ggthemes

To run this tutorial, you’ll need:

install.packages(c('ggplot2', 'grid', 'gridExtra', 'ggthemes', 'dplyr'))

Loading useful packages - The ggplot2 package is one of the best packages for the production of high-quality plots.

library(ggplot2)
library(grid)
library(gridExtra)
library(ggthemes)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following object is masked from 'package:gridExtra':
## 
##     combine

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

Create my theme

my_theme<-function(base_size=14, base_family="Lucia") {
library(grid)
library(ggthemes)
(theme_foundation(base_size= base_size, base_family=base_family)+ 
theme(plot.margin=unit(c(5,5,10,5),"mm"),
plot.background = element_rect(fill = "white", colour = "black", size = 1),
plot.title = element_text(face = "bold", size = rel(1.2), hjust = 0.5),
axis.title = element_text(face = "bold",size = rel(1)),
axis.title.y = element_text(angle=90,vjust =2),
axis.title.x = element_text(vjust = -0.2),
axis.text = element_text(), 
axis.line = element_line(colour="black"),
axis.ticks = element_line(),
panel.grid.major = element_line(colour="#f0f0f0"),
panel.grid.minor = element_line(colour = "#f0f0f0"),
legend.position = "bottom",
legend.direction = "horizontal",
legend.key.size= unit(0.2, "cm"),
legend.spacing = unit(0, "cm"),
legend.title = element_text(face="italic"),
strip.background=element_rect(colour="#f0f0f0",fill="#f0f0f0"),
strip.text = element_text(face="bold")
))
}

scale_fill<-function(){
 scale_fill_brewer(palette="Spectral")
}  

scale_colour<-function(){
  scale_colour_brewer(palette="PRGn")
}

Making barplots with differents themes

Barplot<-ggplot(mtcars, aes(factor(carb),fill=factor(carb))) +
  geom_bar(alpha=0.7) + 
  ggtitle("Bar Plot") + 
  my_theme()

Barplot

library(gridExtra)
#scales
grid.arrange(Barplot,(Barplot + scale_fill()))

Making scatter plots with differents themes

library("dplyr")

set.seed(1234)
centers <- data.frame(cluster=factor(1:3), size=c(100, 150, 50), x1=c(5, 0, -3), x2=c(-1, 1, -2))
points <- centers %>% group_by(cluster) %>%
    do(data.frame(x1=rnorm(.$size[1], .$x1[1]),
                  x2=rnorm(.$size[1], .$x2[1])))

ggplot(points, aes(x1, x2, color=cluster)) + 
  geom_point(size = 2) + 
  ggtitle("Multivariate gaussian") + 
  my_theme()

Making bubble plots with differents themes

Bubble<-ggplot(mtcars, aes(mpg,disp,colour=factor(carb),size=hp)) + 
  geom_point(alpha=0.7) + 
  ggtitle("Bubble Plot") + 
  scale_size_continuous(range = c(3,10)) + 
  my_theme()

Bubble

library(gridExtra)

#scales
grid.arrange(Bubble,(Bubble + scale_colour()))

Making regression plots with differents themes

set.seed(1234)
dat <- data.frame(cond = rep(c("A", "B"), each=50),
                  xvar = 1:50 + rnorm(50,sd=3),
                  yvar = 1:50 + rnorm(50,sd=3))

ggplot(dat, aes(x=xvar, y=yvar)) +
       geom_point(shape=1) +   
       geom_smooth(method=lm) +
       ggtitle("Linear Regression")+
       my_theme()