This is an upgraded version of my 3rd project where I wanted to visualize the trend of top 10 checked DVD in the period 2006-2011 in the Seattle Public Library.

Query 1

SELECT title, count(*) FROM inraw WHERE year(ckoutDateTime) > '2005' and year(ckoutDateTime) < '2012' and itemtype like ‘%dvd%’ GROUP BY title ORDER BYcount(*) DESC LIMIT 10;

Query 2

SELECT title, count(*) FROM inraw WHERE year(ckoutDateTime) > '2005' and year(ckoutDateTime) < '2012' and title like ´#´ // title of the DVD GROUP BY month ORDER BY month;

The process is splitted in 2 parts, in the first I’m querying what are the m10 ost checked DVD in the period 2006-2011, then i’m cheking per each title the amount of checks every year, to have both the total amount of checks and partial results. The transparency of the spheres representing the values is proportional to the value, pressing the button n.1 is possible to show or hide the track per each title.

Early version

Final version

In this project I explored methods for coloring data and representing layers of meaning within a 3D space through an interesting data set. I also spent time in the data selection, filtering and sorting, producing 2 queries to fit the data to the aim of the project. From the data I was able to track the number of checkout for the top 10 dvd and compare them during time.

I used Processing and Peasycam.

Run in Browser

Source Code

1: visualize or hide the track of each DVD during time.