如何将 R 数据框中的行转换为列表？

有时需要对每一行进行不同的处理，因此，可能需要将这些行转换为列表。这将帮助我们对每一行元素进行单独的操作。如要将行转换为列表，我们可以使用 split 函数通过定义数据框中的行数。

考虑以下数据框 -

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

     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

我们来看另一个示例 -

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示例

实时演示

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

输出

 y1  y2  y3  y4  y5
1 A 1 6 1 0.12535201
2 B 2 1 4 0.04849127
3 C 3 7 4 0.10894953
4 D 4 0 4 0.32620261
5 E 5 3 7 0.04711375
6 F 6 5 2 0.10263975
7 G 7 3 1 0.35080088
8 H 8 2 4 0.25617221
9 I 9 0 0 0.31124956
10 J 10 0 5 0.07771391
11 K 11 7 2 0.02583599
12 L 12 2 2 0.06699178
13 M 13 3 3 0.04767600
14 N 14 1 4 0.11942077
15 O 15 6 4 0.62873345
16 P 16 3 6 0.08066371
17 Q 17 3 3 0.58563662
18 R 18 9 0 0.00548393
19 S 19 0 2 0.01171107
20 T 20 0 1 0.10728116

将 df2 的行转换为列表 -

df2_row_list<-split(df2,1:nrow(df2))

df2_row_list