No Limits!

class: center, middle, inverse, title-slide

# No Limits!
## Using custom themes to create beautiful visualizations with ggplot2
### Mike Moore
### April 4, 2019

---

class: inverse, middle

# Breaking: Tufte Starts a Tweet Storm!

Rstats coders and users just can't do words on graphics and typography. Proof: 40 years of clunky, even recent Stanford Statistics textbooks. Publication-quality work requires: R + Adobe Illustrator + reasoning about words on graphics + respect for audience/readers/viewers https://t.co/tqFYoZAH5v

- Edward Tufte (@EdwardTufte) June 26, 2018

---

class: inverse

# Making the case for publication quality graphics in R

.pull-left[
Does Tufte have a point? Perhaps.  
  
That said, more and more organizations like BBC News are using R and ggplot2 with custom themes as the backbone for their visualizations
]

.pull-right[

<blockquote class="twitter-tweet" data-lang="en"><p lang="en" dir="ltr">Over the past year the BBC&#39;s data journalists have fundamentally changed the way we produce graphics. Now we've open-sourced the tools we use for making production-ready visuals with <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a> and <a href="https://twitter.com/hashtag/ggplot?src=hash&amp;ref_src=twsrc%5Etfw">#ggplot</a>. <br><br>Find out more here: <a href="https://t.co/G3DhkFfyQD">https://t.co/G3DhkFfyQD</a></p>&mdash; BBC News Graphics (@BBCNewsGraphics) <a href="https://twitter.com/BBCNewsGraphics/status/1091262653631221761?ref_src=twsrc%5Etfw">February 1, 2019</a></blockquote>
<script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

]

---

class: inverse, middle, center

# ggplot2: A quick primer

---

# What is ggplot2?

--

* An package for creating visualizations in R

--

* Created by Hadley Wickham

--

* Based on the Grammer of Graphics by Leland Wilkinson

--

* ggplot2 does not provide a set of pre-defined visualizations but rather a set of components that can be combined together to produce a customized visualization

--

* ggplot2 is a stand alone package but it's also included with the tidyverse which is a collection of packages designed for data analysis

---

# Let's start with a simple graph

.left-code[

```r
*ggplot(mtcars)
```
]

.right-plot[
<img src="index_files/figure-html/simple1-1.png" width="100%" />
]

---

# Let's start with a simple graph

.left-code[

```r
ggplot(mtcars) +
* aes(x = mpg)
```
]

.right-plot[
<img src="index_files/figure-html/simple2-1.png" width="100%" />
]

---

# Let's start with a simple graph

.left-code[

```r
ggplot(mtcars) +
  aes(x = mpg) +
* aes(y = disp)
```
]

.right-plot[
<img src="index_files/figure-html/simple3-1.png" width="100%" />
]

---

# Let's start with a simple graph

.left-code[

```r
ggplot(mtcars) +
  aes(x = mpg) +
  aes(y = disp) +
* ggtitle("A simple graph built up in layers")
```
]

.right-plot[
<img src="index_files/figure-html/simple4-1.png" width="100%" />
]

---

# Let's start with a simple graph

.left-code[

```r
ggplot(mtcars) +
  aes(x = mpg) +
  aes(y = disp) +
  ggtitle("A simple graph built up in layers") +
* geom_point(size = 4)
```
]

.right-plot[
<img src="index_files/figure-html/simple5-1.png" width="100%" />
]

---

# Let's start with a simple graph

.left-code[

```r
ggplot(mtcars) +
  aes(x = mpg) +
  aes(y = disp) +
  ggtitle("A simple graph built up in layers") +
  geom_point(size = 4) +
* aes(color = cyl)
```
]

.right-plot[
<img src="index_files/figure-html/simple6-1.png" width="100%" />
]

---

# Let's start with a simple graph

.left-code[

```r
ggplot(mtcars) +
  aes(x = mpg) +
  aes(y = disp) +
  ggtitle("A simple graph built up in layers") +
  geom_point(size = 4) +
  aes(color = cyl) +
* theme_bw()
```
]

.right-plot[
<img src="index_files/figure-html/simple7-1.png" width="100%" />
]

---

# Download Tableau's Superstore data set
.center-code[

```r
library(lubridate) # package for working with dates

download.file("https://raw.githubusercontent.com/mikemooreviz/superstore/master/superstore.csv", "superstore.csv")

superstore <- read.csv("superstore.csv", header = TRUE)
```

