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<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml" lang="" xml:lang="">
<head>
<title>the ggplot glow-up</title>
<meta charset="utf-8" />
<meta name="author" content="Ludmila Janda" />
<link href="libs/remark-css/default.css" rel="stylesheet" />
<link href="libs/remark-css/hygge.css" rel="stylesheet" />
<link href="libs/remark-css/metropolis-fonts.css" rel="stylesheet" />
</head>
<body>
<textarea id="source">
class: center, middle, inverse, title-slide
# the ggplot glow-up
## making lovely data visualizations in R
### Ludmila Janda
### Amplify
### 2019/09/19
---
# Amplify
---
[Glow-up definition](https://twitter.com/zhiiiyang/status/1135743078881304576)
---
### Motivation
---
### Motivation
---
### Motivation
---
### Motivation
- One of the great powers of R is visualization
--
- Yet graphs like this persist
<!-- -->
---
```r
ggplot(diamonds, aes(factor(cut), price)) +
geom_boxplot() +
labs(title = "Diamond Prices By Cut") +
theme_minimal()
```
<!-- -->
---
### Make your own theme!
```r
theme_diamonds <- function(x) {
theme(text = element_text(family = "Luminari"),
axis.text = element_text(size = 10, color = "skyblue"),
axis.title.x =
element_text(size = 12, color = "skyblue", vjust = -3),
axis.title.y =
element_text(size = 12, color = "skyblue", vjust = 6),
axis.line.x = element_line(color = "gold"),
axis.line.y = element_line(color = "gold"),
axis.ticks = element_line(color = "gold"),
plot.title =
element_text(size = 14, face = "bold", color = "skyblue"),
plot.caption = element_text(color = "skyblue"),
plot.margin = margin(t = 0.5, r = 0.5, b = 0.5, l = 0.5, "cm"),
panel.background = element_rect(fill = "white"),
panel.grid.minor = element_blank())
}
```
---
<!-- -->
---
```r
library(scales)
ggplot(diamonds, aes(cut, price)) +
geom_boxplot() +
scale_y_continuous(label = comma) +
labs(x = "Cut", y = "Price", title = "Diamond Prices By Cut") +
theme_diamonds()
```
<!-- -->
---
```r
ggplot(diamonds, aes(cut, price)) +
geom_dotplot(binaxis = "y", stackdir = "center", stackratio = 0.5,
dotsize = 0.5, binwidth = 30, alpha = 0.5) +
scale_y_continuous(label = comma) +
labs(x = "Cut", y = "Price", title = "Diamond Prices By Cut") +
theme_diamonds()
```
<!-- -->
---
```r
ggplot(diamonds, aes(cut, price, color = cut)) +
geom_dotplot(binaxis = "y", stackdir = "center", stackratio = 0.5,
dotsize = 0.5, binwidth = 30, alpha = 0.5) +
gghighlight::gghighlight(cut == "Ideal") +
scale_y_continuous(label = comma) +
labs(x = "Cut", y = "Price", title = "Diamond Prices By Cut") +
theme_diamonds()
```
<!-- -->
---
```r
ggplot(diamonds, aes(price, cut)) +
ggridges::geom_density_ridges(alpha = 0.5,
scale = 1.4, # ridge height/overlap
rel_min_height = 0.001) + # where to draw line
scale_x_continuous(limits = c(0, 22000), # set cutoff
expand = c(0.01, 0), # allow expansion
label = comma) +
scale_y_discrete(expand = c(0.1, 0)) + # padding around graph
labs(x = "Price", y = "Cut", title = "Diamond Prices By Cut") +
theme_diamonds()
```
<!-- -->
---
```r
ggplot(diamonds, aes(price, cut)) +
geom_density_ridges(scale = 1.4, rel_min_height = 0.001, alpha = 0.5,
quantile_lines = TRUE, quantiles = 2) +
scale_x_continuous(limits = c(0, 22000),
expand = c(0.01, 0), label = comma) +
scale_y_discrete(expand = c(0.1, 0)) +
labs(x = "Price", y = "Cut", title = "Diamond Prices By Cut") +
theme_diamonds()
```
<!-- -->
---
```r
library(viridis)
ggplot(diamonds, aes(price, cut, fill = ..x..)) +
