如何將 R 資料框中的行轉換為列表？

有時需要對每一行進行不同的處理，因此，可能需要將這些行轉換為列表。這將幫助我們對每一行元素進行單獨的操作。如要將行轉換為列表，我們可以使用 split 函式透過定義資料框中的行數。

考慮以下資料框 -

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

輸出

     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

將 df1 的行轉換為列表 -

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

我們來看另一個示例 -

示例

即時演示

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

輸出

 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

將 df2 的行轉換為列表 -

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

df2_row_list