---

ï..Row.ID  Order.ID         Order.Date   Ship.Date    Ship.Mode        Customer.ID   Customer.Name     Segment     Country         City              State         Postal.Code  Region   Product.ID        Category          Sub.Category   Product.Name                                                           Sales   Quantity   Discount      Profit
----------  ---------------  -----------  -----------  ---------------  ------------  ----------------  ----------  --------------  ----------------  -----------  ------------  -------  ----------------  ----------------  -------------  -----------------------------------------------------------------  ---------  ---------  ---------  ----------
         1  CA-2017-152156   2017-11-08   2017-11-11   Second Class     CG-12520      Claire Gute       Consumer    United States   Henderson         Kentucky            42420  South    FUR-BO-10001798   Furniture         Bookcases      Bush Somerset Collection Bookcase                                   261.9600          2       0.00     41.9136
         2  CA-2017-152156   2017-11-08   2017-11-11   Second Class     CG-12520      Claire Gute       Consumer    United States   Henderson         Kentucky            42420  South    FUR-CH-10000454   Furniture         Chairs         Hon Deluxe Fabric Upholstered Stacking Chairs, Rounded Back         731.9400          3       0.00    219.5820
         3  CA-2017-138688   2017-06-12   2017-06-16   Second Class     DV-13045      Darrin Van Huff   Corporate   United States   Los Angeles       California          90036  West     OFF-LA-10000240   Office Supplies   Labels         Self-Adhesive Address Labels for Typewriters by Universal            14.6200          2       0.00      6.8714
         4  US-2016-108966   2016-10-11   2016-10-18   Standard Class   SO-20335      Sean O'Donnell    Consumer    United States   Fort Lauderdale   Florida             33311  South    FUR-TA-10000577   Furniture         Tables         Bretford CR4500 Series Slim Rectangular Table                       957.5775          5       0.45   -383.0310
         5  US-2016-108966   2016-10-11   2016-10-18   Standard Class   SO-20335      Sean O'Donnell    Consumer    United States   Fort Lauderdale   Florida             33311  South    OFF-ST-10000760   Office Supplies   Storage        Eldon Fold 'N Roll Cart System                                       22.3680          2       0.20      2.5164
         6  CA-2015-115812   2015-06-09   2015-06-14   Standard Class   BH-11710      Brosina Hoffman   Consumer    United States   Los Angeles       California          90032  West     FUR-FU-10001487   Furniture         Furnishings    Eldon Expressions Wood and Plastic Desk Accessories, Cherry Wood     48.8600          7       0.00     14.1694
]

---

# Then tidy the data for analysis

```r
store <- superstore %>%
  mutate(Year = year(as.Date(Order.Date))) %>%
  filter(State %in% c('Ohio', 'Indiana', 'Kentucky')) %>%
  select(State, Year, Sales) %>%
  group_by(State, Year) %>%
  summarise(Sales = sum(Sales))
```

<img src="http://garrettgman.github.io/images/tidy-4.png" width="70%" />

http://garrettgman.github.io/tidying/
---

# Lets see what the data looks like

<table>
 <thead>
  <tr>
   <th style="text-align:left;"> State </th>
   <th style="text-align:right;"> Year </th>
   <th style="text-align:right;"> Sales </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> Indiana </td>
   <td style="text-align:right;"> 2015 </td>
   <td style="text-align:right;"> 2936.81 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Indiana </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:right;"> 6640.32 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Indiana </td>
   <td style="text-align:right;"> 2017 </td>
   <td style="text-align:right;"> 25461.78 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Indiana </td>
   <td style="text-align:right;"> 2018 </td>
   <td style="text-align:right;"> 18516.45 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Kentucky </td>
   <td style="text-align:right;"> 2015 </td>
   <td style="text-align:right;"> 8280.46 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Kentucky </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:right;"> 7673.56 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Kentucky </td>
   <td style="text-align:right;"> 2017 </td>
   <td style="text-align:right;"> 5102.89 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Kentucky </td>
   <td style="text-align:right;"> 2018 </td>
   <td style="text-align:right;"> 15534.84 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Ohio </td>
   <td style="text-align:right;"> 2015 </td>
   <td style="text-align:right;"> 14134.85 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Ohio </td>
   <td style="text-align:right;"> 2016 </td>
   <td style="text-align:right;"> 16110.43 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Ohio </td>
   <td style="text-align:right;"> 2017 </td>
   <td style="text-align:right;"> 24748.01 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Ohio </td>
   <td style="text-align:right;"> 2018 </td>
   <td style="text-align:right;"> 23264.85 </td>
  </tr>
</tbody>
</table>

