R语言使用<-操作符创建新的变量、使用两个数据列通过加和创建新的数据列(sum variables to make new featurs in dataframe) mydata mydata$sum <- mydata$x1 + mydata$x2 mydata > mydata age gender weight x1 x2 1 25 male 160 10 5 2 40 fe
R语言使用names函数查看dataframe的所有字段(数据列)的名称(list the variables in dataframe) # list the variables in mydata names(mydata) # list the structure of mydata #str(mydata) > # list the variables in mydata > names(mydata) [1] "age" "gender" "weight" > 编辑 R语...
data <- data.frame(x1 = 1:5, # Create example data x2 = LETTERS[1:5], x3 = c(2, 4, 6, 8, 0)) data # Print example dataTable 1: Example Data Frame in R.Table 1 illustrates the structure of our data: It contains five rows and the three columns/variables x1, x2, and x...
使用data.frame函数就可以初始化一个Data Frame。比如我们要初始化一个student的Data Frame其中包含ID和Name还有Gender以及Birthdate,那么代码为: student<-data.frame(ID=c(11,12,13),Name=c("Devin","Edward","Wenli"),Gender=c("M","M","F"),Birthdate=c("1984-12-29","1983-5-6","1986-8-8...
Build-in Data FrameWe use built-in data frames in R for our tutorials. For example, here is a built-in data frame in R, called mtcars. > mtcars mpg cyl disp hp drat wt ... Mazda RX4 21.0 6 160 110 3.90 2.62 ... Mazda RX4 Wag 21.0 6 160 110 3.90 2.88 ... Datsun 710 ...
对于没有顺序关系,nominal variables,则会报错。 ★Warning message: In Ops.factor(high, medium) : ‘>’ not meaningful for factors ” 性别不存在顺序。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 # Build factor_survey_vector with clean levels survey_vector <- c("M", "F", "F", "...
This article shows how toadd new variables at a specific position of a data frameinthe R programming language. The tutorial is structured as follows: 1)Example Data & Add-On Packages 2)Example 1: Add Variable Using add_column Function by Index Position ...
#显示对象的结构str(patientdata)'data.frame': 4 obs. of 4 variables:$ patientID: num 1 2 3 4$ age : num 25 34 28 52$ diabetes : Factor w/ 2 levels "Type1","Type2": 1 2 1 1$ status : Ord.factor w/ 3 levels "Excellent...
'data.frame': 4 obs. of 4 variables: $ patientID: num 1 2 3 4 $ age : num 25 34 28 52 $ diabetes : Factor w/ 2 levels "Type1","Type2": 1 2 1 2 $ status : Factor w/ 3 levels "Excellent","Improved",..: 3 2 1 3 > summary(patientdata) patientID age diabetes status...
1 构建数据框df x为factor变量,2010和2011位数值变量 2. 用reshape2::melt将2维数据转换为一维数据 df_melt<-reshape2::melt(df,id.vars="x",variable.name="year",value.name="value") Arguments 经过melt变换之后的df_melt 将长数据转换为宽数据 ...