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mtcars

hist(mtcars$mpg)

hist(mtcars$mpg, breaks=12, col="red") 

1. 数据集：mtcars为一个已知数据集，mpg为mtcars其中一个数据集

2. 间隔：breaks分隔数

3. 颜色：col表示颜色有面积图的颜色；fill表示线、点类的颜色
   

x <- mtcars$mpg

h <- hist(x, breaks=10, col="red", xlab="Miles Per Gallon", main="Histogram with Normal Curve")

print(h)

xfit <-seq(min(x),max(x),length=40)

yfit<-dnorm(xfit,mean=mean(x),sd=sd(x)) 

yfit <- yfit*diff(h$mids[1:2])*length(x)

lines(xfit, yfit, col="blue", lwd=2）

1. h:h为一个数据集

2. 图：该代码描述的是一个组合图

3. 线：yfit<-dnorm（）和lines是加了一条正态曲线
   

counts <- table(mtcars$gear)

barplot(counts, main="Car Distribution", xlab="Number of Gears"）

barplot(counts, main="Car Distribution", horiz=TRUE, names.arg=c("3 Gears", "4 Gears", "5 Gears")）

1. 置换：horiz=TRUE

2. 添加名称：names.arg=c("3 Gears", "4 Gears", "5 Gears")
   

函数：

1.hist(数据，breaks=间隔)

2.barplot(数据集，自由添加)

slices <- c(10, 12, 4, 16, 8)

lbls <- c("US", "UK", "Australia", "Germany", "France")

pie(slices, labels=lbls, main="Pie Chart of Countries"）

1. 赋值：占比赋值slices

2. 标签：lbls

3. 饼图：pie
   

slices <- c(10, 12, 4, 16, 8)

lbls <- c("US", "UK", "Australia", "Germany", "France")

pct <- round(slices / sum(slices) * 100)

print(pct)

lbls <- paste(lbls, pct)

lbls <- paste(lbls, "%", sep="")

pie(slices, labels=lbls, col=rainbow(length(lbls)), main="Pie Chart of Countries")

d <- density(mtcars$mpg)

print(d)

plot(d, xlab="Miles Per Gallon", main="Kernel Density Plot")

polygon(d, col="red", border="blue"）

dotchart(mtcars$mpg,labels=row.names(mtcars),cex=.7,main="Gas Milage for Car Models", xlab="Miles Per Gallon"）

attach(mtcars)

plot(wt, mpg, main="Scatterplot Example", xlab="Car Weight", ylab="Miles Per Gallon", pch=19）

1. 点图
   

2. attach：函数attach() 除了可以用目录路径作为参数，也可以使用数据框。
   

pairs(~mpg+disp+drat+wt, data=mtcars, main="Simple Scatterplot Matrix"）

library(scatterplot3d)

attach(mtcars)

s3d<-scatterplot3d(wt,disp,mpg, pch=16, highlight.3d=TRUE, type="h", main="3D Scatterplot")

fit <- lm(mpg ~ wt+disp)

s3d$plane3d(fit）

boxplot(mpg~cyl, data=mtcars, main="Car Milage Data", xlab="Number of Cylinders", ylab="Miles Per Gallon"）

boxplot(len~supp*dose, data=ToothGrowth, notch=TRUE, col=(c("gold", "darkgreen")), main="Tooth Growth", xlab="Suppliment and Dose"）

library(vioplot)

x1 <- mtcars$mpg[mtcars$cyl==4]

x2 <- mtcars$mpg[mtcars$cyl==6]

x3 <- mtcars$mpg[mtcars$cyl==8]

vioplot(x1, x2, x3, names=c("4 cyl", "6 cyl", "8 cyl"), col="gold")

title("Violin Plots of Miles Per Gallon")

1.应该是箱型图大类的一种

老师说很好看，颜色为屎黄时，一点都不好看的

代码

library(ggplot2)

p <- ggplot(data = mpg, mapping = aes(x = cty, y = hwy))

p + geom_point()

1. 第一步：提取函数

2. 第二部：ggplot(data=?,mapping=aes(x=?,y=?,fill=factor(year)))

3. 第三步：p+geom_point()

4. 说明：aes中的内容一般都是变量，fill=factor(year)表示颜色根据因子year变化
   

library(ggplot2)

p <- ggplot(mpg, aes(x = cty, y = hwy, colour = year))

p + geom_point()+stat_smooth(）

library(ggplot2)

p <- ggplot(mpg, aes(x = cty, y = hwy,size =cty,colour = factor(year)))

p + geom_point(aes(x = cty, y = hwy,size =cty,colour = factor(year)))+stat_smooth(）

 p + geom_point(aes(colour = class, size = displ), alpha = 0.5) +

  stat_smooth() + scale_size_continuous(range = c(4, 10)) + facet_wrap(~ year, ncol = 1）

1. scale_size_continuous(range = c(4, 10))，也就是指定我们size的变化范围

2. facet_wrap(~ year, ncol = 1）将图按year分层，ncol = 1默认分层两列
   

library(ggplot2)

p <- ggplot(mpg, aes(x = cty, y = hwy,size =cty,colour = factor(year)))

p + geom_point(aes(colour = factor(year), size = cty), alpha = 0.5) +stat_smooth() + scale_size_continuous(range = c(4, 10)）

+theme()更偏向于格式的修改

plot.title = element_text(hjust = 0.5)是调整标题的位置‍‍

不加这行，标题会居左，加上才会居中。hjust = 0.5其实就是左右移动的意思，0.5表示居中