R的索引从1开始，Pyhon从0开始
创建leadership数据框
manager <- c(1,2,3,4,5)
date <- c("10/24/08", "10/28/08", "10/1/08", "10/12/08", "5/1/09")
country <- c("US", "US", "UK", "UK", "UK")
gender <- c("M", "F", "F", "M", "F")
age <- c(32,45,25,39,99)
q1 <- c(5,3,3,3,2)
q2 <- c(4,5,5,3,2)
q3 <- c(5,2,5,4,1)
q4 <- c(5,5,5,NA,2)
q5 <- c(5,5,2,NA,1)
leadership <- data.frame(manager, date, country, gender, age,
q1,q2,q3,q4,q5, stringsAsFactors = FALSE)
R1.png
从leadership数据框中选择变量q1, q2, q3, q4, q5，并将其保存到数据框newdata中
方法1：
newdata <- leadership[, c(6:10)]
方法2：
myvars <- c("q1", "q2", "q3", "q4", "q5")
newdata1 <- leadership[myvars]
R2.png
剔除变量q4,q5
方法1：
myvars <- names(leadership) %in% c("q4", "q5")
newdata <- leadership[!myvars]
方法2：
idx <- which(names(leadership)== c("q4","q5"))
newdata <- leadership[-idx]
方法3：
idx <- which(names(leadership)== c("q4","q5"))
leadership[idx] <- NULL
方法4：
leadership$q4 <- NULL
leadership$q5 <- NULL
R3.png
R4.png
设定条件gender为M，age大于30的选入观测值
方法1：
newdata <- leadership[leadership$gender == "M" & leadership$age >30,]
R5.png
方法2：
attach(leadership)
newdata <- leadership[gender == "M" & age > 30,]
detach(leadership)
R6.png
选定时间范围在2009-01-01~2009-10-31之间的观测值
leadership$date <- as.Date(leadership$date, "%m/%d/%y")
startdate <- as.Date("2009-01-01")
enddate <- as.Date("2009-10-31")
newdata <- leadership[which(leadership$date >= startdate &
leadership$date <= enddate),]
R7.png
利用subset函数提取子集
选择age大于35或age小于24的行,并保留变量q1到q4
newdata <- subset(leadership, age>=35|age<=24,
select = c(q1, q2, q3, q4))
R8.png
选择所有25岁以上的男性，并保留变量gender到q4（即gender到q4和其间的所有列）
newdata <- subset(leadership, age>25 &gender=="M",
select = gender:q4)
R9.png
利用sample函数从leadership数据集中随机抽取大小为3的样本
mysample <- leadership[sample(1:nrow(leadership), 3, replace = FALSE),]
R10.png
