如何在R中组合数据框列表？
如果我们有一个数据框列表并且这些数据框的大小相同，那么我们可能想要组合这些列表，以便可以组合数据框。这可以通过使用 mapply 函数和 cbind 来完成。例如，如果我们有两个定义为 List1 和 List2 的数据框列表，那么我们可以使用以下命令将它们组合起来 -
mapply(cbind,List1,List2,SIMPLIFY=FALSE).
示例
考虑以下数据框 -
> x1<-rnorm(10)输出结果> x2<-rnorm(10)
> df1<-data.frame(x1,x2)
> df1
x1 x21 0.2378371 0.51433808
2 0.0638975 -1.66077353
3 0.3987209 0.68480587
4 -1.1321073 0.29528261
5 -0.5603269 1.14556819
6 2.2072545 -1.20718355
7 0.8196423 0.38380242
8 -2.2394064 0.06741712
9 -0.7356725 -1.46968026
10 -1.4642820 -1.39423679
示例
> y1<-rnorm(10)输出结果> y2<-rnorm(10)
> df2<-data.frame(y1,y2)
> df2
y1 y21 2.2307515 0.375538934
2 -1.3539616 -0.169574915
3 -0.1332480 -0.788416414
4 1.3181498 1.887995737
5 -1.4384012 1.261034365
6 0.3725585 -0.493219141
7 -0.7806511 -1.177616450
8 -0.4772392 0.250962895
9 -0.8932982 -0.004567268
10 0.2224190 -0.203232106
示例
> List1<-list(df1,df2)输出结果> List1
[[1]]x1 x2
1 0.2378371 0.51433808
2 0.0638975 -1.66077353
3 0.3987209 0.68480587
4 -1.1321073 0.29528261
5 -0.5603269 1.14556819
6 2.2072545 -1.20718355
7 0.8196423 0.38380242
8 -2.2394064 0.06741712
9 -0.7356725 -1.46968026
10 -1.4642820 -1.39423679
[[2]]
y1 y2
1 2.2307515 0.375538934
2 -1.3539616 -0.169574915
3 -0.1332480 -0.788416414
4 1.3181498 1.887995737
5 -1.4384012 1.261034365
6 0.3725585 -0.493219141
7 -0.7806511 -1.177616450
8 -0.4772392 0.250962895
9 -0.8932982 -0.004567268
10 0.2224190 -0.203232106
列表2
示例
> a1<-rnorm(10)输出结果> a2<-rnorm(10)
> df3<-data.frame(a1,a2)
> df3
a1 a21 1.5711728 0.2861241
2 0.8062374 0.9469154
3 1.1505496 -0.5894829
4 0.9164866 -0.3137043
5 -1.3424446 -1.2921698
6 -0.1499540 -0.8940665
7 -0.1498557 -1.1361156
8 0.9299988 0.7679135
9 -1.7079005 -0.7099908
10 0.8146867 1.3921303
示例
> b1<-rnorm(10)输出结果> b2<-rnorm(10)
> df4<-data.frame(b1,b2)
> df4
b1 b21 -1.7113866 1.7014637
2 -0.0202485 1.2428109
3 -0.3892979 -1.5831333
4 0.2127277 -0.4943695
5 -0.4846616 1.0283278
6 -1.4116239 -1.4882983
7 -0.1737286 -0.1101114
8 1.4613389 0.1531942
9 -0.1573986 0.3431330
10 -0.2782074 0.5439397
示例
> List2<-list(df3,df4)输出结果> List2
[[1]]a1 a2
1 1.5711728 0.2861241
2 0.8062374 0.9469154
3 1.1505496 -0.5894829
4 0.9164866 -0.3137043
5 -1.3424446 -1.2921698
6 -0.1499540 -0.8940665
7 -0.1498557 -1.1361156
8 0.9299988 0.7679135
9 -1.7079005 -0.7099908
10 0.8146867 1.3921303
[[2]]
b1 b2
1 -1.7113866 1.7014637
2 -0.0202485 1.2428109
3 -0.3892979 -1.5831333
4 0.2127277 -0.4943695
5 -0.4846616 1.0283278
6 -1.4116239 -1.4882983
7 -0.1737286 -0.1101114
8 1.4613389 0.1531942
9 -0.1573986 0.3431330
10 -0.2782074 0.5439397
结合数据框列表 -
示例
> mapply(cbind,List1,List2,SIMPLIFY=FALSE)输出结果
[[1]]x1 x2 a1 a2
1 0.2378371 0.51433808 1.5711728 0.2861241
2 0.0638975 -1.66077353 0.8062374 0.9469154
3 0.3987209 0.68480587 1.1505496 -0.5894829
4 -1.1321073 0.29528261 0.9164866 -0.3137043
5 -0.5603269 1.14556819 -1.3424446 -1.2921698
6 2.2072545 -1.20718355 -0.1499540 -0.8940665
7 0.8196423 0.38380242 -0.1498557 -1.1361156
8 -2.2394064 0.06741712 0.9299988 0.7679135
9 -0.7356725 -1.46968026 -1.7079005 -0.7099908
10 -1.4642820 -1.39423679 0.8146867 1.3921303
[[2]]
y1 y2 b1 b2
1 2.2307515 0.375538934 -1.7113866 1.7014637
2 -1.3539616 -0.169574915 -0.0202485 1.2428109
3 -0.1332480 -0.788416414 -0.3892979 -1.5831333
4 1.3181498 1.887995737 0.2127277 -0.4943695
5 -1.4384012 1.261034365 -0.4846616 1.0283278
6 0.3725585 -0.493219141 -1.4116239 -1.4882983
7 -0.7806511 -1.177616450 -0.1737286 -0.1101114
8 -0.4772392 0.250962895 1.4613389 0.1531942
9 -0.8932982 -0.004567268 -0.1573986 0.3431330
10 0.2224190 -0.203232106 -0.2782074 0.5439397
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