ggplot_post_text_example.Rmd

Simple plot with text boxes
========================================================

Was doing a little presentation to our research group and had to explain the difficulties of 'collapsing' longitudinal data into a single measure when the Y var is quite variable. For the particular Y var of interest, it represents burden of disease, so a high Y var for a long time is indicative of high risk, compared to a low value for a similar time. Hence you have issues using with the mean, or the AUC. There's a lot more to it than that, but that's the gist of the point of this graph. Sharing the code cause it might be useful to someone else at some point.

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I wrote this post in [RStudio](http://rstudio.org/download/) using the [R Markdown](http://www.rstudio.org/docs/authoring/using_markdown) language and then [knitr](http://yihui.name/knitr/) to turn in into markdown (.md), and then [pandoc](http://johnmacfarlane.net/pandoc/) to turn it into html. The original file is available here on [github](https://github.com/nzcoops/blog_code/blob/master/ggplot_post_text_example.Rmd).

system("pandoc -s petrol_prices.md -o petrol_prices.html")

## Set up dummy data
```{r results='hide'}
library(ggplot2)

# Set up the data and text separately
dat <- data.frame(
    frame=c(rep("A",6), rep("B",2), rep("C",11), rep("D",11)),
    y=c(rep(10,6), rep(10,2), rep(5,11), seq(5,10,0.5)),
    x=c(seq(13,18,1), seq(17,18,1), seq(8,18,1), seq(8,18,1))
)

txt <- data.frame(
    label=c("Mean - 10","AUC - 50","Mean - 10","AUC - 1","Mean - 5","AUC - 50","Mean - 7.5","AUC - 75"),
    x=rep(17.5,8),
    y=rep(c(13.5,12),4),
    frame=c(rep("A",2), rep("B",2), rep("C",2), rep("D",2))
)
```

## And here's the plot
```{r text_example, fig.width=8, fig.height=8}
ggplot(data=dat, aes(x=x,ymax=y, ymin=0)) + geom_ribbon(data=dat) +
    facet_wrap(~frame) + scale_y_continuous(limits=c(-0.1,14)) + 
    scale_x_continuous(limits=c(5,20)) +
    labs(y="Y var", x="X var") +
    geom_text(data=txt, aes(y=y, label=label))
```