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# <div class="line-block">Getting Started in R<br />
an introduction to data analysis and visualisation</div>
## Mini-project
### 1 July 2019

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## Background

On 23 June 2016 the UK electorate was asked:
<br>
<br>

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## Background

On 23 June 2016 the UK electorate was asked:
<br>
<br>

<br>
--

Several newspapers tried to explain this unexpected result ...

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### The Guardian
<img src="img/theguardian.png" height="450px" />

<https://www.theguardian.com/politics/ng-interactive/2016/jun/23/eu-referendum-live-results-and-analysis>

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### The Economist
<img src="img/theeconomist.png" height="450px" />

<http://www.economist.com/blogs/graphicdetail/2016/06/daily-chart-17>

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### Financial Times
<img src="img/ft.png" height="450px" />

<http://blogs.ft.com/ftdata/2016/06/24/brexit-demographic-divide-eu-referendum-results/>

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## We are going to do the same in R!

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## FT-style scatterplot (using ggplot2)
<img src="img/ft_plot.png" height="450px" />

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## Task

Visualise the relationship between a number of different socio-demographic variables and EU Referendum voting patterns.

You'll need to:

1. **Import**: download and read data
2. **Tidy**: clean data for analysis in R
3. **Transform**: create new variables and merge different data sets
4. **Visualise**: create a set of scatterplots
5. **Report**: put together a summary document of your findings

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## Option B

Do your own thing (BYOD - bring your own data)