1.绘制散点图
# 使用ggplot2
library(ggplot2)
ggplot(data = mtcars, aes(x = wt, y = mpg)) + geom_point()
2.绘制折线图
# 使用ggplot
library(ggplot2)
# 绘制第一条折线附有数据点
g <- ggplot(data = pressure, aes(x = temperature, y = pressure)) +
geom_line(color = "blue") +
geom_point(color = "blue") g + # 绘制第二条折线附有数据点
geom_line(data = pressure, aes(temperature, pressure/2), color = "red") +
geom_point(data = pressure, aes(temperature, pressure/2), color = "red")
3.绘制条形图
# 使用ggplot2(左图)
library(ggplot2)
g <- ggplot(data = BOD, aes(x = Time, y = demand)) +
geom_bar(stat = "identity") # 调用
g # =========================================================== # 使用factor是为了离散x轴取值,这样没有多余的间隔（右图）
library(ggplot2)
g <- ggplot(data = BOD, aes(x = factor(Time), y = demand)) +
geom_bar(stat = "identity") # 调用
g
4.绘制直方图
# 绘制直方图 "+" 运算通过赋值在调用
library(ggplot2)
g <- ggplot(data = mtcars, aes(x = mpg)) +
geom_histogram(binwidth = 4) # 调用
g
5.绘制函数图
# 使用ggplot2
# 设置函数
myFun <- function(x){
1/x
} g <- ggplot(data = data.frame(x = c(0, 20)), aes(x = x)) +
stat_function(fun = myFun, geom = "line", col = "red") # col设置颜色 # 调用
g