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<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml" lang="" xml:lang="">
<head>
<title>Create elegant and informative data graphics with ggplot2</title>
<meta charset="utf-8" />
<meta name="author" content="Javier Nogales" />
<meta name="date" content="2018-03-05" />
<link href="index_files/remark-css-0.0.1/default.css" rel="stylesheet" />
<link href="index_files/remark-css-0.0.1/default-fonts.css" rel="stylesheet" />
</head>
<body>
<textarea id="source">
class: left, top
background-image: url("img/uc3m.jpg")
background-position: 90% 90%
background-size: 60%
### <img src="img/UC3M_logo_cc.png" width="50", hspace="20", align="left"> Coding Club UC3M
<br/>
&nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; <img src="img/ggplot2.png" width="150"> **Elegant and Informative Data-Graphics**
### Javier Nogales
---
# First: install ggplot2
```r
install.packages("ggplot2")
library("ggplot2")
```
<br/>
# Even better: install the set of packages tidyverse
```r
install.packages("tidyverse")
library("tidyverse")
```
Includes: ggplot2, dplyr, tidyr, ...
---
# Let's work
Open a dataset:
```r
install.packages("gapminder")
library("gapminder")
```
Socio-economic dataset:
```r
head(gapminder)
```
```
## # A tibble: 6 x 6
## country continent year lifeExp pop gdpPercap
## <fct> <fct> <int> <dbl> <int> <dbl>
## 1 Afghanistan Asia 1952 28.8 8425333 779.
## 2 Afghanistan Asia 1957 30.3 9240934 821.
## 3 Afghanistan Asia 1962 32.0 10267083 853.
## 4 Afghanistan Asia 1967 34.0 11537966 836.
## 5 Afghanistan Asia 1972 36.1 13079460 740.
## 6 Afghanistan Asia 1977 38.4 14880372 786.
```
---
# A histogram in R Base
```r
hist(gapminder$lifeExp, col="lightblue", main="", xlab="Life Exp")
```
<img src="index_files/figure-html/unnamed-chunk-7-1.png" width="60%" />
---
# A histogram in ggplot2
```r
ggplot(gapminder, aes(lifeExp))+geom_histogram(fill="lightblue")+labs(title="")
```
<img src="index_files/figure-html/unnamed-chunk-8-1.png" width="60%" />
---
# A scatter plot in R Base
```r
plot(gapminder$gdpPercap, gapminder$lifeExp, main="", xlab="GDP", ylab="Life Exp")
```
<img src="index_files/figure-html/unnamed-chunk-9-1.png" width="60%" />
---
# A scatter plot in ggplot2
```r
ggplot(gapminder, aes(gdpPercap,lifeExp))+geom_point()+labs(title="")
```
<img src="index_files/figure-html/unnamed-chunk-10-1.png" width="60%" />
---
# So, why ggplot2?
### Based on The Grammar of Graphics
High-level approach
Breaks up graphs into modular logical pieces (semantic components)
Leland Wilkinson, 2005
(statistician and computer scientist at H2O.ai)
### The ggplot2 package
Implementation of the Grammar of Graphics for R
Very flexible, with nice, informative and intuitive plots
Hadley Wickham, 2005
(statistician and chief scientist at RStudio)
---
# Syntax
```
ggplot(data = <DATA>) +
<GEOM_FUNCTION>(
mapping = aes(<MAPPINGS>),
stat = <STAT>,
position = <POSITION>
) +
<COORDINATE_FUNCTION> +
<FACET_FUNCTION>
```
<img src="img/omg.jpg" width="100"/>
<br/>
7 components, but mainly 3...
But so useful in practice: colors, legends, faceting, rendering, ...
---
# What is exactly ggplot2?
<br/>
> "It is a mapping of data variables to aesthetic attributes of geometric objects"
<br/>
<br/>
Three essential components:
- data: *dataframe* with data that we map
- aes: aesthetic attributes (x/y position, color, shape, size, ...)