---

# How can we show this data visually?

.left-code[

```r
plot <- ggplot(store, aes(x=Year, y=Sales, 
                          fill=State, 
                          color=State))
*plot
```
]

.right-plot[
<img src="index_files/figure-html/store1-out-1.png" width="100%" />
]

---

# We will plot the points first

.left-code[

```r
plot +
* geom_point()
```
]

.right-plot[
<img src="index_files/figure-html/store2-out-1.png" width="100%" />
]

---

# Now add some lines to the see the trend

.left-code[

```r
plot +
  geom_point() +
* geom_line()
```
]

.right-plot[
<img src="index_files/figure-html/store3-out-1.png" width="100%" />
]

---

# ggplot2 built-in themes

.left-code[

The ggplot2 built-in theme_light() function removes the gray background and puts more focus on the data

```r
plot +
  geom_point() +
  geom_line() +
* theme_light()
```
]

.right-plot[
<img src="index_files/figure-html/store4-out-1.png" width="100%" />
]

---

# Here is another theme

.left-code[

This is theme_minimal().  Notice how we are able to keep removing visual elements?

```r
plot +
  geom_point() +
  geom_line() +
* theme_minimal()
```
]

.right-plot[
<img src="index_files/figure-html/store5-out-1.png" width="100%" />
]

---

background-image: url("https://supercultshow.files.wordpress.com/2013/10/starship-troopers-1.jpg")
background-size: cover

---
# Hadley Wickham

.pull-left[
  ggplot2: Elegant Graphics for Data Analysis  
  https://www.amazon.com/ggplot2-Elegant-Graphics-Data-Analysis/dp/0387981403
]

.pull-right[

<img src="https://images-na.ssl-images-amazon.com/images/I/31uoy-qmhEL._SX331_BO1,204,203,200_.jpg" width="70%" />
]
---
class: inverse, middle, center

# How ggplot2 themes work

---

# Components of a ggplot2 theme

* Plot - background, title, margins

--

* Axis - line, text, title, axis ticks, length of tick marks

--

* Legend - legend background, legend key size, height & width, labels

--

* Panel - panel background, border, grid lines, plot aspect ration

--

* Facet - background of panel strips, strip text, marins between facets

https://ggplot2.tidyverse.org/reference/theme.html
---

class: inverse, middle, center

# Create a custom ggplot2 theme

---

layout: ture
# Some theme elements that can be changed

.left-code[

```r
plot +
* ggtitle("Some theme elements that can be changed!")
```
]

.right-plot[
<img src="index_files/figure-html/plot1-out-1.png" width="100%" />
]

---

# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") + 
* theme(
*   plot.background = element_rect(color="steelblue",
*                                  size=2)
  )
```
]

.right-plot[
<img src="index_files/figure-html/plot2-out-1.png" width="100%" />
]

---
# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=2),
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
*                             face="bold.italic")
  )
```
]

.right-plot[
<img src="index_files/figure-html/plot3-out-1.png" width="100%" />
]

---
# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
*   plot.margin = unit(c(1,1,1.5,1.2),"cm")
  )
```
]

.right-plot[
<img src="index_files/figure-html/plot4-out-1.png" width="100%" />
]

---
# Some theme elements that can be changed
.left-code[
If for some reason you want to remove the axis text...

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
*   axis.text.x = element_blank(),
*   axis.text.y = element_blank()
  )
```
]

.right-plot[
<img src="index_files/figure-html/plot5-out-1.png" width="100%" />
]

---
# Some theme elements that can be changed
.left-code[
Or change the axis label to currency.

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm")
    ) +
  # scale_y_continuous(labels = dollar) +
* labs(x="Sales Years",y="Total Sales")
```
]

.right-plot[
<img src="index_files/figure-html/plot7-out-1.png" width="100%" />
]

---
# Some theme elements that can be changed
.left-code[
Or change the axis label to currency.

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
*   panel.background = element_blank()
    ) +
  # scale_y_continuous(labels = dollar) +
  labs(x="Sales Years",y="Total Sales")
```
]

.right-plot[
<img src="index_files/figure-html/plot8-out-1.png" width="100%" />
]

---
# Some theme elements that can be changed
.left-code[
Or change the axis label to currency.

