R 语言常用命令

R语言 常用命令

1. 数据读取

1.1 读取网页

library(httr) 
library(curl) 
library(rvest) 
tryCatch(read_html(url, error=function(err) "Error 404")!="Error 404"  # 保证网页存在
page = read_html(url, encoding="GBK")             # 读取网页内容，指定编码为gbk
page=as(page, "character")
write.csv(page,file="page.csv")       
page=data.frame(var=readLines("page.csv"),stringsAsFactors = F) 
abc=data.frame(var=str_subset(page$var, "abc"))   # 提取包含abc的行

1.2 读取文本

data=read.csv("a.txt",sep="\t",encoding="UTF-8",fill=T,stringsAsFactors = F,quote = "")
data=read.table("a.txt",encoding="UTF-8",stringsAsFactors=FALSE,sep="\t",quote="")
data=data.frame(V1=readLines("a.txt",encoding="UTF-8"),stringsAsFactors = F) # 逐行读，含中文
# 给表格Ta加表头
colnames(Ta)=colnames(read.table("clipboard",sep="\t",header=T))

1.3 批量下载

links="http://.."
page <- links %>% read_html() 
page=as(page, "character")
write.csv(page,file="page.csv")       
page=data.frame(var=readLines("page.csv"),stringsAsFactors = F) 
filelist=data.frame(var=str_subset(page$var, "<a href=\"\""),stringsAsFactors = F)%>%
    mutate(link=sub(".*<a href=\"\"","",var))%>%
    mutate(link=sub("\"\">.*","",link))
filelist=str_subset(filelist$link, "[.]") # 多种文件格式，.pdf, .dta等
for (i in 1:nrow(filelist)){
    filename=paste(links,filelist[i],sep="")
    filename=sub("amp;","",filename)
    destfile=paste("D:\\...", #目标文件夹
                   filelist[i],sep="")
    download.file(filename,destfile=destfile,mode="wb")
}

2. 数据处理

2.1 字符处理

正则表达式：http://www.cnblogs.com/zxin/archive/2013/01/26/2877765.html
# 大小写转换
library(stringr)  #加载包
dog <- "The quick brown dog"
str_to_upper(string = dog)  #转换成大写 "THE QUICK BROWN DOG"
str_to_lower(string = dog)  #转换成小写 "the quick brown dog"
str_to_title(string = dog)  #单词首字母转换大写 "The Quick Brown Dog"
gsub("[:a-z:]","",dog)      #去掉所有小写字母
gsub("[:A-Z:]","",dog)      #去掉所有小写字母

# ABC 包含几个编号（如一篇文章的JEL、Author等），将其分解，存为名为ABC的变量
list=strsplit(data$ABC,";")                   # 将ABC用；分拆为列表，每个元素为字符向量
names(list)=data$idno                         # 用idno命名各元素（如文章编号）
ABC=data.frame(idno=rep(names(list),sapply(list,length)), 
               ABC=unlist(list),stringsAsFactors = F)  # 将列表转换为数据框

3. 作图

+ geom_abline(slope = 1)+               # 加对角线
  geom_text_repel(aes(label=label))+    # library(ggrepel)，点的文本分开
  labs(title="",x="",y="")+
  scale_x_continuous(breaks = c(1997, 2003, 2008, 2014))+
  guides(fill=guide_legend(title=NULL))+ theme_bw()+ theme(legend.position="non")

4. 运算

4.1 矩阵重复

kronecker(matrix(1, M, N), A) # 矩阵A行方向复制M次、列方向复制N次
kronecker(diag(1, N), A)      # 以A为对角元素的对角阵

4.2 符号计算

# 微分
expFun=expression(a*x^2)                                 # 表达式
expFun
a=0.5; x=2; eval(expFun)                                 # 求表达式在a=0.5, x=1处的值
Fun=as.function(alist(x=, a=0.5, a*x^2))                 # 函数f(x;a=0.5)
Fun
Fun(x=2)                                                 # 求函数值f(1)   
D1x=D(expFun, "x")                                       # 对表达式中x求一阶偏导
D1x
D1a=D(expFun, "a")
data.frame(x,a,expFun=as.character(expFun),
           D1x=eval(D1x), D1a=eval(D1a))
DD <- function(expr, name, order){                       # 写函数，循环求高阶导数
   if (order < 1)
       stop("'order' must be >= 1")
   if (order == 1)
       D(expr, name) else DD(D(expr, name), name, order - 1)}
DD(expFun, "x", 2)                                       # 调用函数求2阶导
DD(expFun, "x", 3)
NormDensity <- expression(1/sqrt(2 * pi) * exp(-x^2/2))  # 正态密度函数
class(NormDensity)
D(NormDensity, "x")                                      # 求一阶导数
deriv(NormDensity, "x")
deriv3(NormDensity, "x")
DD(NormDensity, "x", 3)
# 积分
library(Ryacas)
yacas(expression(integrate(1/x, x)))
yacas("Integrate(x)1/x")
x <- Sym("x"); Integrate(1/x, x)
yacas("Integrate(t)a*t")
Simplify(yacas("Integrate(t)a*t"))

5. 老鼠4*4方格，概率

老鼠4*4方格，概率

a=matrix(c(0.6, 0.5, 0, 0.2, 0.5, 1/3, 0, 0.5, 1/3),3,byrow=T)
old=rep(1,3)
for (i in 1:5){
  new=a %*% old
  N=t(new)%*%c(4,8,4)
  print(data.frame(new, old))
  print(N)
  old=new
} 
library(expm)
print(round(rowSums(a%^%10),3))
b=matrix(c(0.6,0.4,0,0.25,0.5,0.25,0,2/3,1/3),3,byrow=T)
print(round(colSums(c(4,8,4)%*%b%^%10),3))
(b%^%10)[2,]*16/c(4,8,4)

参考文献

1. 黄湘云：R语言做符号计算
2. K. Soetaert and T. Petzoldt: CRAN Task View: Differential Equations
3. R.H. Shumway and D.S. Stoffer, 2016: Time Series Analysis and Its Applications: With R Examples(4th ed.), Springer