09-visualize-data.Rmd

# Visualize Data

***

```{r echo = FALSE, results='asis'}
build_toc("09-visualize-data.Rmd")
```

***

## What you should know before you begin {-}

```{block2, type='rmdcaution'}
The ggplot2 package provides the most important tidyverse functions for making plots. These functions let you use the [layered grammar of graphics](https://r4ds.had.co.nz/data-visualisation.html#the-layered-grammar-of-graphics) to describe the plot you wish to make. In theory, you can describe _any_ plot with the layered grammar of graphics.
                                                                                                                                                    
To use ggplot2, you build and then extend the graph template described in [Make a plot]. ggplot is loaded when you run `library(tidyverse)`.                                    
```

## Make a plot

You want to make a plot.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point()
```

#### Discussion {-}

Use the same code template to begin _any_ plot:

```{r eval = FALSE}
ggplot(data = <DATA>, mapping = aes(x = <X_VARIABLE>, y = <Y_VARIABLE>)) +
  <GEOM_FUNCTION>()
```

Replace `<DATA>`, `<X_VARIABLE>`, `<Y_VARIABLE>` and `<GEOM_FUNCTION>` with the data set, column names within that data set, and [geom_function][Make a specific "type" of plot, like a line plot, bar chart, etc.] that you'd like to use in your plot. Within ggplot2 code, you should _not_ surround column names with quotes.

The `geom_point()` function above will create a scatterplot. Notice that some type of plots, like a histogram, will not require a y variable, e.g.

```{r}
ggplot(data = mpg, mapping = aes(x = cty)) +
  geom_histogram()
```

```{block2, type='rmdcaution'}
When using the ggplot2 template, be sure to put each `+` at the _end_ of the line it follows and never at the beginning of the line that follows it.
```

## Make a specific "type" of plot, like a line plot, bar chart, etc.

You want to make a plot that is not a scatterplot, as in the [Make a plot] recipe.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_line()
```

#### Discussion {-}

The `<GEOM_FUNCTION>` in the [ggplot2 code template][Make a plot] determines which type of plot R will draw. So use the geom function that corresponds to the type of plot you have in mind. A complete list of geom functions can be found in the [ggplot2 cheatsheet](https://github.com/rstudio/cheatsheets/raw/master/data-visualization-2.1.pdf) or at the [ggplot2 package website](https://ggplot2.tidyverse.org/reference/index.html).

Geom is short for _geometric object_. It refers to the type of visual mark your plot uses to represent data.


## Add a variable to a plot as a color, shape, etc.

You want to add a new variable your plot that will appear as a color, shape, line type or some other visual element accompanied by a legend.

#### Solution {-}

```{r}
ggplot(
  data = mpg, 
  mapping = aes(x = displ, y = hwy, color = class, size = cty)
) +
  geom_point()
```

#### Discussion {-}

In the language of ggplot2, visual elements, like color, are called _aesthetics_. Use the `mapping = aes()` argument of `ggplot` to map aesthetics to variables in the data set, like `class` and `cty`, in this example. Separate each new mapping with a comma. ggplot2 will automatically add a legend to the plot that explains which elements of the aesthetic correspond to which values of the variable.

Different types of plots support different types of aesthetics. To determine which aesthetics you may use, read the aesthetics section of the help page of the plot's geom function, e.g. `?geom_point`.

```{block2, type='rmdcaution'}
Aesthetic mappings must be defined inside of the `aes()` helper function, which preprocesses them to pass to ggplot2.
```

## Add multiple layers to a plot

You want to add multiple layers of data to your plot. For example, you want to overlay a trend line on top of a scatterplot.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point() +
  geom_smooth()
```

#### Discussion {-}

To add new layers to a plot, add new geom functions to the end of the plot's [ggplot2 code template][Make a plot]. Each new geom will be drawn _on top_ of the previous geoms in the same coordinate space.

```{block2, type='rmdcaution'}
Be sure to put each `+` at the _end_ of the line it follows and never at the beginning of the line that follows it.
```

When you use multiple geoms, data and mappings defined in `ggplot()` are applied _globally_ to each geom. You may also define data and mappings within each geom function. These will be applied locally to only the geom in which they are defined. For that geom, local mappings will override and extend global ones, e.g.

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point(mapping = aes(color = class)) +
  geom_smooth()
```

## Subdivide a plot into multiple subplots

You want to make a collection of subplots that each display a different part of the data set.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point() +
  facet_wrap(~class)
```

#### Discussion {-}

In ggplot2 vocabulary, subplots are called _facets_. Each subplot shares the same x and y variables, which facilitates comparison. 

Use one of two functions to facet your plot.`facet_wrap()` creates a separate subplot for each value of a variable. Pass the variable to `facet_wrap()` preceded by a `~`.

`facet_grid()` creates a grid of facets based on the combinations of values of _two_ variables. Pass `facet_grid()` two variables separated by a `~`, e.g.

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point() +
  facet_grid(cyl ~ fl)
```


## Add a title, subtitle, or caption to a plot

You want to add a title and subtitle above your plot, and/or a caption below it.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point() +
  labs(
    title = "Engine size vs. Fuel efficiency",
    subtitle = "Fuel efficiency estimated for highway driving",
    caption = "Data from fueleconomy.gov"
  )
```

#### Discussion {-}

The `labs()` function adds labels to ggplot2 plots. Each argument of `labs()` is optional. Labels should be provided as character strings.

## Change the axis labels of a plot

You want to change the names of the x and y axes.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point() +
  labs(
    title = "Engine size vs. Fuel efficiency",
    x = "Engine Displacement (L)",
    y = "Fuel Efficiency (MPG)"
  )
```

#### Discussion {-}

By default, ggplot2 labels the x and y axes with the names of the variables mapped to the axes. Override this with the `x` and `y` arguments of `labs()`. 

## Change the title of a legend

You want to change the title of a legend.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = class)) +
  geom_point() +
  labs(color = "Type of car")
```

#### Discussion {-}

ggplot2 creates a legend for each aesthetic except for `x`, `y`, and `group`. By default, ggplot2 labels the legend with the name of the variable mapped to the aesthetic. To override this, add the `labs()` function to your template and pass a character string to the aesthetic whose legend you want to relabel.

Use a `\n` to place a line break in the title, e.g.

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = class)) +
  geom_point() +
  labs(color = "Type of\ncar")
```

## Change the names within a legend

You want to change the value labels that appear within a legend.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = class)) +
  geom_point() +
  scale_color_discrete(labels = c("Two seater", "Compact" ,"Sedan", "Minivan", "Truck", "Subcompact", "SUV"))
```

#### Discussion {-}

To change the labels within a legend, you must interact with ggplot2's [scale system](https://r4ds.had.co.nz/graphics-for-communication.html#scales). To do this:

1. Determine which scale the plot will use. This will be a function whose name is composed of `scale_`, followed by the name of an aesthetic, followed by `_`, followed by an identifier, often `discrete` or `continuous`.
1. Explicitly add the scale to your code template
1. Set the labels argument of the scale to a vector of character strings, one for each label in the legend.

## Remove the legend from a plot

You want to remove the legend from a ggplot2 plot.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = class)) +
  geom_point() +
  theme(legend.position = "none")
```

#### Discussion {-}

To suppress legends, add `theme()` to the end of your [ggplot2 code template][Make a plot]. Pass it the argument `legend.position = "none"`.

## Change the appearance or look of a plot

You want to change the appearance of the _non-data_ elements of your plot.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = class)) +
  geom_point() +
  theme_bw()
```

#### Discussion {-}

The appearance of the non-data elements of a ggplot2 plot are controlled by a _theme_. To give your plot a theme, add a theme function to your [ggplot2 code template][Make a plot]. ggplot2 comes with nine theme functions, `theme_grey()`, `theme_bw()`, `theme_linedraw()`, `theme_light()`, `theme_dark()`, `theme_minimal()`, `theme_classic()`, `theme_void()`, `theme_test()`, and more can be loaded from the [ggthemes package](https://jrnold.github.io/ggthemes/reference/index.html).

Use the `theme()` function to tweak individual elements of the active theme as in [Remove the legend from a plot].

## Change the colors used in a plot

You want to change the colors that you plot uses to display data. 

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy, color = class)) +
  geom_point() +
  scale_color_brewer(palette = "Spectral")
```

#### Discussion {-}

ggplot2 uses colors for both the `color` and `fill` aesthetics. Determine which one you are using, and then add a new color of fill scale with ggplot2's [scale system](https://r4ds.had.co.nz/graphics-for-communication.html#scales). See the [ggplot2 website](https://ggplot2.tidyverse.org/reference/index.html) for a list of available scales. Additional scales are available in the [ggthemes package](https://jrnold.github.io/ggthemes/reference/index.html).

`scale_color_brewer()`/`scale_fill_brewer()` (for discrete data) and `scale_color_distill()`/`scale_fill_distill()` (for continuous data) are popular choices for pleasing color schemes. Each takes a `palette` argument that can be set to the name of any of the scales displayed below 

```{r fig.height = 8}
# install.packages(RColorBrewer)
library(RColorBrewer)
display.brewer.all()
```

`scale_color_viridis_d()`/`scale_fill_viridis_d()` (for discrete data) and `scale_color_viridis()_c`/`scale_fill_viridis()_c` (for continuous data) are another popular choice for continuous data. Each takes an `option` argument that can be set to one of the palette names below.

```{r echo = FALSE}
knitr::include_graphics(rep('images/viridis.png'))
```

The [`ggsci`](https://nanx.me/ggsci/) and [`wesanderson`](https://github.com/karthik/wesanderson) packages also provide popular color scales.

## Change the range of the x or y axis

You want to change the range of the x or y axes, effectively zooming in or out on your data.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point() +
  geom_smooth() +
  coord_cartesian(xlim = c(5, 7), ylim = c(20, 30)) 
```

#### Discussion {-}

Each ggplot2 plot uses a coordinate system, which can be set by adding a `coord_` function to the [ggplot2 code template][Make a plot]. If you do add a `coord_` function, ggplot2 will use `coord_cartesian()` whihc provides a cartesian coordinate system.

To change the range of a plot, set one or both of the `xlim` and `ylim` arguments of its `coord_` function. Each argument taxes a vector of length two: the minimum and maximum values for the range of the x or y axis.

## Use polar coordinates

You want to make a polar plot, e.g. one that uses polar coordinates.

#### Solution {-}

```{r}
ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
  geom_point() +
  coord_polar(theta = "x")
```

#### Discussion {-}

To draw a plot in a polar coordinate system, add `coord_polar()` to the [ggplot2 code template][Make a plot]. Set the `theta` argument to `"x"` or `"y"` to indicate which axis should be mapped to the angle of the polar coordinate system (defaults to `"x"`).

## Flip the x and y axes

You want to flip the plot along its diagonal, swapping the locations of the x and y axes.

#### Solution {-}

```{r}
ggplot(data = diamonds, mapping = aes(x = cut)) +
  geom_bar() +
  coord_flip()
```

#### Discussion {-}

To flip a plot, add `coord_flip()` to the [ggplot2 code template][Make a plot]. This swaps the locations of the x and y axes and keeps the correct orientation of all words. 

`coord_flip()` has a different effect from merely exchanging the x and y variables. For example, you can use it to make bars and boxplots extend horizontally instead of vertically. 

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