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
*   panel.background = element_rect(fill = "yellow",
*                               colour = "blue",
*                               size = 1.0, linetype = "dashed")
    ) +
  # scale_y_continuous(labels = dollar) +
  labs(x="Sales Years",y="Total Sales")
```
]

.right-plot[
<img src="index_files/figure-html/plot9-out-1.png" width="100%" />
]

---
# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
    panel.background = element_rect(fill = "yellow",
                                colour = "blue",
                                size = 1.0, linetype = "dashed"),
*   panel.grid.major = element_line(size = 0.5, linetype = 'solid',
*                               colour = "purple"),
*   panel.grid.minor = element_line(size = 1.0, linetype = 'solid',
*                               colour = "green")
    ) +
  # scale_y_continuous(labels = dollar) +
  labs(x="Sales Years",y="Total Sales")
```
]

.right-plot[
<img src="index_files/figure-html/plot10-out-1.png" width="100%" />
]

---

# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
    panel.background = element_rect(fill = "yellow",
                                colour = "blue",
                                size = 1.0, linetype = "dashed"),
    panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "purple"),
    panel.grid.minor = element_line(size = 1.0, linetype = 'solid',
                                colour = "green")               
    ) +
  # scale_y_continuous(labels = dollar) +
  labs(x="Sales Years",y="Total Sales") +
* geom_point(size = 4)
```
]

.right-plot[
<img src="index_files/figure-html/plot11-out-1.png" width="100%" />
]

---

# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
    panel.background = element_rect(fill = "yellow",
                                colour = "blue",
                                size = 1.0, linetype = "dashed"),
    panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "purple"),
    panel.grid.minor = element_line(size = 1.0, linetype = 'solid',
                                colour = "green"),
*   legend.box.background = element_rect()
    ) +
  # scale_y_continuous(labels = dollar) +
  labs(x="Sales Years",y="Total Sales") +
  geom_point(size = 4) 
```
]

.right-plot[
<img src="index_files/figure-html/plot12-out-1.png" width="100%" />
]

---

# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
    panel.background = element_rect(fill = "yellow",
                                colour = "blue",
                                size = 1.0, linetype = "dashed"),
    panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "purple"),
    panel.grid.minor = element_line(size = 1.0, linetype = 'solid',
                                colour = "green"),
    legend.box.background = element_rect(color="#FF00FF", 
                                         size=2, 
                                         linetype="dotted")
    ) +
  # scale_y_continuous(labels = dollar) +
  labs(x="Sales Years",y="Total Sales") +
  geom_point(size = 4) 
```
]

.right-plot[
<img src="index_files/figure-html/plot14-out-1.png" width="100%" />
]

---

# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
    panel.background = element_rect(fill = "yellow",
                                colour = "blue",
                                size = 1.0, linetype = "dashed"),
    panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "purple"),
    panel.grid.minor = element_line(size = 1.0, linetype = 'solid',
                                colour = "green"),
    legend.box.background = element_rect(color="#FF00FF", 
                                         size=2, 
                                         linetype="dotted"),
    legend.position="bottom"
    ) +
  # scale_y_continuous(labels = dollar) +
  labs(x="Sales Years",y="Total Sales") +
  geom_point(size = 4)
```
]

.right-plot[
<img src="index_files/figure-html/plot15-out-1.png" width="100%" />
]

---

# Some theme elements that can be changed
.left-code[

```r
plot +
  ggtitle("Some theme elements that can be changed!") +
  theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
    panel.background = element_rect(fill = "yellow",
                                colour = "blue",
                                size = 1.0, linetype = "dashed"),
    panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "purple"),
    panel.grid.minor = element_line(size = 1.0, linetype = 'solid',
                                colour = "green"),
    legend.box.background = element_rect(color="#FF00FF", 
                                         size=2, 
                                         linetype="dotted"),
    legend.position="bottom",
    strip.background = element_rect(colour = "black", fill = "white")
    ) +
  # scale_y_continuous(labels = dollar) +
  labs(x="Sales Years",y="Total Sales") +
  geom_point(size = 4) +
* facet_wrap(State ~ .)
```
]

.right-plot[
<img src="index_files/figure-html/plot16-out-1.png" width="100%" />
]

