36-315-Lab2

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# 36-315: Statistical Graphics and Visualization
## Lab 2

Meghan Hall Department of Statistics & Data Science Carnegie Mellon University May 27, 2021

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<div class="my-footer">cmu-36315.netlify.app</div>
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# Today

.large[Reviewing bar charts]
 
.medium[]

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# Standard bar chart

```r
got %>% 
  ggplot(aes(x = region)) +
  geom_bar()
```

.medium[If you don't have a variable on the `y` aesthetic, you don't need a `stat` argument]

.medium[If you *do* have a variable on the `y` aesthetic (whether a count, aggregate, or other data), you need the `stat  = "identity"` argument within `geom_bar()`]

---

# Grouped bar chart

```r
got %>%
  ggplot(aes(x = attacker_king, fill = battle_type)) + 
  geom_bar(position = "dodge")
```

.medium[The `position = "dodge"` argument within `geom_bar()` will created a grouped bar chart, as long as you have a `fill` aesthetic]

---

# Stacked bar chart

```r
got %>% 
  ggplot(aes(x = attacker_king, fill = region)) + 
  geom_bar(position = "stack")
```

.medium[The `position = "stack"` argument within `geom_bar()` will created a stacked bar chart, as long as you have a `fill` aesthetic]

.medium[Be careful using this chart type with a `fill` variable that has too many levels, as it's hard to compare]

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# Percent stacked bar chart

```r
got %>% 
  add_count(attacker_king) %>%
  ggplot(aes(x = attacker_king, y = n, fill = attacker_outcome)) +
  geom_bar(stat = "identity", position = "fill")
```

.medium[The `position = "fill"` argument within `geom_bar()` will created a percent stacked bar chart, as long as you have a `fill` aesthetic and a summary variable on the `y` aesthetic]

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# Upcoming

.large[Lab assignment due 11:30am EDT Friday!]
 
.medium[Ask questions on Piazza if they don't get answered here]

.large[Lecture 4 on Friday May 28]
 
.medium[Histograms and box plots]

.large[Homework 1 due Tuesday June 1]
 
.medium[Will be posted soon]