R基础绘图

par(mfcol = c(2,3), #mfcol按列排列，mfrow按行排列，c(2,3)两行三列 
    mar = c(2,2,2,2), #margin c(botton, left, top, right) 设置边距
    bg = 'gray')  #backgroud，设置背景颜色

lay <- layout(matrix(c(1,1,2,3), 2, 2, byrow = TRUE), 
              # 2, 2划分为两行两列，byrow = TRUE按行顺数，
              # (1,1,2,3)第一行第一、二列为第一幅图，第二行第一列为第二幅图，第二行第二列为第三幅图
              widths = c(3,2), heights = c(2,3)) #widths = c(3,2)设置第一列比第二列比例为3:2
layout.show(lay) #展示划分结果

plot(1:10, type = "n", xlim = c(0, 10), ylim = c(0,10))

plot(1:10, type = "n", xlim = c(0, 10), ylim = c(0,10))
lines(1:10, abs(rnorm(10)))

plot(1:10, type = "n", xlim = c(0, 10), ylim = c(0,10))
abline(a = 2, b = 1, col = "gray") #y=b*x+a
abline(v = 2, lty = 2) #x=2，vertical
abline(h = 2, lty = 2) #y=2，horizontal

plot(1:10, type = "n", xlim = c(0, 10), ylim = c(0,10))
points(7.5,6)
points(8,8,pch =15)

plot(1:10, type = "n", xlim = c(0, 10), ylim = c(0,10))
abline(a = 2, b = 1, col = "gray") #y=b*x+a
text(7, 7, "abline(a = 2, b = 1)") #文本位置在8,3

plot(1:10, type = "n", xlim = c(0, 10), ylim = c(0,10))
arrows(8, 3.5, 6, 5.7, angle =45 ) 

plot(1:10, type = "n", xlim = c(0, 10), ylim = c(0,10))
segments(1,2,3,4)
segments(rep(3, 4), 6:9, rep(5, 4), 6:9, col = gray(seq(0.2,0.8, length = 4))) 
text(4, 9.8, "segments")

plot(1:10, type = "n", xlim = c(0, 10), ylim = c(0,10))
grid(nx = NULL,ny = NA) 

# install.packages('MSG') 需要先下载R的数据包MSG
library(MSG)

data(BinormCircle)
plot(BinormCircle)

library(MASS)
data(geyser) 
par(mfrow = c(2,2), mar = c(3,3,2,0.5), mgp = c(2, 0.5, 0))
hist(geyser$waiting, main = "(1) freq = TRUE", xlab = "waiting")
hist(geyser$waiting, freq = FALSE, main = "(2) freq = FALSE", xlab = "waiting")
hist(geyser$waiting, breaks = 5, density = 20, xlab = "waiting", main = "(3) breaks = 5") #
hist(geyser$waiting, breaks = 40, col = "red", xlab = "waiting", main = "(4) breaks = 40")

InsectSprays[sample(nrow(InsectSprays), 10), ]

InsectSprays

x <- InsectSprays[,1]

boxplot(x)

par(mar = c(2, 2.5, 0.2, 0.1))
boxplot(count ~ spray, data = InsectSprays, col = "lightgray", 
        horizontal = T, pch = 4) #horizontal = T横向

data(VADeaths)
#install.packages('RColorBrewer')
library(RColorBrewer) #调用调色板
par(mfrow = c(2, 1), mar = c(3, 2.5, 0.5, 0.1))
death = t(VADeaths)[, 5:1] #转置、重新排列年龄段
death

barplot(death, col = brewer.pal(4, "Set1"))
barplot(death, col = brewer.pal(4, "Set1"), 
        beside = TRUE, #beside相邻，不堆叠
        legend = TRUE,#length图例
        horiz = T) #length图例

par(mfcol = c(1,2))
x <- c(95,26,36,78,25,65)
labels <- c("a", "b", "c","d", "e", "f")
pie(x,labels,main = 'Simple Pie Chart')
pct <- round(x/sum(x)*100) #转化百分比
labels2 <- paste(labels,' ',pct,'%',sep = '') #paste连接函数,seperate
labels2

pie(pct,labels2,col = rainbow(length(labels2)),main = 'Pie Chart with Percentages')

par(mfcol = c(1,3),mar = c(4,4,0.5,0.5))
curve(sin(x), from = -2*pi, to = 2*pi, n = 100)
curve(sin(x), from = 0, to = 10, n = 100, add = F,
      type = 'l', xlab = 'x', ylab = 'sin(x)',xlim = c(-2,12), ylim = c(-1.5,1.5))
curve(cos(x), from = -2*pi, to = 2*pi, n = 100)

