Hide some exercises

Author: Gammerdinger

Tidyverse_ggplot2/lessons/03_ggplot2.md

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 **Exercises**
 
 1. Arrange `bp_oe` by `term_percent` in descending order.
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 So far we have explored many layers that can be added to any plot with the ggplot2 package. However, we haven't explored the different `geom`s available. The type of data you are plotting will determine the type of `geom` needed, but a nice summary of the main `geom`s is available on the [RStudio ggplot2 cheatsheet](https://rstudio.github.io/cheatsheets/data-visualization.pdf).
 
 Let's explore different `geom`s by creating a couple of different plots. We'll start with a bar plot of the number of genes per category. We can start with the most basic plot by specifying the dataframe, geom, and aesthetics. 
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 **Exercises**
 
 Based on the number of genes associated with each GO term ("term.size" column) we can categorize them into "small", "large" or "medium" categories. Once we have done that, we want to determine what the spread of p-values is for each category; we can do this by drawing a boxplot.
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 4. Add appropriate labels and `theme()` layers to your liking.
 
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 ## Resources