The first round of the presidential election in Finland was held on Sunday. It was a super-exciting race with Sauli Niinistö coming out on top, but with Pekka Haavisto of the Green Party as the great surprise. Haavisto finished second, just before the grand ol’ man of the Center Party, Paavo Väyrynen.
Haavisto is having great momentum and is quickly rising in the polls. But can he really take on Sauli Niinistö who has been the favorite for years already?
With this interactive visualization I will show that Pekka Haavisto face a great challenge in the second round. In the first round he got 570.000 votes. Niinistö got twice as much. 1,4 million voters will have to find a new candidate in the second round. Haavisto will have to get about 70 percent of those votes, which won’t be easy considering he is the liberal alternative of the two finalists and a lot of the undecided voters are conservatives.
Anyway here is the visualization. It lets you drag and drop the votes of the candidates that didn’t make it to the second round. Hopefully it gives you an idea of the effort that Haavisto will have to go through to stand a chance. But who knows? He has surprised us once already.
November is the big gossip fest in Finland. Every year in the beginning of the month the tax records from last year are published. In other words: you get to know who made the most money.
Every year the Finnish media outlets do a very conventional presentation of this material. Page after page of lists of top-earners. Rarely does anyone do anything more creative with the data.
I gave it a shot. This is what came out:
This is my first visualization in Raphael.js. Previously I have been working with D3 and Protovis, but the weak browser support of these two libraries is becoming a growing concern. Especially when one tries to do sell the work. However, I have found Raphael to be very useful and somehow more intuitive than D3.
The idea for this presentation came from the super-visualization, The Sexperience, by British Channel 4, a survey about the sex life of ordinary Brits (don’t worry, you can open it at work as well). I think the geniality behind this setup is that you can follow the respondents in the quiz from question to question, which gives the user the possibility to explore the relation between different questions instead of just looking at one question at a time. What are for example the sexual preferences of the people who lost their virginity late?
To some extent my presentation of the 100 top earners let you do the same thing. You can select the persons you are interested in and follow them through the presentation. This is a potential of the modern web that I think we will see much more of in the future.
For a month now we have been getting news about the Occupy movement that started on Wall Street in the beginning of October. There has been some arguing about the size of this movement. Guardian has made and interesting attempt to answer the question using crowdsourcing. I took a different approach.
The protest are coordinated at the site meetup.com. Here you find a complete list of the 2 506 occupy communities. I wrote a Ruby scraper that goes through this list and gathers information about all the meetups that has been arranged so far (more than 4 000 in a month).
I used the D3.js library to visualize the the list of meetups. This is the result (opens in new window):
The movement clearly peaked on Octboer 15th with meetups in around 600 different locations around the world. Protestors have continued to rally on Saturdays, but not with the same intensity.
Note that there is a number of protests that are missing here. I had some technical difficulties geocoding special characters (using the Yahoo Place Finder API), but that should not distort the picture of how the movement has developed. I didn’t have time to resolve the problem at the moment, but if someone knows how to get the API to understand odd characters such as ä, é and ü I’d appreciate the assistance.
The IAAF athletics world championships just came to an end with the one and only world record set by Jamaica in the short relay. This (the lack of world records) comes as no surprise. It is getting harder and harder to beat the old records, as the graph below shows.
More than 2 000 official IAAF world records have been set since the beginning of the 20th century. In other words: a very interesting set of data. Inspired by this visualization by The New York Times from 2008 I decided to do my own mashup with this data. This is the result (click to open in new window):
There were two challenges with this visualization: getting the data and visualizing it. It was surprisingly difficult to find world record data in an accessible format. Wikipedia provides some help, but the data contains plenty of holes. Instead I had to turn to the only thing the IAAF has to offer: a 700 page pdf with all the athletics statistics you can think of. The open data gospel has apparently not reached IAAF quite yet.
On the other hand this was an opportunity to practice some Excel formatting skills. To copy-paste the data into Excel was easy, transforming into readable columns and rows took some time. But I did it and you’ll find the result in Google Docs. I didn’t figure out how to make Google Docs format seconds, tenths and hundredths correctly, but if you open the spreadsheet in Excel you should be able to get the correct times.
With the data in a pretty spreadsheet I indexed all the results with 1951 as a base year (or the first recorded record for new events) and manually added the newest records, such as the one set by the Jamaican relay team.
As a d3-n00b I used Jan Willem Tulps tutorial as a base script and built around that. The d3.js documentation is still not conclusive, so for a beginner it takes some trial and error to progress, but undoubtedly this is a very powerful library for making handmade interactive visualizations.
All in all a very educative process and a result that I’m quite content with.
Do you, by the way, know which the sixth greatest athletics nation of all time is (measured in number of world records)? FINLAND! A bit hard to believe a year like this when non of our athletes made the top-eight.
|Country||Number of records|
These two interactive visualizations has been in the drawer all summer. I made them in June already and did a small effort to get them published, but then I when that didn’t happen they were sort of forgotten about.
The starting point was the campaign funding data that was published after the parliamentary elections here in Finland. All MPs have to publicly declare all donations above 1500 euros. The data can be found here, or in a slightly refined form here (thanks Helsingin Sanomat!). Helsingin Sanomat has already provided their own visualization, check it out here.
I started by approaching the data as a network using Protovis. This was the result:
The network approach above might be pretty, but not as informative as it could be. Again I used Protovis to build an interface that quickly lets you browse through all the reports.
I think this visualization has a lot of strengths. It is “click-less” which means you can quickly browse the candidates. Life is too short to be clicking. The loading time is also much, much shorter than in the network visualization.
Yesterdays elections turned out to be even more exciting than everyone had expected. True Finns shocked everyone with their third position. Trying to get a government together now is not easy.
- Get the data. (Note that the answers might be slightly outdated, I noted in the reporting from Yle that a few new candidates seem to have participated since I did the scrape. However, the big picture should be accurate.)