Introduction to R

class: center, middle, inverse, title-slide

# Introduction to R
### Alex Hollingsworth, Grant McDermott, and Kelli Marquardt
### Indiana University | University of Oregon | Chicago FED
### 2021-07-19

---

# This document was made using R-Markdown.

---
# This document was also made using R-Markdown.
.center[
<img src="figures/personal-website.png" width="75%" />
]
---
# This document was also made using R-Markdown.
.center[
<img src="figures/package-website-and-package.png" width="75%" />
]

---
# Summary statistics table

Now we can use the `datasummary_skim` function.

```r
datasummary_skim(diamonds)
```

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 <thead>
  <tr>
   <th style="text-align:left;">   </th>
   <th style="text-align:right;"> Unique (#) </th>
   <th style="text-align:right;"> Missing (%) </th>
   <th style="text-align:right;"> Mean </th>
   <th style="text-align:right;"> SD </th>
   <th style="text-align:right;"> Min </th>
   <th style="text-align:right;"> Median </th>
   <th style="text-align:right;"> Max </th>
   <th style="text-align:right;">    </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> carat </td>
   <td style="text-align:right;"> 273 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 0.8 </td>
   <td style="text-align:right;"> 0.5 </td>
   <td style="text-align:right;"> 0.2 </td>
   <td style="text-align:right;"> 0.7 </td>
   <td style="text-align:right;"> 5.0 </td>
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   <td style="text-align:left;"> depth </td>
   <td style="text-align:right;"> 184 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 61.7 </td>
   <td style="text-align:right;"> 1.4 </td>
   <td style="text-align:right;"> 43.0 </td>
   <td style="text-align:right;"> 61.8 </td>
   <td style="text-align:right;"> 79.0 </td>
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   <td style="text-align:left;"> table </td>
   <td style="text-align:right;"> 127 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 57.5 </td>
   <td style="text-align:right;"> 2.2 </td>
   <td style="text-align:right;"> 43.0 </td>
   <td style="text-align:right;"> 57.0 </td>
   <td style="text-align:right;"> 95.0 </td>
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   <td style="text-align:left;"> price </td>
   <td style="text-align:right;"> 11602 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3932.8 </td>
   <td style="text-align:right;"> 3989.4 </td>
   <td style="text-align:right;"> 326.0 </td>
   <td style="text-align:right;"> 2401.0 </td>
   <td style="text-align:right;"> 18823.0 </td>
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   <td style="text-align:left;"> x </td>
   <td style="text-align:right;"> 554 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 5.7 </td>
   <td style="text-align:right;"> 1.1 </td>
   <td style="text-align:right;"> 0.0 </td>
   <td style="text-align:right;"> 5.7 </td>
   <td style="text-align:right;"> 10.7 </td>
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   <td style="text-align:left;"> y </td>
   <td style="text-align:right;"> 552 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 5.7 </td>
   <td style="text-align:right;"> 1.1 </td>
   <td style="text-align:right;"> 0.0 </td>
   <td style="text-align:right;"> 5.7 </td>
   <td style="text-align:right;"> 58.9 </td>
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   <td style="text-align:left;"> z </td>
   <td style="text-align:right;"> 375 </td>
   <td style="text-align:right;"> 0 </td>
   <td style="text-align:right;"> 3.5 </td>
   <td style="text-align:right;"> 0.7 </td>
   <td style="text-align:right;"> 0.0 </td>
   <td style="text-align:right;"> 3.5 </td>
   <td style="text-align:right;"> 31.8 </td>
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</td>
  </tr>
</tbody>
</table>
---
# Graphing with `ggplot`
**g**rammar of **g**raphics **plot**

.pull-right[
<img src="figures/ggplot-layers.png" width="75%" />
]

---
# Graphing with `ggplot`
**g**rammar of **g**raphics **plot**

.center[
<img src="figures/ggplot-layers-2.png" width="75%" />
]
---
# Graphing with `ggplot`

