R学习02（数据集创建）

• 注意
  1、 TRUE,FALSE严格区分大小写
  2、R不支持多行注释
  3、变量不能被declared,they come into existence on first assignment
  4、

vactor

Note:vectors are one-dimensional arrays,scalars are one-element vectors.

• 创建
  

use c() function

a<-c(1,2,3)  #a numeric vectorb<-c("one",'two","three") # a charactor vectorc<-(TRUE,TRUE,FALSE) # a logical vector)f<-3  # scalars are used to hold constants(常量)

matrices

• 创建
  

mymatrix<- matrix(vector,nrow=number_of_rows,ncol=number_of_columns,byrow=logical_value,dimname=list(char_vector_rownames,char_vector_colnames))
默认：byrow=FALSE

> y<-matrix(1:20,nrow=5,ncol=4)> y     [,1] [,2] [,3] [,4][1,]    1    6   11   16[2,]    2    7   12   17[3,]    3    8   13   18[4,]    4    9   14   19[5,]    5   10   15   20> cells<-c(1,2,3,4)> rnames<-c("R1","R2")> cnames<-c("C1,","C2")> mymatrix<-matrix(cells,nrow=2,ncol=2,byrow = TRUE,dimnames=list(rnames,cnames))> mymatrix   C1, C2R1   1  2R2   3  4

arrays

Arrays are similar to matrices but can have more than two dimensions.
Like matrices,they must be asingle mode.
- 创建

myarray<-array(vertor,dimensions,dimnames)

dimensions is a numeric vector giving the maximal index for each dimension
dimnames is an optional list of dimension lables

> dim1<-c("a1","a2")> dim2<-c("b1","b2","b3")> dim3<-c("c1","c2","c3","c4")> z<-array(1:24,c(2,3,4),dimnames = list(dim1,dim2,dim3))> z, , c1   b1 b2 b3a1  1  3  5a2  2  4  6, , c2   b1 b2 b3a1  7  9 11a2  8 10 12, , c3   b1 b2 b3a1 13 15 17a2 14 16 18, , c4   b1 b2 b3a1 19 21 23a2 20 22 24

data frames

a data from is more general than a matrix in that different columns can contain different modes of data.

• 创建
  

mydata<- data.frame(col1,clo2,clo3,…)

> ID<-c(1,2,3,4)> age<-c(25,34,28,52)> diabetes<-c("type1","type2","type1","type1")> status<-c("poor","improved","excellent","poor")> patientdata<-data.frame(ID,age,diabetes,status)> patientdata  ID age diabetes    status1  1  25    type1      poor2  2  34    type2  improved3  3  28    type1 excellent4  4  52    type1      poor

each column must have only one mode,but you can put colmns of different modes together to form the data frame.

factor

variables canbe described as nominal(名义型),ordinal(有序型),or continuous.
Categorical(nominal) and ordered categorical(ordinal) variables in R are called factors.
norminal:上个例子中的diabetes(type1,type2),是无序的
ordinal:上个例子中的status(poor,improved,excellent)，是有序的，但不表示数量

factor()
myfactor<-factor(factor_vector,order=TRUE,levels)

> ID<-c(1,2,3,4)> age<-c(25,34,28,52)> diabetes<-c("type1","type2","type1","type1")> status<-c("poor","improved","excellent","poor")> diabetes<-factor(diabetes)> status<-factor(status,order=TRUE)> patientdata<-data.frame(patientdata,age,diabetes,status)> str(patientdata)'data.frame':   4 obs. of  7 variables: $ ID        : num  1 2 3 4 $ age       : num  25 34 28 52 $ diabetes  : Factor w/ 2 levels "type1","type2": 1 2 1 1 $ status    : Factor w/ 3 levels "excellent","improved",..: 3 2 1 3 $ age.1     : num  25 34 28 52 $ diabetes.1: Factor w/ 2 levels "type1","type2": 1 2 1 1 $ status.1  : Ord.factor w/ 3 levels "excellent"<"improved"<..: 3 2 1 3> summary(patientdata)       ID            age         diabetes       status  Min.   :1.00   Min.   :25.00   type1:3   excellent:1   1st Qu.:1.75   1st Qu.:27.25   type2:1   improved :1   Median :2.50   Median :31.00             poor     :2   Mean   :2.50   Mean   :34.75                           3rd Qu.:3.25   3rd Qu.:38.50                           Max.   :4.00   Max.   :52.00                               age.1       diabetes.1      status.1 Min.   :25.00   type1:3    excellent:1   1st Qu.:27.25   type2:1    improved :1   Median :31.00              poor     :2   Mean   :34.75                            3rd Qu.:38.50                            Max.   :52.00

注意，对factor指定order=TRUE，并规定level，是为了让factor的排序方式与逻辑顺序一致，默认情况是依照字母顺序创建的

list

A list allows you to gather a variety of objects under one name.For example,a list may contain a conbination of vectors,matrices,data frames,and even other lists.

• 创建
  

mylist<-list(object1,object2,…)
# Optionally,you can name the objects in a list
mylist<-list(name1=object1,name2=object2,…)

> g<-"my first list"> h<-c(1,2,3,4)> j<-matrix(1:10,nrow=5)> k<-c("one","two","three")> mylist<-list(title=g,ages=h,j,k)> mylist$title[1] "my first list"$ages[1] 1 2 3 4[[3]]     [,1] [,2][1,]    1    6[2,]    2    7[3,]    3    8[4,]    4    9[5,]    5   10[[4]][1] "one"   "two"   "three"> mylist[[2]][1] 1 2 3 4> mylist[["ages"]][1] 1 2 3 4

R refers to case identifiers as rownames and categorical variables(nominal[名义型] ,ordinal[有序型]) as factors
A dataset is usually a rectangular array of data with rows representing observations and columns representing variables.
R has a wide variaty of objects for hoding data,including scalars(标量),vectors,matrices,arrays,data frame,and lists.——《R in Action》