Module 03: Introduction to ggplot2

.title[
# Module 03: Introduction to <code>ggplot2</code>
]
.subtitle[
## Rollins COVID-19 Epidemiology Fellowship R Training: Nov 11, 2022
]
.author[
### <a href="https://melindahiggins.netlify.app/">Melinda Higgins</a>
]
.date[
### Director Biostatistics & Data Core </br> School of Nursing - Emory University </br>
]

---

background-size: 80%
background-image: url(img/ggplot2_masterpiece.png)
background-position: 70% 70%
class: center, top

.footnote[
* Illustrations by Allison Horst, RStudio Artist in Residence, <https://github.com/allisonhorst/stats-illustrations>
]

---

# Be an Artist! 
# Create Awesome Figures with `ggplot2`

---

]

---

]

.footnote[[https://www.r-craft.org/r-news/mandalas-colored/](https://www.r-craft.org/r-news/mandalas-colored/)]

---

```r
library(kandinsky)
kandinsky(iris)
```

![](Rworkshop_11Nov2022_Module03_files/figure-html/unnamed-chunk-3-1.png)
]

```r
kandinsky(airquality)
```

![](Rworkshop_11Nov2022_Module03_files/figure-html/unnamed-chunk-4-1.png)

]

.footnote[[Link to Kandinsky Package from Github](http://giorasimchoni.com/2017/07/30/2017-07-30-data-paintings-the-kandinsky-package/)]
---

# Get inspired at R-Graph-Gallery

<img src="img/rgraphgallery_parallel.JPG" width="100%" />
]

]

.footnote[[https://www.r-graph-gallery.com/ggplot2-package.html](https://www.r-graph-gallery.com/ggplot2-package.html)]
---

# R-Graph-Gallery

.footnote[[https://www.r-graph-gallery.com/ggplot2-package.html](https://www.r-graph-gallery.com/ggplot2-package.html)]
---
# R-Graph-Gallery - lollipops and roses

.footnote[[https://www.r-graph-gallery.com/ggplot2-package.html](https://www.r-graph-gallery.com/ggplot2-package.html)]
---

# Make a Scatterplot

Let's look at the Palmer Penguins dataset. Make a scatterplot of

```r
library(palmerpenguins)

# Make a scatterplot
ggplot(penguins) + 
  aes(x=bill_length_mm, 
      y=bill_depth_mm, 
      color = species) + 
  geom_point() +
  xlab("Bill Length (mm)") +
  ylab("Bill Depth (mm)") +
  ggtitle("Penguins Bill Dimensions")
```

_See "module03_Rscript.R" - EXERCISE 01)_

]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/plot-label-out-1.png" width="80%" />
]

---

# Scatterplot - make plot area

```r
# Step 1 specify dataset 
# penguins for ggplot()
*ggplot(penguins)
```

The basic plot space is created.

]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/plot-label1-out-1.png" width="80%" />
]

---

# Scatterplot - add aethetics

```r
# Next add aes (aesthetics)
ggplot(penguins) + 
* aes(x=bill_length_mm,
*     y=bill_depth_mm)
```

Add "aesthetics" using aes - provide the variables for X and Y axes. Notice the `aes()` is added using the `+` operator.

]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/plot-label2-out-1.png" width="80%" />
]

---

# Add a `geom_xxx` - Geometric Object

```r
# Add points to graph
ggplot(penguins) + 
  aes(x=bill_length_mm, 
      y=bill_depth_mm) + 
* geom_point()
```

Add `geom_point()` to add the **points** to the graph.

]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/plot-label3-out-1.png" width="80%" />
]

---

# Add Color - use `aes()`

```r
# Add color aesthetic
ggplot(penguins) + 
  aes(x=bill_length_mm, 
      y=bill_depth_mm,
*     color = species) +
  geom_point() 
```

Add `color` option to the aesthetics inside the `aes()`.

]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/plot-label4-out-1.png" width="80%" />
]

---

# Add Labels - to the axes and add a title

```r
# Add axis labels and a title
ggplot(penguins) + 
  aes(x=bill_length_mm, 
      y=bill_depth_mm,
      color = species) + 
  geom_point() +
* xlab("Bill Length(mm)") +
* ylab("Bill Depth (mm)") +
* ggtitle("Penguins Bill Dimensions")
```

Add axis labels with `xlab()` and `ylab()` and add a title with `ggtitle()`.

]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/plot-label5-out-1.png" width="80%" />
]

---

.footnote[See more themes at [https://ggplot2.tidyverse.org/reference/ggtheme.html](https://ggplot2.tidyverse.org/reference/ggtheme.html)]

# Jazz it up - add a theme

```r
# Add axis labels and a title
ggplot(penguins) + 
  aes(x=bill_length_mm, 
      y=bill_depth_mm,
      color = species) + 
  geom_point() +
  xlab("Bill Length(mm)") + 
  ylab("Bill Depth (mm)") + 
  ggtitle("Penguins Bill Dimensions") +
* theme_dark()
```

]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/plot-label6-out-1.png" width="80%" />
]

---

.footnote[Try `ggthemes` on CRAN [https://cran.r-project.org/web/packages/ggthemes/index.html](https://cran.r-project.org/web/packages/ggthemes/index.html)]

### `ggthemes` package

```r
library(ggthemes)

ggplot(penguins) + 
  aes(x=bill_length_mm, 
      y=bill_depth_mm,
      color = species) + 
  geom_point() +
  xlab("Bill Length(mm)") + 
  ylab("Bill Depth (mm)") + 
  ggtitle("WSJ Theme") +
  theme_wsj()
```
]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/ggtheme1-out-1.png" width="80%" />
]

