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 >
A data frame is used for storing data tables. It is a list of vectors of equal length. For example, the following variable df is a data frame containing three vectors n, s, b. > n = c(2, 3, 5) > s = c("aa", "bb", "cc") > b = c(TRUE, FALSE, TRUE) > df = data...
1:3) Error in data.frame(1:5, 1:3) : arguments imply differing number of rows: 5...
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...
构建data frame 选取data frame的信息 通过条件语句获得信息 修改数据框 排序 处理缺失值 连接不同数据框 tibble 3. 因子factors 什么是factor 将向量转换为因子 两种类型的变量下的factor summary a factor 比较factor 中的变量 小回顾recap 4. R lists 新建一个list 从list 中获取信息 拆开表格 删除变量 易错点...
str(product_info) #> Classes 'data.table' and 'data.frame': 6 obs. of 5 variables: #> $ id : chr "T01" "T02" "M01" "M02" ... #> $ name : chr "SupCar" "SupPlane" "JeepX" "AircraftX" ... #> $ type : chr "toy" "toy" "model" "model" ... #> $ class : chr...
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 ...
If TRUE then the names of the variables in the data frame are checked to ensure that they are syntactically valid variable names and are not duplicated. If necessary they are adjusted (by make.names) so that they are. 1. 2. 3. 4. 逻辑值,取值为TRUE,则检查数据框中的变量名称确保变量...
mymatrix<-matrix(cells,nrow=2,ncol=2,byrow=FALSE,dimnames=list(rnames,cnames))mymatrixC1C2R1124R22668 矩阵下标的使用: x <- matrix(1:10, nrow=2)#创建了一个内容为数字1到10的2×5矩阵x[,1] [,2] [,3] [,4] [,5][1,]13579[2...
'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...