---

# Introducting our new theme!

.left-code[

```r
  theme_jurassic <- theme(
    plot.background = element_rect(color="steelblue", size=5) ,
    plot.title = element_text(family="Times", 
                              color="red", 
                              size=14, 
                              face="bold.italic"),
    plot.margin = unit(c(1,1,1.5,1.2),"cm"),
    panel.background = element_rect(fill = "yellow",
                                colour = "blue",
                                size = 1.0, linetype = "dashed"),
    panel.grid.major = element_line(size = 0.5, linetype = 'solid',
                                colour = "purple"),
    panel.grid.minor = element_line(size = 1.0, linetype = 'solid',
                                colour = "green"),
    legend.box.background = element_rect(color="#FF00FF", 
                                         size=2, 
                                         linetype="dotted"),
    legend.position="bottom"
    )
```

```r
plot +
  ggtitle("Wow! Look at my new theme!!!") +
  geom_col() +
  labs(x="Sales Years",y="Total Sales") +
  geom_point(size = 4) +
* theme_jurassic
```
]

.right-plot[
<img src="index_files/figure-html/wow-out-1.png" width="100%" />
]

---

class: center, inverse

background-image: url("https://cdn-images-1.medium.com/max/1600/0*gcOQ0bTIYGdOynR7.jpg")
background-position: center
background-size: cover
---

class: inverse, middle, center

# Built-in ggplot2 themes

---

# Create a base plot

.left-code[

```r
theme_set(theme_gray())
plot <- ggplot(store, aes(x = Year, y = Sales, 
                          fill = State, 
                          color = State))
plot
```
]

.right-plot[
<img src="index_files/figure-html/baseplot-out-1.png" width="100%" />
]

---

# The default ggplot2 theme: theme_gray()

.left-code[

```r
plot + geom_col()
```
]

.right-plot[
<img src="index_files/figure-html/gray-out-1.png" width="100%" />
]

---

# The default ggplot2 theme: theme_gray()

.left-code[

```r
plot + geom_line() +
  geom_point()
```
]

.right-plot[
<img src="index_files/figure-html/grayline-out-1.png" width="100%" />
]

---

# ggplot2 theme: theme_dark()

.left-code[

```r
plot + geom_col() +
  theme_dark()
```
]

.right-plot[
<img src="index_files/figure-html/darkcol-out-1.png" width="100%" />
]

---

# ggplot2 theme: theme_dark()

.left-code[

```r
plot + geom_line() +
  geom_point() +
  theme_dark()
```
]

.right-plot[
<img src="index_files/figure-html/darkline-out-1.png" width="100%" />
]

---

class: inverse, middle, center

# The ggthemes package

---

# The Wall Street Journal

.left-code[

```r
library(ggthemes)

plot + geom_col() +
* theme_wsj() +
* scale_fill_manual(values = wsj_pal(palette = "colors6")(3)) +
* scale_color_manual(values = wsj_pal(palette = "colors6")(3))
```
]

.right-plot[
<img src="index_files/figure-html/wsj-out-1.png" width="100%" />
]

---

# The Wall Street Journal

.left-code[

```r
library(ggthemes)

plot + geom_point() +
  geom_line() +
* theme_wsj() +
* scale_fill_manual(values = wsj_pal(palette = "colors6")(3)) +
* scale_color_manual(values = wsj_pal(palette = "colors6")(3))
```
]

.right-plot[
<img src="index_files/figure-html/wsjl-out-1.png" width="100%" />
]

---

# The Economist

.left-code[

```r
library(ggthemes)

plot + geom_col() +
* theme_economist() +
* scale_fill_manual(values = economist_pal(fill = TRUE)(3)) +
* scale_color_manual(values = economist_pal(fill = TRUE)(3))
```
]

.right-plot[
<img src="index_files/figure-html/econ1-out-1.png" width="100%" />
]

---

# The Economist

.left-code[

```r
library(ggthemes)

plot + geom_point() +
  geom_line() +
* theme_economist() +
* scale_fill_manual(values = economist_pal(fill = TRUE)(3)) +
* scale_color_manual(values = economist_pal(fill = TRUE)(3)) #<<
```
]

.right-plot[
<img src="index_files/figure-html/econ2-out-1.png" width="100%" />
]

---

# The Tufte inspired theme

.left-code[

```r
library(ggthemes)

plot + geom_col() +
* theme_tufte()
```
]

.right-plot[
<img src="index_files/figure-html/tufte1-out-1.png" width="100%" />
]

---

# The Tufte inspired theme

.left-code[

```r
library(ggthemes)

plot + geom_point() +
  geom_line() +
* theme_tufte()
```
]