---

.footnote[See `ggthemr` in development on Github [https://github.com/Mikata-Project/ggthemr](https://github.com/Mikata-Project/ggthemr)]

### `ggthemr` package

```r
library(ggthemr)

ggthemr('pale')
ggplot(penguins,
       aes(x=bill_length_mm, 
           y=bill_depth_mm,
           colour = species)) + 
  geom_point() +
  xlab("Bill Length(mm)") + 
  ylab("Bill Depth (mm)") + 
  ggtitle("ggthemr - pale theme") +
  scale_colour_ggthemr_d()
ggthemr_reset()
```

]

.right-plot[
<img src="Rworkshop_11Nov2022_Module03_files/figure-html/ggthemr1-out-1.png" width="80%" />
]
---

# A Great Resource - R Graphics Cookbook

### [https://r-graphics.org/](https://r-graphics.org/)

and

### [http://www.cookbook-r.com/Graphs/](http://www.cookbook-r.com/Graphs/)

---

.footnote[See code examples at [http://www.cookbook-r.com/Graphs/Plotting_distributions_(ggplot2)/](http://www.cookbook-r.com/Graphs/Plotting_distributions_(ggplot2)/)]

# Make a histogram with overlaid density curve

```r
# Look at flipper_length_mm
# for Palmer Penguins
# Histogram with density curve
# Use y=..density..
# Overlay with transparent density plot
ggplot(penguins, 
       aes(x=flipper_length_mm)) + 
  geom_histogram(aes(y=..density..),      
                 binwidth=2,
                 colour="black", 
                 fill="white") +
  geom_density(alpha=.2, 
               fill="#FF6666") 
```

]

]

---
class: left, middle, inverse

# YOUR TURN [ZOOM BREAKOUT 10 MIN]

### 1. Open module03_Rscript.R
### 2. Do EXERCISE 02
### 3. Do EXERCISE 03

---

# Break out by Facet/Panels

Add `facet_wrap()` to make histogram plots for each penguin species in a different facet or panel.

]

]

---

# Add best fit line to scatterplot

```r
# take out color=species
ggplot(penguins,
       aes(x=bill_length_mm, 
*          y=bill_depth_mm)) +
  geom_point() +
  # add best fit line
  # using lm, linear model
  geom_smooth(method=lm) + 
  xlab("Bill Length(mm)") + 
  ylab("Bill Depth (mm)") + 
  ggtitle("Penguins Bill Depth by Length")
```
]

]

---
# Add `color` back, see how fit lines change

```r
ggplot(penguins,
       aes(x=bill_length_mm, 
           y=bill_depth_mm,
*          color = species)) +
  geom_point() +
  geom_smooth(method=lm) + 
  # add best fit line
  # using lm, linear model
  xlab("Bill Length(mm)") + 
  ylab("Bill Depth (mm)") + 
  ggtitle("Penguins Bill Depth by Length")
```
]

]

---
class: left, middle, inverse

# YOUR TURN [ZOOM BREAKOUT 5-10 MIN]

### 1. Open module03_Rscript.R
### 2. Do EXERCISE 04
### 3. Do EXERCISE 05

---

# Make side-by-side boxplots

```r
# Do boxplots of body_mass_g
# by year as a factor
ggplot(penguins, 
       aes(x=as.factor(year), 
           y=body_mass_g)) + 
  geom_boxplot() + 
  xlab("Year") +   
  ylab("Body Mass (g)") + 
  ggtitle("Body Mass by Year")
```
]

]

---

# Add points over boxplots with jitter

.footnote[Get Ideas at R-Gallery [https://r-graph-gallery.com/89-box-and-scatter-plot-with-ggplot2.html](https://r-graph-gallery.com/89-box-and-scatter-plot-with-ggplot2.html)]

```r
# Do boxplots of body_mass_g
# by year as a factor
# add jitter'ed points
ggplot(penguins, 
       aes(x=as.factor(year), 
           y=body_mass_g)) + 
  geom_boxplot() + 
  geom_jitter(color="black") +
  xlab("Year") +   
  ylab("Body Mass (g)") + 
  ggtitle("Body Mass by Year")
```
]

]
---

# YOUR TURN [ZOOM BREAKOUT 5-10 MIN]

### 1. Open module03_Rscript.R
### 2. Do EXERCISE 06
### 3. Do EXERCISE 07

---

# Pulling it together - make a canvas

# Patchwork!

---

---

```r
library(ggplot2)
library(patchwork)

# save each plot as an object
p1 <- ggplot(penguins, 
         aes(x=bill_length_mm, 
             y=bill_depth_mm, 
             color = species)) +
  geom_point()  
  
p2 <- ggplot(penguins, 
             aes(x=species, 
                 y=bill_length_mm)) + 
  geom_boxplot() + 
  xlab("Species") +   
  ylab("Bill Depth (mm)")

p3 <- 
  ggplot(penguins, 
         aes(x=flipper_length_mm)) + 
  geom_histogram(aes(y=..density..),      
    binwidth=2, colour="black", 
    fill="white") +
  geom_density(alpha=.2, fill="#FF6666") +
  facet_wrap(vars(species))
  
# arrange plots as you like
(p1 | p2) / p3
```

]

![](Rworkshop_11Nov2022_Module03_files/figure-html/plot-patch-out-1.png)

]

---

# YOUR TURN [ZOOM BREAKOUT 5 MIN]

### 1. Open module03_Rscript.R
### 2. Do EXERCISE 08