如何在R中按垂直顺序显示数据框摘要？
要按垂直顺序显示数据框摘要，我们可以将lapply和cbind函数与summary函数一起使用。例如，如果我们有一个名为df的数据框，那么可以使用以下命令找到按垂直顺序排列的df摘要-
lapply(df,function(x) cbind(summary(x)))
示例1
考虑以下数据框-
> x1<-rpois(20,5) > x2<-rpois(20,2) > x3<-rpois(20,3) > x4<-rpois(20,3) > x5<-rpois(20,5) > df1<-data.frame(x1,x2,x3,x4,x5) > df1输出结果
x1 x2 x3 x4 x5 1 4 0 2 2 6 2 7 2 4 1 7 3 7 2 3 3 6 4 4 0 4 5 2 5 5 2 2 1 8 6 2 1 2 9 5 7 4 0 2 6 6 8 5 2 1 5 5 9 3 3 2 2 10 10 5 2 1 4 3 11 4 2 3 4 6 12 3 4 5 2 6 13 6 1 1 2 10 14 3 2 3 5 9 15 2 1 0 1 8 16 2 2 4 5 7 17 5 1 3 3 5 18 4 6 5 1 3 19 10 2 4 3 6 20 2 1 4 3 7
按垂直顺序查找df1的摘要-
> lapply(df1,function(x) cbind(summary(x)))输出结果
$x1
[,1]
Min. 2.00
1st Qu. 3.00
Median 4.00
Mean 4.35
3rd Qu. 5.00
Max. 10.00
$x2
[,1]
Min. 0.0
1st Qu. 1.0
Median 2.0
Mean 1.8
3rd Qu. 2.0
Max. 6.0
$x3
[,1]
Min. 0.00
1st Qu. 2.00
Median 3.00
Mean 2.75
3rd Qu. 4.00
Max. 5.00
$x4
[,1]
Min. 1.00
1st Qu. 2.00
Median 3.00
Mean 3.35
3rd Qu. 5.00
Max. 9.00
$x5
[,1]
Min. 2.00
1st Qu. 5.00
Median 6.00
Mean 6.25
3rd Qu. 7.25
Max. 10.00例2
> y1<-rnorm(20,21,2.25) > y2<-rnorm(20,252,37.24) > y3<-rnorm(20,25457,3654.25) > df2<-data.frame(y1,y2,y3) > df2输出结果
y1 y2 y3 1 19.85077 283.9417 27360.27 2 22.30740 224.1180 21955.95 3 22.82174 289.0184 29019.13 4 23.01813 197.2612 20215.58 5 20.14611 272.0723 22895.22 6 18.06886 160.0688 27238.66 7 24.64121 213.4816 21500.75 8 18.02140 306.3236 26131.44 9 20.35991 230.8819 24885.17 10 18.23664 226.1749 28375.36 11 25.54674 234.6761 22919.52 12 19.24247 239.6695 23611.60 13 23.25991 273.1509 25088.87 14 17.31507 172.9442 20658.12 15 17.38401 269.1130 20928.33 16 20.18348 256.1337 21907.11 17 21.77760 210.4990 17576.79 18 21.64395 304.7984 19382.12 19 20.19686 214.9300 22940.67 20 21.81332 279.9707 19274.34
按垂直顺序查找df2的摘要-
> lapply(df2,function(x) cbind(summary(x)))输出结果
$y1
[,1]
Min. 17.31507
1st Qu. 18.99101
Median 20.27838
Mean 20.79178
3rd Qu. 22.43599
Max. 25.54674
$y2
[,1]
Min. 160.0688
1st Qu. 214.5679
Median 237.1728
Mean 242.9614
3rd Qu. 274.8559
Max. 306.3236
$y3
[,1]
Min. 17576.79
1st Qu. 20860.78
Median 22907.37
Mean 23193.25
3rd Qu. 25349.52
Max. 29019.13