.right-plot[
<img src="index_files/figure-html/tufte2-out-1.png" width="100%" />
]

---

class: inverse, middle, center

# Other popular themes
---

# hrbrthemes

"A very focused package that provides typography-centric themes and theme components for ggplot2"  
<img src="https://github.com/hrbrmstr/hrbrthemes/blob/master/README_figs/README-unnamed-chunk-12-1.png?raw=true" width="60%" />

https://github.com/hrbrmstr/hrbrthemes

---

# ggpubr

"The 'ggpubr' package provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots"

.pull-left[
<img src="https://rpkgs.datanovia.com/ggpubr/tools/README-ggpubr-1.png" width="60%" />
]

.pull-right[
<img src="https://rpkgs.datanovia.com/ggpubr/tools/README-ggpubr-2.png" width="60%" />
]

https://github.com/kassambara/ggpubr 
---
# tidyquant

"tidyquant integrates the best resources for collecting and analyzing financial data"

<img src="https://github.com/business-science/tidyquant/raw/master/man/figures/sample_img_1_volatility.png" width="50%" />

https://github.com/business-science/tidyquant

---

class: inverse, middle, center

# Styleguides

---

class: inverse, middle, center

# The Sunlight Foundation

---

# Why Data Viz Needs a Style Guide

.pull-left[
.large[Amy Cesal] is a graphic designer specializing in data visualization. She's currently a User Experience contractor for the Veterans Administration. Previously, Amy worked for the federal government as a Technology and Innovation Fellow at the Consumer Financial Protection Bureau and at the nonprofit Sunlight Foundation. Amy also holds a master's degree in Information Visualization from the Maryland Institute College of Art and is a 2017 Information is Beautiful rising star.

twitter: https://twitter.com/AmyCesal  
website: https://www.amycesal.com
]

.pull-right[
<iframe width="560" height="315" src="https://www.youtube.com/embed/SkATiaTJXFU" frameborder="0" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
]
---

# Create consistency
![](https://github.com/mikemooreviz/nolimits/blob/gh-pages/sl1.jpeg?raw=true)

---
# Reduce rework
![](https://github.com/mikemooreviz/nolimits/blob/gh-pages/sl2.jpeg?raw=true)

---
# Build trust
![](https://github.com/mikemooreviz/nolimits/blob/gh-pages/sl3.jpeg?raw=true)

---
# Sunlight Foundation ggplot2 theme
.left-code[

```r
plot +
  ggtitle("Sunlight Foundation ggplot2 R theme") +
  geom_col() +
* theme_sunlight() +
  scale_fill_manual(values = c("#F2DA57", "#E6842A", "#005D6E")) +
  scale_color_manual(values = c("#F2DA57", "#E6842A", "#005D6E"))
```
]

.right-plot[
<img src="index_files/figure-html/sl2-out-1.png" width="100%" />
]

https://github.com/sunlightlabs/chartoff
---

class: inverse, middle, center

# BBC News data team
"At the BBC data team, we have developed an R package and an R cookbook to make the process of creating publication-ready graphics in our in-house style using R's ggplot2 library a more reproducible process, as well as making it easier for people new to R to create graphics."

---
# BBPLOT R Cookbook

![](https://github.com/mikemooreviz/nolimits/blob/gh-pages/bbc.png?raw=true)

---
# A graphic using the bbc_style() theme

.left-code[

```r
library(bbplot)
plot + geom_col() +
  bbc_style() +
  scale_fill_manual(values = c("#FAAB18", "#1380A1","#588300")) +
  scale_color_manual(values = c("#FAAB18", "#1380A1","#588300"))
```
]

.right-plot[
<img src="index_files/figure-html/bbc-out-1.png" width="100%" />
]

https://github.com/bbc/bbplot
---

class: inverse, middle

# Acknowledgments
Thanks to Amy Cesal for leading the way on the use of style guides in data visualiztion.  
https://www.amycesal.com/

Thanks to Yihui Xie for creating the Xaringan package that was used for this presentation.  
https://yihui.name/en/  
  
Thanks to Gina Reynolds whose work showed me what possible using Xaringan.  
https://evangelinereynolds.netlify.com/

Thanks to Garrick Aden-Buie whose work showed me how to use Xaringan.  
https://www.garrickadenbuie.com

Thanks to Hadley Wickahm for ggplot2.  
http://hadley.nz/