Rough out plot-communication

communicate-plots.Rmd

@@ -1,19 +1,26 @@
-*Section 2* will show you how to prepare your plots for communication. You'll learn how to make your plots more legible with titles, labels, zooming, and default visual themes. 
-
-```{r echo = FALSE, messages = FALSE, warning=FALSE}
-library(ggplot2)
-```
-
-
 # Communication with plots
 
-The previous sections showed you how to make plots that you can use as a tools for _exploration_. When you made these plots, you knew---even before you looked at them---which variables the plot would display and which datasets the variables would come from. You might have even known what to look for in the completed plots, assuming that you made each plot with a goal in mind. As a result, it was not very important to put a title or a useful set of labels on your plots.
+## Introduction
+
+In [EDA], you learned how to use plots as tools for _exploration_. When you made these plots, you knew---even before you looked at them---which variables the plot would display and which datasets the variables would come from. You might have even known what to look for in the completed plots, assuming that you made each plot with a goal in mind. As a result, it was not very important to put a title or a useful set of labels on your plots.
 
 The importance of titles and labels changes once you use your plots for _communication_. Your audience will not share your background knowledge. In fact, they may not know anything about your plots except what the plots themselves display. If you want your plots to communicate your findings effectively, you will need to make them as self-explanatory as possible.
 
 Luckily, `ggplot2` provides some features that can help you.
 
-### Labels
+### Prerequisites
+
+In this chapter, we'll focus once again on ggplot2.
+
+```{r}
+library(ggplot2)
+```
+
+## Labels
+
+### Plot
+
+### Axes and legends
 
 You can add a title to any `ggplot2` plot by adding the command `labs()` to your plot call. Set the `title` argument of `labs()` to the character string that you would like to appear as the title of your plot. `ggplot2` will place the title at the top of your plot.
 
@@ -47,7 +54,13 @@ ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
        color = "Type of Car") 
 ```
 
-### Zooming
+## Scales
+
+### Transformations
+
+### Colour
+
+## Zooming
 
 Often, it can be helpful to zoom in on a specific region of your plot. In `ggplot2` you can do this by adding `coord_cartesian()` to your plot and setting it's `xlim` and `ylim` arguments. Pass each argument a vector of two numbers, the minimum value to display on that axis and the maximum value, e.g.
 
@@ -62,11 +75,11 @@ ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
 
 What if your plot uses a different coordinate system? Most of the other coordinate functions also take `xlim` and `ylim` arguments. You can look up the help pages of the coordinate functions to learn more.
 
-### Themes
+## Themes
 
 Finally, you can also quickly customize the "look" of your plot by adding a theme function to your plot call. This can be a useful thing to do, for example, if you'd like to save ink when you print your plots, or if you wish to ensure that the plots photocopy well. 
 
-`ggplot2` contains eight theme functions, listed in the table below. Each applies a different visual theme to your finished plot. You can think of the themes as "skins" for the plot. The themes change how the plot looks without changing the information that the plot displays.
+ggplot2 contains eight theme functions, listed in the table below. Each applies a different visual theme to your finished plot. You can think of the themes as "skins" for the plot. The themes change how the plot looks without changing the information that the plot displays.
 
 To use any of the theme functions, add the function to your plot all. No arguments are necessary.