ggplot flipbook

.title[
# ggplot flipbook
]
.subtitle[
## Use <span style="font-size:50px">⇦</span> and <span style="font-size:50px">⇨</span> to navigate.
]
.author[
### Andy Grogan-Kaylor
]
.date[
### 2024-07-28
]

---

@import url('https://fonts.googleapis.com/css2?family=Montserrat&display=swap');
.title-slide { 
  color: #ffcb05;
  background-color: #00274C; 
}
.title-slide h1 {
    color: #ffcb05;
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pre {
  white-space: pre-wrap;
}
h1, h2, h3 {
  font-family: 'Montserrat', sans-serif;
}
body { 
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.author, .date {
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}

</style>

# How To Navigate This Presentation

* Use the <span style="font-size:100px">&#8678;</span> and <span style="font-size:100px">&#8680;</span> keys to move through the presentation.
* Press *o* for *panel overview*.
* This presentation plays a *tone* when each new item appears. Turn the volume down if you find these tones annoying.

Based upon [2 Page ggplot](https://agrogan1.github.io/R/two-page-ggplot2/two-page-ggplot2.pdf)

---
class: animated, slideInRight
# The Essential Idea Of ggplot2 Is Simple

There are 3 essential elements to any ggplot call:

1. An *aesthetic* that tells ggplot which variables are being mapped to the *x axis*, *y axis*, (and often other attributes of the graph, such as the *color fill*).  Intuitively, the aesthetic can be thought of as **what you are graphing**.
2. A *geom* or *geometry* that tells ggplot about the basic structure of the graph.  Intuitively, the geom can be thought of as **how you are graphing it**.
3. Other options, such as a *graph title*, *axis labels* and *overall theme* for the graph.

---
class: animated, slideInRight
# Get Started

---

```r
*library(ggplot2)  # beautiful graphs
```
]
 
.panel2-graph0-auto[

]

---
count: false

```r
library(ggplot2)  # beautiful graphs

*library(ggthemes)  # nice themes
```
]
 
.panel2-graph0-auto[

]

---
count: false

```r
library(ggplot2)  # beautiful graphs

library(ggthemes)  # nice themes
```
]
 
.panel2-graph0-auto[

]

---
class: animated, slideInRight

# One Continuous Variable

---

```r
*ggplot(mydata,  # data
*      aes(x = outcome))   # variable
```
]
 
.panel2-graph1-auto[
<img src="ggplot-flipbook_files/figure-html/graph1_auto_01_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = outcome)) +  # variable
* geom_histogram()
```
]
 
.panel2-graph1-auto[
<img src="ggplot-flipbook_files/figure-html/graph1_auto_02_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = outcome)) +  # variable
  geom_histogram()
```
]
 
.panel2-graph1-auto[
<img src="ggplot-flipbook_files/figure-html/graph1_auto_03_output-1.png" width="432" />
]

---
class: animated, slideInRight

# Add Color

---

```r
ggplot(mydata,  # data
       aes(x = outcome)) +  # variable
  geom_histogram(
    )
```
]
 
.panel2-graph1colorful-non_seq[
<img src="ggplot-flipbook_files/figure-html/graph1colorful_non_seq_01_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = outcome)) +  # variable
  geom_histogram(
*   fill = "red"
    )
```
]
 
.panel2-graph1colorful-non_seq[
<img src="ggplot-flipbook_files/figure-html/graph1colorful_non_seq_02_output-1.png" width="432" />
]

---
class: animated, slideInRight

# An Alternative Geometry

---

```r
ggplot(mydata,  # data
       aes(x = outcome)) +  # variable
  geom_density(
    )
```
]
 
.panel2-graph1A-non_seq[
<img src="ggplot-flipbook_files/figure-html/graph1A_non_seq_01_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = outcome)) +  # variable
  geom_density(
*   fill = "blue"
    )
```
]
 
.panel2-graph1A-non_seq[
<img src="ggplot-flipbook_files/figure-html/graph1A_non_seq_02_output-1.png" width="432" />
]

---
class: animated, slideInRight

# One Categorical Variable

---

```r
ggplot(mydata,  # data
       aes(
         x = group,
       )) +
  geom_bar()  # geometry
```
]
 
.panel2-graph2-non_seq[
<img src="ggplot-flipbook_files/figure-html/graph2_non_seq_01_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(
         x = group,
*        fill = group
       )) +
  geom_bar()  # geometry
```
]
 
.panel2-graph2-non_seq[
<img src="ggplot-flipbook_files/figure-html/graph2_non_seq_02_output-1.png" width="432" />
]

---
class: animated, slideInRight

# Continuous by Continuous

---

```r
ggplot(mydata,  # data
       aes(
         x = predictor,  # variables
         y = outcome,
       )) +
  geom_point()  # geometry
```
]
 
.panel2-graph3-non_seq[
<img src="ggplot-flipbook_files/figure-html/graph3_non_seq_01_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(
         x = predictor,  # variables
         y = outcome,
*        color = group
       )) +
  geom_point()  # geometry
```
]
 
