如何将R数据框中的行转换为列表？

2024-04-15 23:10:04 30

有时每行需要区别对待，因此，我们可能希望将这些行转换为列表。这将帮助我们分别对行元素执行操作。要将行转换为列表，我们可以通过定义数据框中的行数来使用拆分功能。

请看以下数据帧-

示例

set.seed(101)
x1<-rnorm(20,5,1)
x2<-rnorm(20,5,2)
x3<-rnorm(20,5,1.5)
x4<-rnorm(20,3,0.096)
df1<-data.frame(x1,x2,x3,x4)
df1

输出结果

     x1       x2      x3       x4
1 4.673964 4.672489 5.723688 2.975059
2 5.552462 6.417044 6.137321 2.864527
3 4.325056 4.464039 1.521009 2.938430
4 5.214359 2.072156 4.310743 3.010796
5 5.310769 6.488872 3.341924 3.040570
6 6.173966 2.179220 5.604392 3.037136
7 5.618790 5.934135 5.853402 2.933971
8 4.887266 4.761360 3.940875 3.014295
9 5.917028 5.934478 4.564864 2.994466
10 4.776741 5.996271 2.774183 2.992817
11 5.526448 6.789874 3.274617 3.144950
12 4.205156 5.558304 4.588293 3.155514
13 6.427756 7.015732 5.866852 3.110703
14 3.533180 0.853787 2.904646 2.992550
15 4.763317 7.379707 6.123587 2.825382
16 4.806662 3.551252 3.423220 2.900405
17 4.150245 5.335968 5.248071 3.029039
18 5.058465 6.840670 6.694714 2.877317
19 4.182330 1.656790 6.760584 3.013281
20 2.949692 5.896938 4.358205 2.995106

将df1的行转换为列表-

df1_row_list<-split（df1,1：nrow(df1)）

df1_row_list

$`1`

x1 x2 x3 x4
1 4.673964 4.672489 5.723688 2.975059

$`2`

x1 x2 x3 x4
2 5.552462 6.417044 6.137321 2.864527

$`3`

x1 x2 x3 x4
3 4.325056 4.464039 1.521009 2.93843

$`4`

     x1       x2 x3 x4
4 5.214359 2.072156 4.310743 3.010796

$`5`

    x1        x2       x3     x4
5 5.310769 6.488872 3.341924 3.04057

$`6`

x1 x2 x3 x4
6 6.173966 2.17922 5.604392 3.037136

$`7`

x1 x2 x3 x4
7 5.61879 5.934135 5.853402 2.933971

$`8`

x1 x2 x3 x4
8 4.887266 4.76136 3.940875 3.014295

$`9`

x1 x2 x3 x4
9 5.917028 5.934478 4.564864 2.994466

$`10`

x1 x2 x3 x4
10 4.776741 5.996271 2.774183 2.992817

$`11`

x1 x2 x3 x4
11 5.526448 6.789874 3.274617 3.14495

$`12`

x1 x2 x3 x4
12 4.205156 5.558304 4.588293 3.155514

$`13`

x1 x2 x3 x4
13 6.427756 7.015732 5.866852 3.110703

$`14`

x1 x2 x3 x4
14 3.53318 0.853787 2.904646 2.99255

$`15`

x1 x2 x3 x4
15 4.763317 7.379707 6.123587 2.825382

$`16`

x1 x2 x3 x4
16 4.806662 3.551252 3.42322 2.900405

$`17`

x1 x2 x3 x4
17 4.150245 5.335968 5.248071 3.029039

$`18`

x1 x2 x3 x4
18 5.058465 6.84067 6.694714 2.877317

$`19`

x1 x2 x3 x4
19 4.18233 1.65679 6.760584 3.013281

$`20`

x1 x2 x3 x4
20 2.949692 5.896938 4.358205 2.995106

is.list(df1_row_list)[1]TRUE

让我们看另一个例子-

示例

y1<-LETTERS[1:20]
y2<-1:20
y3<-sample(0:9,20,replace=TRUE)
y4<-rpois(20,3)
y5<-rexp(20,3)
df2<-data.frame(y1,y2,y3,y4,y5)
df2