geom_density_ridges_gradient(scale = 1.4, rel_min_height = 0.001,
gradient_lwd = 1) + ## add gradient
scale_x_continuous(limits = c(0, 2000),
expand = c(0.01, 0), label = comma) +
scale_y_discrete(expand = c(0.1, 0)) +
viridis::scale_fill_viridis(name = "Price", option = "D") +
labs(x = "Price", y = "Cut", title = "Diamond Prices By Cut") +
theme_diamonds()
```
<!-- -->
---
```r
ggplot(diamonds, aes(price, cut, fill = factor(..quantile..))) +
stat_density_ridges(scale = 1.4, rel_min_height = 0.001,
geom = "density_ridges_gradient", calc_ecdf = TRUE,
quantiles = 4, quantile_lines = TRUE) +
scale_x_continuous(limits = c(0, 22000),
expand = c(0.01, 0), label = comma) +
scale_y_discrete(expand = c(0.1, 0)) +
viridis::scale_fill_viridis(discrete = TRUE, name = "Quartiles") +
labs(x = "Price", y = "Cut", title = "Diamond Prices By Cut") +
theme_diamonds()
```
<!-- -->
---
```r
ggplot(diamonds, aes(price, cut)) +
geom_density_ridges(scale = 1.4, rel_min_height = 0.001,
alpha = 0.5, size = 0.25, jittered_points = TRUE,
point_shape = "|", point_size = 3,
position = position_jitter(height = 0)) +
scale_x_continuous(limits = c(0, 22000),
expand = c(0.01, 0), label = comma) +
scale_y_discrete(expand = c(0.1, 0)) +
labs(x = "Price", y = "Cut", title = "Diamond Prices By Cut") +
theme_diamonds()
```
<!-- -->
---
<!-- -->
---
```r
## FROM: https://orchid00.github.io/tidy_raincloudplot
source("see code above")
lb <- function(x) mean(x) - ((0.5)*sd(x))
ub <- function(x) mean(x) + ((0.5)*sd(x))
sumld <- diamonds %>%
group_by(cut) %>%
summarise(mean = mean(price),
median = median(price),
lower = lb(price),
upper = ub(price))
ggplot(data = diamonds, aes(y = price, x = cut, fill = cut)) +
geom_flat_violin(position = position_nudge(x = .2, y = 0), alpha = .8) +
geom_point(aes(y = price, color = cut),
position = position_jitter(width = .15),
size = .5, alpha = 0.8) +
geom_point(data = sumld, aes(x = cut, y = mean),
position = position_nudge(x = 0.3), size = 2.5) +
geom_errorbar(data = sumld, aes(ymin = lower, ymax = upper, y = mean),
position = position_nudge(x = 0.3), width = 0) +
scale_y_continuous(limits = c(0, 22000),
expand = c(0.01, 0), label = comma) +
scale_x_discrete(expand = c(0.1, 0)) +
labs(x = "Price", y = "Cut", title = "Diamond Prices By Cut") +
guides(fill = FALSE) +
guides(color = FALSE) +
coord_flip() +
theme_diamonds()
```
---
### TidyTuesday
[Github](https://github.com/rfordatascience/tidytuesday), [Shiny app: tidytuesday.rocks](https://nsgrantham.shinyapps.io/tidytuesdayrocks/)
---
```r
plot <-
theme_void() +
theme(text = element_text(family = "Gaegu"),
axis.text = element_text(size = 15, color = "white"),
axis.title = element_text(size = 20, color = "white"),
plot.title = element_text(size = 25,face = "bold",
color = "white", hjust = 0.5),
plot.caption = element_text(color = "white"),
plot.margin = margin(t = 1, r = 3, b = 1, l = 1, "cm"),
axis.title.y = element_text(angle = 90))
ggimage::ggbackground(plot, "chalkboard_simpsons.gif", by = "height")
```
<!-- -->
---
```r
library(magick)
propic <- image_read(here::here("images/propic.png"))
bigdata <- image_read('https://jeroen.github.io/images/bigdata.jpg')
bdl <- image_scale(image_rotate(image_background(propic, "none"), 300), "x150")
ic <- image_composite(image_scale(bigdata, "x400"), bdl, offset = "+170+140")
image_write(ic, here::here("images/ic.png"))
```
---
```r
library(magick)
jared <- image_read(here::here("images/jared.jpeg"))
j1 <- image_annotate(jared, "hey....
