2-starwars_characters_final.Rmd

---
title: "Star Wars Character Data"
author: "Angela Zoss"
date: "1/30/2020"
output: html_document
---

## Setup your environment

```{r}

# Load required libraries

library(tidyverse)

```

## Load your data

```{r}

# built-in data

starwars_chars <- starwars

```

## Create a plot to explore the height of Star Wars characters

```{r}

# hint: height is numerical; 
# look for geoms that do a good job of summarizing numerical variables

ggplot(starwars_chars) +
  geom_histogram(aes(height))

```

## Facets: Add a facet to the chart to create small multiples for each gender

```{r}

# hint: try facet_wrap

ggplot(starwars_chars) +
  geom_histogram(aes(height)) + 
  facet_wrap(vars(gender))

```

## Create a new plot to compare character heights to weights (masses)

```{r}

# what geom is best for two numerical variables?

ggplot(starwars_chars, aes(height,mass)) +
  geom_point()

```

## Add a linear trend line

```{r}

# hint: look at the options for geom_smooth

ggplot(starwars_chars, aes(height,mass)) +
  geom_point() +
  geom_smooth(method = "lm", se=FALSE)

```


## Data inheritance: Add a label to (only) the heaviest character

```{r}

# hint: you can use "data=" in a geom layer to use different data for that layer 

ggplot(starwars_chars, aes(height,mass)) +
  geom_point() +
  geom_smooth(method = "lm", se=FALSE) + 
  geom_text(data=starwars_chars %>% dplyr::filter(mass > 1000), aes(label=name), nudge_y = -50)

ggplot(starwars_chars, aes(height,mass)) +
  geom_point() +
  geom_smooth(method = "lm", se=FALSE) + 
  geom_text(data=starwars_chars %>% dplyr::filter(mass == max(mass, na.rm=T)), aes(label=name), nudge_y = -50)

```