R语言数据可视化.ppt

1,语言,数据可视化,2,学习内容,一 R绘图基础 二 各类图形绘制 三 习题和资料,为什么要学习R语言,R是 一个开放(GPL)的统计编程环境 一种语言，是语言(由AT qqline(y, col = 2) #和正态分布比 qqplot(y, rt(300, df = 5); #和t(5)分布比 data(precip) qqnorm(precip, ylab = “Precipitation in/yr for 70 US cities”); qqline(precip,col=3) #和正态分布比 par(mfrow=c(1,1),QQ图,24,data(iris) pairs(iris1:4, main = Andersons Iris Data - 3 species, pch = 21, bg = c(red, green3, blue)codes(iris$Species) #iris为1505数据,这里是4个数量变量的点图(最后一个是分类变量(iris$Species),散点图矩阵,par(bg = cornsilk) data(quakes) coplot(lat long | depth, data = quakes, pch = 21, bg = green3)#Hit to see next plot:,25,条件分割图,x - seq(-10, 10, length= 30) y - x f - function(x,y) r - sqrt(x2+y2); 10 * sin(r)/r z - outer(x, y, f) zis.na(z) - 1 persp(x, y, z, theta = 30, phi = 30, expand = 0.5, col = lightblue),26,三维透视图,27,data(volcano) rx - range(x - 10*1:nrow(volcano) ry - range(y - 10*1:ncol(volcano) ry - ry + c(-1,1) * (diff(rx) - diff(ry)/2 tcol - terrain.colors(12) par(opar); opar - par(pty = s, bg = lightcyan) plot(x = 0, y = 0,type = n, xlim = rx, ylim = ry, xlab = , ylab = ) u - par(usr) rect(u1, u3, u2, u4, col = tcol8, border = “red”) #rect画矩形 contour(x, y, volcano, col = tcol2, lty = solid, add = TRUE, vfont = c(sans serif, plain) title(A Topographic Map of Maunga Whau, font = 4) abline(h = 200*0:4, v = 200*0:4, col = lightgray, lty = 2, lwd = 0.1);par(opar),等高线图,28,等高线图,29,data(volcano) x - 10*(1:nrow(volcano) y - 10*(1:ncol(volcano) image(x, y, volcano, col = terrain.colors(100), axes = FALSE) contour(x, y, volcano, levels = seq(90, 200, by=5), add = TRUE, col = peru) axis(1, at = seq(100, 800, by = 100) axis(2, at = seq(100, 600, by = 100) box() title(main = Maunga Whau Volcano, font.main = 4),颜色图,30,颜色图,ggplot2,31,32,ggplot2简介,33,为什么要使用ggplot2,34,Ggplot2的基本概念,35,数据（data）和映射（mapping）,36,几何对象（Geometric）,37,统计变换（statistics）,38,坐标（coordinate）,39,图层（layer）,40,分面（facet）,41,42,43,三 习题和资料,44,练习1：绘图,生成0到2之间的50个随机数，分别命名为x,y x - runif(50,0,2) y - runif(50,0,2) 绘图：将主标题命名为“散点图”， 横轴命名为”横坐标”， 纵轴命名为“纵坐标” plot(x, y, main=散点图, xlab=横坐标, ylab=纵坐标) text(0.6,0.6,text at (0.6,0.6) abline(h=.6,v=.6),45,图 练习1:绘图举例,46,练习2：分步绘图,1.打开绘图窗口，不绘制任何对象 plot(x, y, type=n, xlab=, ylab=, axes=F) #用练习1的x、y值 2.添加坐标点 points(x,y) 3.添加坐标轴 axis(1); axis(at=seq(0.2,1.8,0.2), side=2) 4.补齐散点图的边框 box() 5.添加标题、副标题、横轴说明、纵轴说明 title(main=Main title, sub=subtitle, xlab=x-label, ylab=y-label),47,图 练习2:分步绘图,48,教材,Crawley Statistics an introduction using R Peter Dalgaard Introductory statistics with R E. Paradis R for Beginners Verzani SimpleR. D G Rossiter Introduction to the R Project for Statistical Computing for use at ITC J. Maindonald Using R for data analysis and graphics introduction code and commentary using R Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S,49,R网络资源,R主页: http:/www.r-project.org R资源列表 NCEAS http:/www.nceas.ucsb.edu/scicomp/software/r 统计之都: http:/cos.name/ QuikR R数据挖掘 http:/www.RdataM 在线数据分析协作平台 R- 大数据分析的众包平台-Kaggle ,50,谢谢！,