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#R三大绘图系统 #1.基本绘图系统 #1)艺术家的调色板:绘图始于空白帆布 #需要事先计划;支管地实时反映绘图个分析数据的逻辑 #2)两部=图+修饰/添加=执行一系列函数 #3)适于绘制2D图形 #2.Lattice绘图系统 #1)特别适用于变量之间的交互:在变量Z不同水平,变量Y如何随着变量X变化 #2)绘图=使用一次函数调用 #3.ggplot2 #1)The Grammar of Graphics # 图:动词,名词,形容词等. # 数据映射到几何客体的美学属性 #2)基本绘图系统+Lattice绘图系统 # 自动处理标题/文字说明/空间等,但也允许通过添加注释进行修改.查看全部
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#全局参数 par("bg")#背景颜色 par("col")#颜色 par("mar")#(bottom,left,right, right) par("mfrow") par("mfcol") par(mfrow = c(1,2)) hist(airquality$Temp) hist(airquality$Wind) par(mfrow = c(1,1)) boxplot(airquality$Temp)查看全部
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library(ggplot2) ggplot(airquality, aes(Wind, Temp))+ geom_point(aes(color = factor(Month), group = 1,alpha = 0.4, size = 5))+ geom_smooth(method = "lm", se = F, aes(group = 1))#前一个group只输出群体拟合,后一个控制再做一条群体拟合 ggplot(airquality, aes(Wind, Temp)) + geom_point()+ geom_smooth(method = "lm", se = F, aes(group = 1)) ggplot(airquality, aes(Wind, Temp, col = factor(Month))) + geom_point()+ geom_smooth(method = "lm", se = F, aes(group = 1))+ scale_color_manual("Month", values = myColors)+ facet_grid(.~Month)+ theme_classic()查看全部
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library(ggplot2) qplot(Wind, Temp, data = airquality, col = Month, shape = Month, size = Month, xlab = "Wind(mph)", ylab = "Temperature", main = "Wind vs.Temperature" ) qplot(Wind, Temp, data = airquality, geom = c("point", "smooth")) qplot(Wind, Temp, data = airquality, facets = Month~.) qplot(Wind, Temp, data = airquality, facets = .~Month) qplot(Wind, data = airquality, facets = .~Month) qplot(Wind, data = airquality, fill = Month) qplot(Wind, data = airquality, geom = "dotplot")查看全部
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#数据科学家必须具备的只是和技能 #了解数据的特征 #数据可视化 #探索性数据分析 #制作和发布报告查看全部
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#Lattice绘图系统 install.packages("lattice") library(lattice) xyplot(Temp~Ozone,data=airquality) airquality$Month <-factor(airquality$Month) xyplot(Temp~Ozone|Month,data=airquality,layout=c(5,1)) q <- xyplot(Temp~Wind,data=airquality) print(q) set.seed(1)#每次产生的随机数相同 x <- rnorm(100)#随机数服从正态分布 f <- rep(0:1,each=50) y <- x+f-f*x+rnorm(100,sd=0.5) f <- factor(f,labels=c("Group1","Group2")) xyplot(y~x|f,layout=c(2,1)) xyplot(y~x|f,panel=function(x,y){ panel.xyplot(x,y) panel.abline(v=mean(x),h=mean(y),lty=2) panel.lmline(x,y,col="red") })查看全部
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为什么我把ltyp=2后，出来的还是实线而不是虚线呢？查看全部
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#Lattice绘图系统 #xyplot/bwplot/histgram/stripplot/dotplot/splom/levelplot/contourplot #格式:xyplot(y ~ x|f * g, data) #panel,用来控制每个面板内的绘图 #lattice和Base的重要区别 #Base绘图函数直接在图形设备上绘图 #Lattice绘图函数返回trellis类对象 # 打印函数真正执行了在设备上绘图 # 命令执行时, trellis类对象会被自动打印.查看全部
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hist(airquality$Wind, xlab = "wind") boxplot(airquality$Wind, xlab = "wind", ylab = "speed(mpc)") boxplot(Wind ~ Month, airquality, xlab = "wind", ylab = "speed(mpc)") plot(airquality$Wind, airquality$Temp) with(airquality, plot(Wind, Temp, main="Wind and Temp in NYC", type = "n")) with(subset(airquality, Month == 9), points(Wind, Temp, col = "red")) with(subset(airquality, Month == 5), points(Wind, Temp, col = "blue")) with(subset(airquality, Month %in% c(6,7,8)), points(Wind, Temp, col = "black")) fit <- lm(Temp ~ Wind, airquality) abline(fit, lwd = 2) legend("topright", pch = 1, cex = 1, col = c("red", "blue", "black"), legend = c("sep", "May", "Other"))查看全部
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3-3 R语言 基本绘图系统之实践
hist(airquality$Wind,xlab="Wind")(数值型变量风速的柱状图)
boxplot(airquality$Wind,xlab="Wind",ylab="Speed(mph)")(箱图)
boxplot(Wind~Month,airquality,xlab="Month",ylab="Speed(mph)")（一个分类变量和一个数值变量的关系,每个月份的风速）
plot(airquality$Wind,airquality$Temp)(风速和温度的散点图)=with(airquality,plot(Wind,Temp))
title(main="Wind and Temp in NYC")(加标题，可以直接将括号中的命令放入with命令中)
with(airquality,plot(Wind,Temp,main="Wind and Temp in NYC",type="n"))(除了点以外其他的信息都有)
with(subset(airquality,Month==9),points(Wind,Temp,col="red"))（按月份画点，不同月份显示的点有不同的颜色）
with(subset(airquality,Month%in%c(6,7,8)),points(Wind,Temp,col="red"))
fit<-lm(Temp~Wind,airquality)(拟合模型)
abline(fit,lwd=2)
legend("topright",pch=1,col=c("red","blue","black"),legend=c("Sep","May","Other"))(点的颜色代表的含义)
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变量的类型查看全部
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Markdown语法：斜体*文本*，粗体**文本**，标题前添加几个#代表几级标题，无序列表和有序列表，链接，换行（在上一行末尾添加两个空格）
echo=FALSE表示隐藏代码，cache表示缓存
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#最强大的绘图系统-ggplot2
层（Layer）
data 数据 Aesthetics 美学属性 Geometries 几何客体层 Facets 面 Statistics 统计层 Coordinates 坐标系 Themes 主题
绘图函数
#qplot() 类似于base绘图系统中的plot 隐藏了绘图细节 #ggplot() 核心 调用函数本身并不可以绘图
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x <- c(1.2,3,4,5,6) mean(x) #均值 median(x) #中位数 var(x) #方差 sd(x) #标准差 summary(x) #
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par（）:全局参数
bg：背景颜色
mar：做图的时候和边界的边距
las：xy的标签的文字是横排还是竖排
mfrow（mf肉）：把当前画板分成几行几列，并且按照行来填充
mfcol（mfcold）：……列来填充
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