.pull-left[

```r
*ggplot(data = diamonds)
```
First add data
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-01-out-1.png)
]
---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
*      aes(y = price, x = carat))
```
Second add aesthetics
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-0-out-1.png)
]
---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat)) +
*   geom_point()
```
Third add geometry
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-1-out-1.png)
]
---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat)) +
    geom_point() +
*   theme_classic()
```
Fourth add theme
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-2-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
base_plot = ggplot(data = diamonds, 
                   aes(y = price, x = carat)) +
    geom_point()

*base_plot +
* theme_classic()
```
Alternative way of making changes to a "base" plot
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-3-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat)) +
*   geom_point(alpha = .1) +
    theme_classic()
```
Exploring geometry options
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-5-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat)) +
    geom_point(alpha = .1) +
    theme_classic() + 
*   theme(text = element_text(size = 18)) +
    labs(title = "Larger diamonds cost more", 
          subtitle = "Price, $",
          y = "", 
          x = "Carat")
```
Change text size
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-6a-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat)) +
    geom_point(alpha = .1) +
    theme_classic() + 
    theme(text = element_text(size = 18)) +
*   labs(title = "Larger diamonds cost more",
*         subtitle = "Price, $",
*         y = "",
*         x = "Carat")
```
Change text options
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-6b-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat)) +
    geom_point(alpha = .1) +
*   facet_wrap(~color) +
    theme_classic() + 
    theme(text = element_text(size = 18)) +
    labs(title = "Larger diamonds cost more", 
          subtitle = "Price, $", 
          y = "",  
          x = "Carat") 
```
Add facets
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-7-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
*      aes(y = price, x = carat, color = clarity)) +
    geom_point(alpha = .1) +
    facet_wrap(~color) +
    theme_classic() + 
    theme(text = element_text(size = 14)) +
    labs(title = "Larger diamonds cost more by diamond color", 
          subtitle = "Price, $",
          y = "", 
          x = "Carat")
```
Add color to points based on clarity of diamond
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-8-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat, color = clarity)) + 
    geom_point(alpha = .1) +
    facet_wrap(~color) +
*   geom_smooth(method = "lm") +
    theme_classic() + 
    theme(text = element_text(size = 14)) +
    labs(title = "Larger diamonds cost more by diamond color", 
          subtitle = "Price, $",
          y = "", 
          x = "Carat")
```
Add regression line
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-9-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat, color = clarity)) + 
*   geom_point(alpha = .1) +
    facet_wrap(~color) +
    geom_smooth(method = "lm") + 
    theme_classic() + 
    theme(text = element_text(size = 14)) +
    labs(title = "Larger diamonds cost more by diamond color", 
          subtitle = "Price, $",
          y = "", 
          x = "Carat")
```
De-clutter by removing points
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-9b-out-1.png)
]

---
# Graphing with `ggplot`

.pull-left[

```r
ggplot(data = diamonds, 
       aes(y = price, x = carat, color = clarity)) + 
    facet_wrap(~color) +
    geom_smooth(method = "lm") + 
    theme_classic() + 
    theme(text = element_text(size = 14)) +
    labs(title = "Larger diamonds cost more by diamond color", 
          subtitle = "Price, $",
          y = "", 
          x = "Carat")
```
De-clutter by removing points
]

.pull-right[
![](introduction-slides_files/figure-html/ggplot-10-out-1.png)
]

---
# Let's switch over to an R-Markdown document

### Also look. Some latex

$$
f(x) = \frac{1}{\sigma\sqrt{2\pi}} 
  \exp\left( -\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^{2}\,\right)
$$
---
# And oh yea, this was made in R too.

.pull-left[
![](figures/montereybay.gif)
]
.pull-right[
- Check out [`rayshader`](https://www.rayshader.com) if you want to make your own awesome map, 2D, and 3D visualization. 
- Source of image: https://wcmbishop.github.io/rayshader-demo/
]
---
exclude: true