My friend Johanna asked me to help her figure out how to visualize some data she was working with.
(Maybe I can get her to update this blog with some actual information on the Data. My Estonian is about as good as my Esperanto or my Inuit, so I know what the labels on the data say, but well. Not what they mean)
She gave me a list of buildings of a district of Talinn. Each building had two datapoints: a) it was classified according to some (to me completely mystical) Estonian system and b) the year it was built in. My first thought was to just to give each classification a value and create a scatter plot:
This initially seemed quite useful. You can see which classifications concern newer buildings, which ones concern older buildings. You can see that very few - well actually, no buildings at all where built after 1940 and before 1945. However, I did not feel like one sees the entire picture. So I decided to add some jitter.
Once I saw the result, I decided to add a whole lot more jitter. This is the graph I came up with:
Here we can see a whole lot more detail. For example the third, fourth and fifth category from the top looked fairly similar around the year 200 in the first graph. Here we see that there is actually a lot more going on.
I still was not quite satisfied, so I considered it a programming challange and tried to see what I could come up with using processing.
I would have never anticipated the huge spike in the first classification just by looking at the chart I had previously made. I'm not quite sure if the mirrored thing is so smart, as it might make the differences between a large and a small number of occurrences appear to be smaller then it is... still, I think its a pretty graph.
Here is (some of) the code I used:
("some of" because estonian seems to break snippler which I use for the code formatting)
Finally, this is what happened, when i did not use pushMatrix() and popMatrix() correctly. I think its quite a beautiful result:
