01-Visualize.Rmd

---
title: "Data Visualization"
output: html_notebook
editor_options: 
  chunk_output_type: inline
---

<!-- This file by Jake Thompson is licensed under a Creative Commons Attribution 4.0 International License, adapted from the orignal work at https://github.com/rstudio/master-the-tidyverse by RStudio. -->

## Setup

The first chunk in an R Notebook is usually titled "setup," and by convention includes the R packages you want to load. Remember, in order to use an R package you have to run some `library()` code every session. Execute these lines of code to load the packages. 

```{r setup, include = FALSE}
library(tidyverse)
library(fivethirtyeight)
```


## Bechdel test data

We're going to start by playing with data collected by the website FiveThirtyEight on movies and [the Bechdel test](https://en.wikipedia.org/wiki/Bechdel_test). 

To begin, let's just preview our data. There are a couple ways to do that. One is just to type the name of the data and execute it like a piece of code. 

```{r}
bechdel
```

Notice that you can page through to see more of the dataset. 

Sometimes, people prefer to see their data in a more spreadsheet-like format, and RStudio provides a way to do that. Go to the Console and type `View(bechdel)` to see the data preview. 

(An aside-- `View` is a special function. Since it makes something happen in the RStudio interface, it doesn't work properly in R Notebooks. Most R functions have names that start with lowercase letters, so the uppercase "V" is there to remind you of its special status.)


## Consider
What relationship do you expect to see between movie budget (budget) and domestic gross(domgross)?


## Your Turn 1

Run the code on the slide to make a graph. Pay strict attention to spelling, capitalization, and parentheses!

```{r}

```


## Your Turn 2

Add `color`, `size`, `alpha`, and `shape` aesthetics to your graph. Experiment.  

```{r}
ggplot(data = bechdel) +
  geom_point(mapping = aes(x = budget, y = domgross))
```


## Set vs map

```{r}
ggplot(bechdel) + 
    geom_point(mapping = aes(x = budget, y = domgross), color = "blue")
```


## Your Turn 3

Replace this scatterplot with one that draws boxplots. Use the cheatsheet. Try your best guess.

```{r}
ggplot(data = bechdel) +
  geom_point(mapping = aes(x = clean_test, y = budget))
```


## Your Turn 4

Make a histogram of the `budget` variable from `bechdel`.

```{r}

```


## Your Turn 5

Make a density plot of `budget` colored by `clean_test`.

```{r}

```


## Your Turn 6

Make a barchart of `clean_test` colored by `clean_test`.

```{r}

```


## Your Turn 7

Predict what this code will do. Then run it.

```{r}
ggplot(data = bechdel) +
  geom_point(mapping = aes(x = budget, y = domgross)) +
  geom_smooth(mapping = aes(x = budget, y = domgross))
```


## global vs local

```{r}
ggplot(data = bechdel, mapping = aes(x = budget, y = domgross)) +
  geom_point(mapping = aes(color = clean_test)) +
  geom_smooth()
```

```{r}
ggplot(data = bechdel, mapping = aes(x = budget, y = domgross)) +
  geom_point(mapping = aes(color = clean_test)) +
  geom_smooth(data = filter(bechdel, clean_test == "ok"))
```


## Your Turn 8

Add a position adjustment to this plot to compare the frequency of test results across decades.

```{r}
ggplot(data = bechdel, mapping = aes(x = decade_code)) +
  geom_bar(mapping = aes(fill = clean_test))
```


## Saving plots

Save the last plot. If you run your `ggsave()` code inside this notebook, the image will be saved in the same directory as your .Rmd file but if you run `ggsave()` in the Console it will be in your working directory. You can manually set the directory with the `path` argument. 

```{r}
ggsave("my-plot.png", width = 8, height = 6, units = "in", dpi = "retina")
```

***

# Take aways

You can use this code template to make thousands of graphs with **ggplot2**.

```{r eval = FALSE}
ggplot(data = <DATA>) +
  <GEOM_FUNCTION>(mapping = aes(<MAPPINGS>),
                  stat = <STAT>, position = <POSITION>) +
  <FACET_FUNCTION> +
  <SCALE_FUNCTION> +
  <THEME_FUNCTION>
```