I heard you
were the
September speaker
for the meetup",
size = 20,
gravity = "east", color = "white")
image_write(j1, here::here("images/j1.png"))
```
---
```r
f1 <- image_read(here::here("images/fig.png"))
s1 <- image_read(here::here("images/simpsons.jpeg"))
out <- image_composite(f1, s1, offset = "+1600+30")
image_write(out, here::here("images/out.png"))
```
---
```r
ggplot(GOT_pets, aes(fct_infreq(animals_name), fill = species)) +
geom_bar() +
scale_fill_got_d(option = "Targaryen", direction = - 1) +
labs(title = "A Goat Named Arya",
subtitle = "Game of Thrones Inspired (Maybe) Pet Names in Seattle",
x = element_blank(), y = element_blank(), caption = "@MaraAlexeev") +
theme_minimal() +
theme(legend.position = c(0.9, 0.6)) +
labs(fill = "Pet Species") +
theme(text = element_text(size = 9, family = "Cinzel"))
```
<!-- -->
---
### Alluvial Plot
<!-- -->
---
### Alluvial Plot Code
```r
sim_data_pre_post <- read_csv(here::here("sim_data_pre_post.csv")) %>%
select(student, unit_title, assessment, score_level) %>%
mutate(score_level = factor(score_level),
assessment = factor(assessment, levels = c("pre", "post"))) %>%
spread(assessment, score_level) # get wide dataset (pivot_wider)
head(sim_data_pre_post, 5)
```
```
## # A tibble: 5 x 4
## student unit_title pre post
## <dbl> <chr> <fct> <fct>
## 1 1 Dinosaur Domestication 2 4
## 2 1 Earth's Giant Turtle 2 1
## 3 1 Life on Mars 1 2
## 4 1 Potions 1 4
## 5 1 Unicorn Traits and Reproduction 1 4
```
---
### Alluvial Plot Code
```r
sim_data_pre_post <- sim_data_pre_post %>%
ggalluvial::to_lodes_form(key = "assessment", axes = 3:4) # set up dataset
head(sim_data_pre_post, 5)
```
```
## # A tibble: 5 x 5
## student unit_title alluvium assessment stratum
## <dbl> <chr> <int> <fct> <fct>
## 1 1 Dinosaur Domestication 1 pre 2
## 2 1 Earth's Giant Turtle 2 pre 2
## 3 1 Life on Mars 3 pre 1
## 4 1 Potions 4 pre 1
## 5 1 Unicorn Traits and Reproduction 5 pre 1
```
---
### Alluvial Plot Code
```r
sim_data_pre_post %>%
ggplot(aes(x = assessment, # categorical x var (pre or post)
stratum = fct_rev(stratum), # categorical var (score_level)
alluvium = alluvium, # individual/unit (student)
fill = fct_rev(stratum), # color of fill
label = fct_rev(stratum))) +
ggalluvial::geom_flow(alpha = 0.5) +
ggalluvial::geom_stratum() +
scale_fill_manual("Score Level",
values = c("1" = "#4d5050", "2" = "#c2c5c6",
"3" = "#f2ac80", "4" = "#F37321")) +
scale_y_continuous(labels = comma) +
labs(x = "") +
facet_wrap(~unit_title, scales = "free_y") +
theme_minimal() +
theme(panel.border = element_blank(),
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
axis.line = element_line(colour = "grey"),
axis.text.x = element_text(size = 18),
axis.text.y = element_text(size = 14),
strip.text.x = element_text(size = 16),
legend.position = "bottom",
legend.title = element_text(size = 16),
legend.text = element_text(size = 16))
```
---
<!-- -->
---
```r
## FROM: https://mdneuzerling.com/post/my-data-science-job-hunt/
job_outcomes %>%
mutate(final_outcome = coalesce(outcome, `2nd stage`, `1st stage`)) %>%
ggalluvial::to_lodes_form(key = "contact", axes = 2:5) %>%
ggplot(aes(x = contact, stratum = stratum,
alluvium = alluvium, label = stratum)) +
geom_alluvium(aes(fill = final_outcome),
color = "darkgrey", na.rm = TRUE) +
geom_stratum(na.rm = TRUE) +
geom_text(stat = "stratum", na.rm = TRUE, size = 1) +
scale_fill_manual(values = c("ghosted" = "#F0E442",
"no role" = "#CC79A7",
"withdrew" = "#0072B2",
"rejected" = "#D55E00",
"offer" = "#009E73")) +
labs(x = "", fill = "Final Outcome",
caption = "David Neuzerling @mdneuzerling") +
theme_minimal(legend.position = "bottom") +
theme(text = element_text(size = 12))
```
---
<!-- -->
---
```r