- geom: the geometric object (points, lines, bars, ...) we want to plot
---
# Let's understand how ggplot2 works
```r
plot = ggplot(gapminder, aes(x = gdpPercap, y = lifeExp))
```
Nothing happens...
---
# Let's understand how ggplot2 works
```r
plot + geom_point()
```
<img src="index_files/figure-html/unnamed-chunk-12-1.png" width="60%" />
---
# Let's understand how ggplot2 works
```r
ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent)) + geom_point()
```
<img src="index_files/figure-html/unnamed-chunk-13-1.png" width="60%" />
---
# Let's understand how ggplot2 works
```r
ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent)) + geom_point() +
* scale_x_log10()
```
<img src="index_files/figure-html/unnamed-chunk-14-1.png" width="60%" />
---
# Let's understand how ggplot2 works
```r
ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent)) + geom_point() +
* scale_x_log10() + theme_minimal() + theme(legend.position="bottom")
```
<img src="index_files/figure-html/unnamed-chunk-15-1.png" width="60%" />
---
# Let's understand how ggplot2 works
Combine layers:
```r
ggplot(gapminder, aes(x = gdpPercap, y = lifeExp, color = continent, size = pop)) +
geom_point(alpha=0.5) + theme_minimal() + theme(legend.position="bottom") +
scale_x_log10(breaks = c(300, 1e3, 3e3, 10e3, 30e3)) +
labs(title = "Gapminder and ggplot2",
x = "Gross Domestic Product (log scale)",
y = "Life Expectancy at birth (years)",
* color = "Continent", size = "Population")
```
In that way, 4D information in a 2D plot...
---
# Let's understand how ggplot2 works
<img src="index_files/figure-html/unnamed-chunk-17-1.png" width="80%" />
---
# Some simple statistical models
```r
ggplot(gapminder, aes(x = gdpPercap, y = lifeExp)) + geom_point() + geom_smooth()
```
<img src="index_files/figure-html/unnamed-chunk-18-1.png" width="70%" />
---
# Let's try bar plots
```r
ggplot(gapminder, aes(x=reorder(continent, continent, length)))+geom_bar(aes(fill=continent))
```
<img src="index_files/figure-html/unnamed-chunk-19-1.png" width="70%" />
---
# Let's try bar plots with polar coordinates
```r
ggplot(gapminder, aes(x=reorder(continent, continent, length)))+geom_bar(aes(fill=continent))+
* coord_polar()
```
<img src="index_files/figure-html/unnamed-chunk-20-1.png" width="70%" />
---
## The syntax is the same!
### Just change the geom function or add more pieces (layers)...
# Let's try boxplots
```r
ggplot(gapminder, aes(x = continent, y = lifeExp)) +
* geom_boxplot(fill="lightblue", outlier.colour = "hotpink") +
geom_jitter(position = position_jitter(width = 0.1, height = 0), alpha = 1/4)
```
---
# Boxplots
<img src="index_files/figure-html/unnamed-chunk-22-1.png" width="80%" />
---
# Densities (and formulas)
```r
ggplot(gapminder,aes(lifeExp))+geom_density(aes(group=continent,colour=continent,fill=continent),alpha=0.1) +
annotate("text", x = 38, y = 0.09, parse = TRUE, size = 8, label = "y==frac(1, sqrt(2*pi)) * e^{-x^2/2}")
```
<img src="index_files/figure-html/unnamed-chunk-23-1.png" width="80%" />
---
# Time Series
```r
gapminder %>%
mutate(gdp=gdpPercap*pop) %>%
group_by(continent,year) %>%
summarize(MeanLifeExp=mean(lifeExp), MeanGDP=mean(gdp)) %>%
ggplot(aes(year,MeanGDP,color=continent)) +
* geom_line()
```
---
# Time Series
<img src="index_files/figure-html/unnamed-chunk-25-1.png" width="80%" />
---
# Facets
```r
ggplot(gapminder, aes(gdpPercap, lifeExp, group=continent, color=year, size=pop)) +
geom_point() +
* facet_wrap(~ continent) +
scale_color_gradient(low="red", high="green") +
theme_minimal()+ theme(legend.position="bottom")
```
---
