I’ve been looking into development trends in Raleigh lately using open data. Here’s a historical look at building permits over the past seven years using Plotly. What trends do you see?
In my development environment the graph was stacked bars (far easier on the eyes), but when I uploaded it to the hosting site the bars ended up side-by-side. Also, I could probably have incorporated some sort of sorting algorithm to make the bars look nicer.
Have suggestions for a visualization? Leave a comment!
This video by the vlogbrothers does a great job at breaking down what the unemployment rate in America really means, but also exemplifies how reporting data improperly can cause issues. There are six main ways(probably more) to measure unemployment! Mixing measurement types or presenting one out of context can distort what is happening in reality.
Keep those critical thinking skills sharp, folks. We’re gonna need them.
Here’s a little visualization app I made a couple of months back which explores hockey players in the NHL during the 2015 – 2016 season. As we get closer to the end of the regular season this year I’ll take a look at 2017’s players.
Over the past ten years, Raleigh and the outlying areas have been growing at a breakneck pace. The availability of jobs and the awesome local amenities have made the Oak City one of the most desirable places in the country to live. Where are all these people living? Some of them get lucky in the hot resale market, but many are choosing to build new. In this graph, I used data from Raleigh Open Data and plot_ly in R to display the builders who completed the most new builds in 2016. Click the picture for an interactive version!