# install.packages('maps')
library('maps')
map('world')

map('state',boundary = T,col = 'red',fill = T)

#install.packages('geosphere') #绘图的包，用到里面的弧线连线函数
library('geosphere') 

#设置坐标范围使焦点集中在美国周边，并且设置一些有关颜色
xlim <- c(-171.738, -56.602)#经度
ylim <- c(12.039,71.856)#纬度
map('world', col = '#f2f2f2', fill = T, bg = 'white', xlim = xlim, ylim = ylim)

#给定点的位置，在地图中标注出来，比如芝加哥坐标北纬41°39′、西经87°34′,加拿大多伦多北纬43度39分，西经79度23分
points(-87.34,41.39,pch = 12)
points(-79.23,43.39,pch = 15)

#调整经纬度范围
xlim <- c(-100,-50)#经度
ylim <- c(20,50)#纬度
map('world', col = '#f2f2f2', fill = T, bg = 'white', xlim = xlim, ylim = ylim)

#画一条弧线连线，表示社交关系
lon_ca <- -87.34 #longitude 经度
lat_ca <- 41.39 #latitudu 纬度
lon_me <- -79.23
lat_me <- 43.39
lines(c(-87.34,-79.23),c(41.39,43.39),col='red')
inter<- gcIntermediate(c(lon_ca, lat_ca), c(lon_me, lat_me), addStartEnd=TRUE) #addStartEnd=TRUE 连接起始点
lines(inter, col='green')

#装载数据
airports <- read.csv("http://datasets.flowingdata.com/tuts/maparcs/airports.csv", header=TRUE)
flights <- read.csv("http://datasets.flowingdata.com/tuts/maparcs/flights.csv", header=TRUE, as.is=TRUE)
map("world", col="#f2f2f2", fill=TRUE, bg="white", lwd=0.05, xlim=xlim, ylim=ylim)

fsub <- flights[flights$airline == "AA",]
for (j in 1:length(fsub$airline)) {
  air1 <- airports[airports$iata == fsub[j,]$airport1,]   
  air2 <- airports[airports$iata == fsub[j,]$airport2,]
  inter <- gcIntermediate(c(air1[1,]$long, air1[1,]$lat), c(air2[1,]$long, air2[1,]$lat), n=100, addStartEnd=TRUE)
  lines(inter, col="black", lwd=0.8)
}

#R语言地图绘制，底图+数据，会用到ggplot2，暂时跳过
#install.packages('rgdal')
library('rgdal')

#install.packages('mapdata')
library('mapdata')

#install.packages('maptools')
library('maptools')

#install.packages('ggplot2')
library('ggplot2')
#设置路径工作路径
x<-readOGR('./data/bou2_4p.shp',stringsAsFactors=F) 

# head(x) # x
plot(x)

#设置颜色
getColor = function(x, provname, provcol){
  f = function(x, y) ifelse(x %in% y, which(y == x), 0);
  colIndex = sapply(x@data$NAME, f, provname);
  col = c(provcol)[colIndex + 1];
  return(col);
}
provname =c ("北京市", "天津市", "河北省", "山西省", "内蒙古自治区","辽宁省", "吉林省", "黑龙江省", "上海市", "江苏省","浙江省", "安徽省", "福建省", "江西省", "山东省","河南省", "湖北省", "湖南省", "广东省","广西壮族自治区", "海南省", "重庆市", "四川省", "贵州省","云南省", "西藏自治区", "陕西省", "甘肃省", "青海省","宁夏回族自治区", "新疆维吾尔自治区", "台湾省","香港特别行政区")
pop=c(111,28,65,35,18,39,14,43,101,129,428,200,101,162,145,278,4586,277,311,78,46,165,142,12,70,1,63,26,6,12,14,8,10)
provcol = rgb(blue = 1 - pop/max(pop)/2, green = 1-pop/max(pop)/2, red = 0.5)
#最关键的上色
plot(x, col= getColor(x, provname, provcol), xlab = "", ylab = "")