Emma, and Danny.

Speaker #5: Michael Kane

Wordswram

Dynamic word cloud visualization: how does word usage change over time? Michael created an app in PyGame to create these visualizations.

He used the AAAS Science Magazine Google books n-gram, and social security baby names as data sets. He then dynamically generated word clouds based on the most used words for each year.

In his visualization, each word is a box in PyGame, and the built-in physics emulator performs collision detection between the boxes.

He shows dynamic word cloud visualizations for the following collections of articles/data:

Topics in AAAS Science Magazine over time, US President Popularity in Google nGrams over time, Baby name popularity over time.

Code lives at: https://github.com/thisIsMikeKane/WordSwarm

Check out some example word clouds at Michael’s Youtube Channel

Speaker #6: Chris

PolTwt

Chris created a webapp that pulls in top tweets from public figures, breaks out topics, mentions, and hashtags.

He takes this data and stores it in memory tables – not for long-term storage but great for very fast queries and queries with many joins. Not great for complex comparisons – the performance boost isn’t too much in those cases.

The app is built with Flask & Bootstrap.

Live demo at: alpha.poltwt.com

Speaker #7: Shannon Turner

Let’s Go!

Shannon created a website where you can search for over 6000 museums from all across the US based on category or location.

To make this site, she needed to create an extract, transform, and load process to get data from the Institute of Museum & Library Sciences into working order.

Data cleaning was a big problem: there were a lot of bad museums in the data. After all the hard work, she was able to build a fully functioning website!

The code behind her website was written in Django.

Try it for yourself at: shannonvturner.com/museums

Code lives at: https://github.com/shannonturner/museums

Speaker #8: Reed Spool

Executing JavaScript written plainly in a Google Document

Reed figured out a hack that lets you execute javascript within a google document. It uses a bookmarklet, and makes use of the dreaded eval()!

Check out the hacked google document he put together: here

Thanks to everyone who presented, everyone who attended, Eric Haengel, @svt827, @reedspool and @metasemantic for the writeup, and of course thanks to our favorite WeWork for hosting!