Tyler Sipprelle
CS 171
5-15-2009

Final Project

Motivating Questions

As an economics major, I spend a fair amount of time discussing and writing about exchange rate movements. When it came to come up with a final project proposal for this class, it occurred to me that it would be fantastically useful to visualize these numbers in their global context. Fluctuations in exchange rates often reflect fundamental shifts in the economic or political stability of countries or regions, and I was interested to see if trends would appear.

Questions:
• What countries had the largest / smallest exchange rate movement against the target country?
• What regions had the largest / smallest exchange rate movement against the target country?
• Do certain regions' currencies appreciate or depreciate in concert??
• What countries not in the same region have similarly moving exchange rates?

Data

I scraped my data from Google Finance (http://www.google.com/finance) using a Python script and regular expressions. I scrape 1-day percentage changes in the values of 63 different currencies against the dollar. I can then use these changes to compute the movements of the currencies against one another.

My data is stored in the file currencies.tsv. With more time, I would have loved to learn how to use cron to run my scraper on a daily basis. As is, the user has to run the scraper each time he or she wants new data for the visualization. Doing so requires typing "python currency.py" at the command prompt and dragging the resulting currencies.tsv file into the data folder for my processing script.

Design

I settled on the design I did because I wanted to simeltaneously portay the exchange rate movements of the entire world. Coloring each country seemed problematic, both programmatically and because many of the countries are so small as to be almost invisible on the map. Therefore, I decided to associate rectangles with the countries as a solution that was both easily comprehensible and aesthetically pleasing.

From there, it was an obvious decision to use Color Brewer to pick good colors to encode exchange rate fluctuations. I settled on green to designate the presently selected country for green's association with money. Mousing over any of the rectangles gives specific information on that country. The user can change the country against which to track exchange rate movements while clicking on a different rectangle. Had my circumstances been different, I would have loved to implement brushing and linking features, as well as incorporating data over different time periods.

Use

Use of my visualization is extremely simple. The user can change the base country (designated by the green rectangle) against which he or she wants to visualize exchange rate movements by clicking on any other rectangle. Mousing over any other rectangle will reveal data for that country.

Insights

I have been extremely happy with what my visualization reveals, even with its relatively limited feature set. Looking at the data for today, my visualization immediately reveals that Europe as a region weakened significantly against the dollar, while East Asia held much more steady. South America was a bit of a mixed bag. I was surprised by the weaknesses of the Australian pound and New Zealand dollar.

The country that really stands out in my visualization on May 15th is South Africa, the country that suffered the largest slide today against the dollar. This seemed unusual, given that the only two other countries near SA had not depreciated at all. I looked up the news on SA and found that the country's stock market experienced its largest decline of the year today and that political uneasiness (apparently the country has just inaugurated a new president) is keeping investors on edge.
While my visualization does not provide fantastically deep insights, I believe that it is a useful tool for surveying the world at large. It is immediately obious how the currencies of entire regions move together. Currencies that are not moving with their neighbors stick out, and alert the user to investigate further.

Applet

Click here for my visualization.

Files

Scraper
Zipped Processing Files