plot <- ggplot(df_scores, aes(x = reorder(publisher, average_score),
y = metascore)) +
geom_jitter(aes(color = publisher), size = 5, alpha = 0.25, width = 0.15) +
ggforce::geom_mark_circle(x = 10, y = 94, color = 'grey50',
label.fill = NA, expand = unit(4, "mm")) +
geom_segment(aes(x = publisher, xend = publisher,
y = total_avg, yend = average_score),
size = 0.5, color='gray30') +
geom_point(mapping = aes(x = publisher, y = average_score, fill = publisher),
color = "gray30", shape = 21, size = 7, stroke = 1) +
geom_hline(aes(yintercept = total_avg), color = "gray30", size = 0.5) +
annotate("text", x = 6.6, y = 86, fontface = "bold",
label = 'Average Overall') +
annotate("text", x = 6.3, y = 86,
label = glue::glue('{round(total_avg, 1)} Metascore')) +
annotate("text", x = 2.5, y = 55, fontface = "italic",
label = 'Average per publisher') +
annotate("text", x = 9.7, y = 45, fontface = "bold",
label = 'Worst Game Overall') +
annotate("text", x = 9.4, y = 45,
label = "Rogue Warrior") +
annotate("text", x = 9.6, y = 88, fontface = "bold",
label = 'Best Games Overall') +
annotate("text", x = 9.3, y = 88,
label = "Elder Scroll Series") +
coord_flip() +
scale_y_continuous(limits = c(25, 100))+
theme_minimal() +
guides(color = FALSE, fill = FALSE) +
labs(title = "PC Game Ratings by Publisher",
subtitle = "Ratings based on Metascore out of 100",
caption = "Tanya Shapiro @tanya_shapiro",
x = "", y = 'METASCORE', color = "# of Owners")
```
---
```r
arrows <- tibble(
x1 = c(6.2, #Avg Overall
2.6, #Avg Per Publisher
2.6, #Avg Per Publisher
9.4, #Worst Game
9.7), #Best Game
x2 = c(5.5, #Avg Overall
4.1,
3.1,
9.9,
9.9),
y1 = c(86, #Avg Overall
55, #Avg Per Publisher
55, #Avg Per Publisher
40,
88),
y2 = c(total_avg, #Avg Overall
70.2, #Avg Per Publisher
68.2, #Avg Per Publisher
30,
92))
# add arrows
p <-
plot +
geom_curve(data = arrows, aes(x = x1, y = y1, xend = x2, yend = y2),
arrow = arrow(length = unit(0.07, "inch")), size = 0.6,
color = "gray20", curvature = -0.25)
```
---
[Cédric Scherer, king of #tidytuesday](https://github.com/Z3tt/TidyTuesday)
---
```r
## FROM: https://twitter.com/lpmkremer/status/1168912680767447040?s=21
dat <- bind_rows(
tibble(x = rnorm(7000, sd = 1), y = rnorm(7000, sd = 10), group = "foo"),
tibble(x = rnorm(3000, mean = 1, sd = .5),
y = rnorm(3000, mean = 7, sd = 5), group = "bar"))
ggplot(data = dat, mapping = aes(x = x, y = y)) +
geom_pointdensity(adjust = 3) +
scale_color_viridis() +
theme_minimal()
```
<!-- -->
---
# In Summary
- Change your background
--
- Pick a nice font and font size
--
- Annotate away!
--
- Use ggplot and ggplot adjacent packages
--
- Add images
--
- Follow #TidyTuesday
--
- HAVE FUN!
--
---
### More resources
Take a sad plot and make it better (from Alison Hill:
https://alison.rbind.io/talk/2018-ohsu-sad-plot-better/
BBC Visual and Data Journalism cookbook for R graphics:
https://bbc.github.io/rcookbook/
The Economist:
https://medium.economist.com/mistakes-weve-drawn-a-few-8cdd8a42d368
New way to make alluvial charts:
https://ggforce.data-imaginist.com/reference/geom_parallel_sets.html
You Can Design a Good Chart with R (on the Tufte tweetstorm):
https://medium.com/nightingale/you-can-design-a-good-chart-with-r-5d00ed7dd18e
ggridges gallery: https://cran.r-project.org/web/packages/ggridges/vignettes/gallery.html
---
# Thank you
- Samuel Crane, @samuelcrane and Amplify
- Sebastian Teran Hidalgo, @steranhidalgo
- RLadies-NYC, @RLadiesNYC
- Jared Lander, @jaredlander
- all the #TidyTuesday contributors:
Gil Henriques, @_Gil_Henriques
Mara Alexeev, @MaraAlexeev
David Neuzerling, @mdneuzerling
Tanya Shapiro, @tanya_shapiro
Cédric Scherer, @CedScherer
- the Rstats community
---
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