# Facets
<img src="index_files/figure-html/unnamed-chunk-27-1.png" width="70%" />
---
# Themes and text
```r
gapminder %>% filter(year==2007) %>%
ggplot(aes(x = gdpPercap, y = lifeExp, color = continent, size = pop, label = country)) +
* geom_text() +
# clean the axes names and breaks
scale_x_log10(limits = c(200, 60000)) +
labs(title = "GDP versus life expectancy in 2007",
x = "GDP per capita (log scale)",
y = "Life expectancy") +
# add a nicer theme
* theme_classic() + theme(legend.position="none")
```
---
# Themes and text
<img src="index_files/figure-html/unnamed-chunk-29-1.png" width="80%" />
---
# Correlations
```r
library(GGally)
ggcorr(gapminder[,3:6], label = T)
```
<img src="index_files/figure-html/unnamed-chunk-30-1.png" width="80%" />
---
# Animations
```r
install.packages("gifski")
library(gganimate)
gapminder %>%
ggplot(aes(gdpPercap, lifeExp, size = pop, colour = continent)) +
geom_point(alpha = 0.4) +
geom_text(aes(x = gdpPercap, y = lifeExp + 2, label = country), size=4,
data = filter(gapminder, country %in% c("Spain"))) +
scale_x_log10(limits = c(200, 60000)) +
theme_light() + theme(legend.position = 'bottom') +
labs(title = 'Year: {frame_time}', x = 'GDP per capita (log)', y = 'Life expectancy') +
* transition_time(year) +
* ease_aes('linear')
```
We are going to plot 5D information in a 2D plot...
---
class: center, middle
<img src="img/gganimate.gif" width="800"/>
---
# A little practice and you'll get...
<img src="img/kll4.jpg" width="650"/>
---
# A little practice and you'll get...
Edward Tufte's book: Visual Display of Quantitative Information
<img src="img/Dayton.png" width="1000"/>
---
# A little practice and you'll get...
Publication-ready plots
<img src="img/heatmap.png" width="800"/>
---
# A little practice and you'll get...
Ask the Question, Visualize the Answer (Flowing Data)
<img src="img/male-female.gif" width="650"/>
---
# Final comments
- Input for ggplot2 must be a data.frame
- But there are shortcuts to avoid creating data frames, like qplot
- Easy to save: ggsave("myplot.png")
- Many themes to get different looks to your plots
- Many packages based on ggplot2: factoextra, GGally, gganimate, ...
- It can be integrated in interactive graphics: shyny, ggvis, etc.
<br/>
No excuses: use ggplot2 in your teaching, talks, publications, ...
<br/>
<br/>
> "The purpose of visualization is insight, not pictures" --- Ben Shneiderman
---
# More resources
The main website:
http://ggplot2.tidyverse.org/
The book: ggplot2 (Elegant Graphics for Data Analysis), by Hadley Wickham
https://www.springer.com/us/book/9780387981413
The cheat sheet:
https://www.rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf
The R Graph Gallery:
http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
Top 50 ggplot2 Visualizations
http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html
Getting help (RStudio community)
https://community.rstudio.com
Getting help (stack overflow)
https://stackoverflow.com/questions/tagged/ggplot2
---
background-image: url("img/uc3m.jpg")
background-position: 90% 90%
background-size: 60%
# Thanks
<br/>
### <img src="img/UC3M_logo_cc.png" width="60", hspace="20", align="left"> [**Coding Club**](https://codingclubuc3m.github.io) UC3M
### <img src="img/ggplot2.png" width="60", hspace="20", align="left"> ggplot2 is a part of the [**tidyverse**](https://ggplot2.tidyverse.org) ecosystem
### <img src="img/xaringan.png" width="60", hspace="20", align="left"> Slides created via the R package [**xaringan**](https://github.com/yihui/xaringan)
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