R语言ggplot2作图及代码（气泡图、热图、箱图、蜜蜂图、玫瑰图、地图等）

16个ggplot图形及源码

加载相关R包

library(ggplot2)
library(reshape2)
library(lattice)
library(car)
library(tidyverse)
library(giscoR)
library(dplyr)
library(sf)
library(ggbeeswarm)
library(ridgeline)
library(treemapify)

1、散点图

ggplot(data=mtcars, aes(x=wt, y=mpg)) + geom_point(pch=17, color="blue", size=2) + geom_smooth(method="lm", color="red", linetype=2) + labs(title="Automobile Data", x="Weight", y="Miles Per Gallon")+theme_classic()+theme(axis.line = element_line(arrow = arrow(length = unit(0.2, 'cm'))))

2、气泡图

ggplot(mtcars, aes(x=wt, y=mpg, size=disp,color=cyl))+geom_point(alpha=.5) + geom_smooth(method="lm", linetype=1)+theme_classic()+theme(axis.line = element_line(arrow = arrow(length = unit(0.2, 'cm'))))

3、直方图

# Data
set.seed(5)
x <- rnorm(1000)
df <- data.frame(x)
#histogram
ggplot(df, aes(x = x)) + geom_histogram(aes(y = ..density..),colour = 1, fill = "white") +geom_density(lwd = 1, colour = 4,fill = 4, alpha = 0.25)+theme_classic()+theme(axis.line = element_line(arrow = arrow(length = unit(0.2, 'cm')))) #添加箭头

4、蜜蜂图

# Data
set.seed(1995)
y <- round(rnorm(200), 1)
beeswarm <- data.frame(y = y,group = sample(c("G1", "G2", "G3"),size = 200,replace = TRUE))
# Beeswarm
ggplot(beeswarm, aes(x = group, y = y, color = group)) +geom_beeswarm(cex = 3) +scale_color_brewer(palette = "Set1")+theme_classic()+theme(axis.line = element_line(arrow = arrow(length = unit(0.2, 'cm'))))

5、小提琴图

ggplot(singer, aes(x=voice.part, y=height)) + geom_violin(fill="lightblue") + geom_boxplot(fill="lightgreen", width=.2) +theme_classic()+theme(axis.line = element_line(arrow = arrow(length = unit(0.2, 'cm'))))

6、地毯图

ggplot(Salaries, aes(x=rank, y=salary)) + geom_boxplot(fill="cornflowerblue", color="black", notch=TRUE)+ geom_point(position="jitter", color="blue", alpha=.5)+ geom_rug(side="l", color="black")#地毯图

7、密度图

ggplot(data=Salaries, aes(x=salary, fill=rank)) + geom_density(alpha=.3)+theme_classic()+theme(axis.line = element_line(arrow = arrow(length = unit(0.2, 'cm')))) #添加箭头

8、分组密度图

remotes::install_github("R-CoderDotCom/ridgeline@main")
ridgeline(chickwts$weight, chickwts$feed)

9、箱图

ggplot(data=Salaries, aes(x=rank, y=salary, fill=sex)) + geom_boxplot() + scale_x_discrete(breaks=c("AsstProf", "AssocProf", "Prof"), labels=c("Assistant\nProfessor", "Associate\nProfessor", "Full\nProfessor")) + scale_y_continuous(breaks=c(50000, 100000, 150000, 200000), labels=c("$50K", "$100K", "$150K", "$200K")) + labs(title="Faculty Salary by Rank and Gender", x="", y="", fill="Gender") + theme(legend.position=c(.1,.8))

10、热图

# Data
set.seed(8)
m <- matrix(round(rnorm(200), 2), 10, 10)
colnames(m) <- paste("Col", 1:10)
rownames(m) <- paste("Row", 1:10)
# Transform the matrix in long format
heat <- melt(m)
colnames(heat) <- c("x", "y", "value")ggplot(heat, aes(x = x, y = y, fill = value)) +geom_tile(color = "black") +geom_text(aes(label = value), color = "white", size = 4) +scale_fill_gradient2(low = "#075AFF",mid = "#FFFFCC",high = "#FF0000") +coord_fixed()

11、堆积条形图

# Data
set.seed(1)
age <- factor(sample(c("Child", "Adult", "Retired"),size = 50, replace = TRUE),levels = c("Child", "Adult", "Retired"))
hours <- sample(1:4, size = 50, replace = TRUE)
city <- sample(c("A", "B", "C"),size = 50, replace = TRUE)
df <- data.frame(x = age, y = hours, group = city)ggplot(df, aes(x = x, y = y, fill = group)) + geom_bar(stat = "identity") +scale_fill_manual(values = c("#DADAEB", "#9E9AC8", "#6A51A3"))

12、饼图

df <- data.frame(value = c(10, 23, 15, 18),group = paste0("G", 1:4))ggplot(df, aes(x = "", y = value, fill = group)) +geom_col(color = "black") +geom_text(aes(label = value),position = position_stack(vjust = 0.5)) +coord_polar(theta = "y") +scale_fill_brewer() +theme_void()

13、树图

group <- paste("Group", 1:9)
subgroup <- c("A", "C", "B", "A", "A","C", "C", "B", "B")
value <- c(7, 25, 50, 5, 16,18, 30, 12, 41)
df <- data.frame(group, subgroup, value) ggplot(df, aes(area = value, fill = value, label = group)) +geom_treemap() +geom_treemap_text(colour = "white",place = "centre",size = 15,grow = TRUE)

14、玫瑰图

set.seed(4)
df <- data.frame(x = 1:10,y = sample(1:10))
ggplot(df, aes(x = x, y = y, fill = y)) +geom_bar(stat = "identity", color = "white",lwd = 1, show.legend = FALSE)+ coord_polar()

15、地图

ggplot(map_data("world"),aes(long, lat, group = group)) +geom_polygon(fill = "white", colour = 1)

16、地图

# CRS
epsg_code <- 3035
# Countries
EU_countries <- gisco_get_countries(region = "EU") %>%st_transform(epsg_code)
# Centroids for each country
symbol_pos <- st_centroid(EU_countries, of_largest_polygon = TRUE)
# Airports
airports <- gisco_get_airports(country = EU_countries$ISO3_CODE) %>%st_transform(epsg_code)
number_airports <- airports %>%st_drop_geometry() %>%group_by(CNTR_CODE) %>%summarise(n = n())
labels_n <-symbol_pos %>%left_join(number_airports,by = c("CNTR_ID" = "CNTR_CODE")) %>%arrange(desc(n))
# Rescale sizes with log
labels_n$size <- log(labels_n$n / 15)
plot(st_geometry(EU_countries),main = "Airports by country (2013)",sub = gisco_attributions(),col = "white", border = 1,xlim = c(2200000, 7150000),ylim = c(1380000, 5500000))
plot(st_geometry(labels_n),pch = 21, bg = 4,    # Symbol type and colorcol = 4,             # Symbol border colorcex = labels_n$size, # Symbol sizesadd = TRUE)
legend("right",xjust = 1,y.intersp = 1.3,bty = "n",legend = seq(100, 500, 100),col = "grey20",pt.bg = 4,pt.cex = log(seq(100, 500, 100) / 15),pch = 21,title = "Airports")

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R语言ggplot2作图及代码（气泡图、热图、箱图、蜜蜂图、玫瑰图、地图等）

16个ggplot图形及源码

R语言ggplot2作图及代码（气泡图、热图、箱图、蜜蜂图、玫瑰图、地图等）相关推荐

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