This doesn’t have a lot to do with bio part of biostatistics, but is an interesting data analysis that I just started. In the wake of the Brexit vote, there is a petition for a redo. The data for the petition is here, in JSON format.
Fortunately, in R, working with JSON data is pretty easy. You can easily download the data from the link and put it into a data frame. I start on that here, with the RJSONIO package, ggplot2, and a version of the petition I downloaded on 6/26/16.
One question I had was whether all the signers are British. Fortunately, the petition collects the place of residence of the signer, assuming no fraud. I came up with the following top 9 non-UK countries of origin of signers.
- I left off the UK. The number of signatures is over 3 million, and contains by far the largest percentage of signatories.
- 5 of the 9 top countries are neighbors, including the top 2. The other 4 are Australia, the US, Canada, and New Zealand, who are all countries that have strong ties to the UK.
- This assumes no petition fraud, which I can’t guarantee. I saw at least one Twitter posting telling people to use her (if the profile pic is to be believed) residence code. There is a section of the petition data showing constituency, so I’m wondering if it would be possible to analyze the petition for fraud. I’m not as familiar with British census data as I am with US, but I imagine a mashup of the two would be useful.
(Update: Greg Jefferis posted a nice analysis here. See comments below.)