选择不同的ggplot画图主题

Ploting
Author

Tony Duan

Published

October 12, 2022

1. 线型图

Code 
library(gapminder)
library(tidyverse)
library(plotly)
library(ggpubr)
Code 
gapminder_data=gapminder 
glimpse(gapminder_data)
Rows: 1,704
Columns: 6
$ country   <fct> "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", …
$ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, …
$ year      <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, …
$ lifeExp   <dbl> 28.801, 30.332, 31.997, 34.020, 36.088, 38.438, 39.854, 40.8…
$ pop       <int> 8425333, 9240934, 10267083, 11537966, 13079460, 14880372, 12…
$ gdpPercap <dbl> 779.4453, 820.8530, 853.1007, 836.1971, 739.9811, 786.1134, …

准备数据

Code 
gapminder_data_cn_us_2007=gapminder_data %>%  filter(country %in% c('China','United States')) %>% filter(year==year)

gapminder_data_cn_2007=gapminder_data %>%  filter(country %in% c('China')) %>% filter(year==year)

gapminder_data_2007=gapminder_data %>% filter(year==2007)

glimpse(gapminder_data_cn_us_2007)
Rows: 24
Columns: 6
$ country   <fct> "China", "China", "China", "China", "China", "China", "China…
$ continent <fct> Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, Asia, …
$ year      <int> 1952, 1957, 1962, 1967, 1972, 1977, 1982, 1987, 1992, 1997, …
$ lifeExp   <dbl> 44.00000, 50.54896, 44.50136, 58.38112, 63.11888, 63.96736, …
$ pop       <int> 556263527, 637408000, 665770000, 754550000, 862030000, 94345…
$ gdpPercap <dbl> 400.4486, 575.9870, 487.6740, 612.7057, 676.9001, 741.2375, …
Code 
gapminder_data_cn=gapminder_data %>%  filter(country %in% c('China')) %>% filter(year==year)


gapminder_data_us=gapminder_data %>%  filter(country %in% c('United States')) %>% filter(year==year)



gapminder_data_cn_us=gapminder_data %>%  filter(country %in% c('China','United States')) %>% filter(year==year)

中国VS美国人均GPD的线性图,更改主题

Code 
ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "中国VS美国人均GPD",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")

Show the code 
# theme_bw
theme_bw=ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_bw 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")+
  theme_bw()

# theme_classic
theme_classic=ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_classic 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")+
  theme_classic()

# theme_dark
theme_dark=ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_dark 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")+
  theme_dark()

# theme_void
theme_void=ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_void 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")+
  theme_void()

ggarrange(theme_bw,theme_classic,theme_dark,theme_void)

Show the code 
library(ggthemes)

#theme_base
theme_base=ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_base 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")+
  theme_base()

#theme_calc 
theme_calc=ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_calc 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")+
  theme_calc()+scale_fill_calc()

# theme_economist
theme_economist=ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_economist 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")+
  theme_economist()+scale_fill_economist()

# theme_gdocs
theme_gdocs=ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_gdocs 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")+
  theme_gdocs()+scale_fill_gdocs()



ggarrange(theme_base,theme_calc,theme_economist,theme_gdocs)

ggthemr包会将全部ggplot变为一个主题，如果要重置需要用ggthemr_reset()

Show the code 
#devtools::install_github('Mikata-Project/ggthemr')
library(ggthemr)

#flat/dust/fresh/sky/sea
ggthemr_reset()
ggthemr("flat")

ggplot(data=gapminder_data_cn_us, aes(x=year, y=gdpPercap,color=country)) +
  geom_line()+
  geom_point()+
  labs(
    title = "theme_base 主题",
    subtitle = "1952年到2007年",
    caption = "数据来源: Gapminder dataset",
  )+
  ylab("人均GPD")+
  xlab("年")

Show the code 
ggthemr_reset()
ggsave("feature.png")

Reference

https://r-charts.com/ggplot2/themes/