.panel2-graph3-non_seq[
<img src="ggplot-flipbook_files/figure-html/graph3_non_seq_02_output-1.png" width="432" />
]

---
class: animated, slideInRight

# Build A Graph With Better Design Elements

---

```r
*ggplot(mydata,  # data
*      aes(x = predictor,  # variables
*          y = outcome,
*          color = group))
```
]
 
.panel2-graph4-auto[
<img src="ggplot-flipbook_files/figure-html/graph4_auto_01_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = predictor,  # variables
           y = outcome,
           color = group)) +
* geom_point()   # 1st geometry
```
]
 
.panel2-graph4-auto[
<img src="ggplot-flipbook_files/figure-html/graph4_auto_02_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = predictor,  # variables
           y = outcome,
           color = group)) +
  geom_point() +  # 1st geometry
* geom_smooth(size = 3)   # 2nd geometry
```
]
 
.panel2-graph4-auto[
<img src="ggplot-flipbook_files/figure-html/graph4_auto_03_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = predictor,  # variables
           y = outcome,
           color = group)) +
  geom_point() +  # 1st geometry
  geom_smooth(size = 3) +  # 2nd geometry
* labs(title = "My Title", caption = "Colors Inspired by UNICEF", x = "Predictor", y = "Outcome")   # labels
```
]
 
.panel2-graph4-auto[
<img src="ggplot-flipbook_files/figure-html/graph4_auto_04_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = predictor,  # variables
           y = outcome,
           color = group)) +
  geom_point() +  # 1st geometry
  geom_smooth(size = 3) +  # 2nd geometry
  labs(title = "My Title", caption = "Colors Inspired by UNICEF", x = "Predictor", y = "Outcome") +  # labels
* scale_colour_manual(name = "Group", values = c("#6A1E74", "#1CABE2"),  labels = c("group 1", "group 2"))   # manual colors
```
]
 
.panel2-graph4-auto[
<img src="ggplot-flipbook_files/figure-html/graph4_auto_05_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = predictor,  # variables
           y = outcome,
           color = group)) +
  geom_point() +  # 1st geometry
  geom_smooth(size = 3) +  # 2nd geometry
  labs(title = "My Title", caption = "Colors Inspired by UNICEF", x = "Predictor", y = "Outcome") +  # labels
  scale_colour_manual(name = "Group", values = c("#6A1E74", "#1CABE2"),  labels = c("group 1", "group 2")) +  # manual colors
* theme_minimal()   # theme
```
]
 
.panel2-graph4-auto[
<img src="ggplot-flipbook_files/figure-html/graph4_auto_06_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = predictor,  # variables
           y = outcome,
           color = group)) +
  geom_point() +  # 1st geometry
  geom_smooth(size = 3) +  # 2nd geometry
  labs(title = "My Title", caption = "Colors Inspired by UNICEF", x = "Predictor", y = "Outcome") +  # labels
  scale_colour_manual(name = "Group", values = c("#6A1E74", "#1CABE2"),  labels = c("group 1", "group 2")) +  # manual colors
  theme_minimal() +  # theme
* theme(plot.title = element_text(size = rel(5.0), color = "#1CABE2"), plot.caption = element_text(size=rel(2.0)))  # add to theme
```
]
 
.panel2-graph4-auto[
<img src="ggplot-flipbook_files/figure-html/graph4_auto_07_output-1.png" width="432" />
]

---
count: false

```r
ggplot(mydata,  # data
       aes(x = predictor,  # variables
           y = outcome,
           color = group)) +
  geom_point() +  # 1st geometry
  geom_smooth(size = 3) +  # 2nd geometry
  labs(title = "My Title", caption = "Colors Inspired by UNICEF", x = "Predictor", y = "Outcome") +  # labels
  scale_colour_manual(name = "Group", values = c("#6A1E74", "#1CABE2"),  labels = c("group 1", "group 2")) +  # manual colors
  theme_minimal() +  # theme
  theme(plot.title = element_text(size = rel(5.0), color = "#1CABE2"), plot.caption = element_text(size=rel(2.0)))  # add to theme
```
]
 
.panel2-graph4-auto[
<img src="ggplot-flipbook_files/figure-html/graph4_auto_08_output-1.png" width="432" />
]

---
class: animated, slideInRight

# References

Reynolds, E. (2020). _flipbookr: Parses code, creates
partial code builds, delivers code movie_. R package
version 0.1.0.

Wickham, H. (2016). _ggplot2: Elegant Graphics for Data
Analysis_. Springer-Verlag New York. ISBN:
978-3-319-24277-4. URL:
[https://ggplot2.tidyverse.org](https://ggplot2.tidyverse.org).