T is for Themes

April 23, 2020
By

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One of the easiest ways to make a beautiful ggplot is by using a theme. ggplot2 comes with a variety of pre-existing themes. I’ll use the genre statistics summary table I created in yesterday’s post, and create the same chart with different themes.

library(tidyverse)
## -- Attaching packages ------------------------------------------- tidyverse 1.3.0 --
##  ggplot2 3.2.1      purrr   0.3.3
## tibble 2.1.3 dplyr 0.8.3
## tidyr 1.0.0 stringr 1.4.0
## readr 1.3.1 forcats 0.4.0
## -- Conflicts ---------------------------------------------- tidyverse_conflicts() --
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
reads2019 <- read_csv("~/Downloads/Blogging A to Z/SaraReads2019_allrated.csv",
col_names = TRUE)
## Parsed with column specification:
## cols(
## Title = col_character(),
## Pages = col_double(),
## date_started = col_character(),
## date_read = col_character(),
## Book.ID = col_double(),
## Author = col_character(),
## AdditionalAuthors = col_character(),
## AverageRating = col_double(),
## OriginalPublicationYear = col_double(),
## read_time = col_double(),
## MyRating = col_double(),
## Gender = col_double(),
## Fiction = col_double(),
## Childrens = col_double(),
## Fantasy = col_double(),
## SciFi = col_double(),
## Mystery = col_double(),
## SelfHelp = col_double()
## )
genrestats <- reads2019 %>%
filter(Fiction == 1) %>%
arrange(OriginalPublicationYear) %>%
group_by(Childrens, Fantasy, SciFi, Mystery) %>%
summarise(Books = n(),
WomenAuthors = sum(Gender),
AvgLength = mean(Pages),
AvgRating = mean(MyRating))

genrestats <- genrestats %>%
bind_cols(Genre = c("General Fiction",
"Mystery",
"Science Fiction",
"Fantasy",
"Fantasy SciFi",
"Children's Fiction",
"Children's Fantasy")) %>%
ungroup() %>%
select(Genre, everything(), -Childrens, -Fantasy, -SciFi, -Mystery)

genre <- genrestats %>%
ggplot(aes(Genre, Books)) +
geom_col() +
scale_y_continuous(breaks = seq(0,20,1))

Since I’ve created a new object for my figure, I can add a theme by typing genre + [theme]. Here’s a handful of the ggplot2 themes.

You can also get more themes with additional packages. My new favorite is ggthemes. I’ve been loving their Economist themes (particularly economist_white), which I’ve been using for most of the plots I create at work. Here are some of my favorites.

You can also customize different elements of the plot with theme(). For instance, theme(plot.title = element_text(hjust = 0.5)) centers your plot title. theme(legend.position = “none”) removes the legend. You could do both of these at once within the same theme() by separating them with commas. This is a great way to tweak tiny elements of your plot, or if you want to create your own custom theme.

library(ggthemes)
## Warning: package 'ggthemes' was built under R version 3.6.3
genre +
theme_economist_white() +
theme(plot.background = element_rect(fill = "lightblue"))

These themes also have color schemes you can add to your plot. We’ll talk about that soon!

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