We had approximately 48 hours to use open data and create a hack (web app/ mobile app). This was never going to be easy considering:
- I don’t know data science
- I didn’t have a team when I registered
By Friday evening I was in a team of 6 people. Three developers including me, and three non developers.
A: Choosing a Project
This was the hardest part. It took us 8 hours during the hackathon to decide. The biggest mistake that we did was we assumed that data would be available (more on that later). My team started talking about the issues we were dealing with: transport, immigration (due to the changes proposed), housing prices etc. One of us dropped a bombshell and said let’s make a game. Suddenly I didn’t care about dealing with problems: I wanted to make the game.
I always wanted to make games but I don’t know much about it. Plus, I don’t have a clearer picture of where I wanna go with the game development so I haven’t tried it yet.
Our idea was simple: You start the game about 15 years prior. You start buying houses and earn money and in 15 years time you should have certain amount of money to win. Brilliant (and typically the premise of every tycoon game) idea. We knew it worked. To implement it we needed open data of house prices in the city/country.
We don’t have to work on the data at all. We just had to use it as stepping points. All of us loved the idea and even before we found the idea we started working out the mechanics of the game.
Turns out Auckland has no housing data of any kind. Sure we could find data related to renting or number of people in the city but house prices? Nope. This is an important point because there is a house price bubble in the city: housing prices are going up.
On Saturday afternoon we dropped the idea. I wanted to make that game but without data it wouldn’t be eligible in the hackathon. We had another brainstorm and finally settled on looking at the employment statistics.
B: Our App
His idea was to look at how industries are distributed and how many people are depended on it. This way we can tell predict which economies are vulnerable to decline in that particular industry. We planned on using a heatmap to show all the districts with varying colors depending on the distribution.
We found the data fairly easily. We needed three components: a heat map, piechart for further distribution and lastly a slider so that we can see all fifteen years. We used C3 charts and Here API for creating the heatmap and pie chart (FYI: use C3, they are super easy and look amazing). I worked mostly on the layout and the slider.
Here is the finished product presentation and you can try it out here.
I haven’t seen this much work done in such a short amount of time except in university when the assignment is due. Neither one of us were willing to settle for anything less than what we had envisioned.
My friend also wanted to come but didn’t because he didn’t know coding. What he didn’t know was coding was only 50% of the work and the easier bit. We had to make a video on our project and the skills required for that is rare. All of us occasionally gave feedback to one another, encouraged one another. I ate all the food because someone has to.
There is something amazing about working straight for 36 hours. Sure I was tired, I still am a little bit. But if I was doing everything alone in my time, I would probably take couple of weeks for this, if I didn’t give up on this in the middle by frustration.