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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.Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
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.
There are a couple of things to remember when interpreting this graph:
- 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.
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