How to convert rows in an R data frame to list?

Sometimes each row needs to be treated differently, therefore, we might want to convert those rows into list. This will help us to perform the operations on our row elements separately. To convert the rows into list, we can use split function by defining the number of rows in the data frame.
Consider the below data frame −
 Live Demo
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
     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
Converting rows of df1 into a list −
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
Let’s have a look at another example −
 Live Demo
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
 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
Converting rows of df2 into list −
df2_row_list<-split(df2,1:nrow(df2))
df2_row_list
$`1`
y1 y2 y3 y4 y5
1 A 1 4 2 0.02331396
$`2`
y1 y2 y3 y4 y5
2 B 2 6 2 0.2343971
$`3`
y1 y2 y3 y4 y5
3 C 3 1 5 0.022928
$`4`
y1 y2 y3 y4 y5
4 D 4 3 2 0.009332871
$`5`
y1 y2 y3 y4 y5
5 E 5 3 4 0.3321631
$`6`
y1 y2 y3 y4 y5
6 F 6 8 5 0.6256276
$`7`
y1 y2 y3 y4 y5
7 G 7 8 2 0.03358184
$`8`
y1 y2 y3 y4 y5
8 H 8 2 3 0.2089223
$`9`
y1 y2 y3 y4 y5
9 I 9 6 3 0.5231238
$`10`
y1 y2 y3 y4 y5
10 J 10 7 3 0.01456478
$`11`
y1 y2 y3 y4 y5
11 K 11 2 2 0.670605
$`12`
y1 y2 y3 y4 y5
12 L 12 1 2 0.1021066
$`13`
y1 y2 y3 y4 y5
13 M 13 5 7 0.2673457
$`14`
y1 y2 y3 y4 y5
14 N 14 0 1 0.442615
$`15`
y1 y2 y3 y4 y5
15 O 15 3 5 0.2244831
$`16`
y1 y2 y3 y4 y5
16 P 16 7 2 0.2897614
$`17`
y1 y2 y3 y4 y5
17 Q 17 2 4 0.4671283
$`18`
y1 y2 y3 y4 y5
18 R 18 7 3 0.274696
$`19`
y1 y2 y3 y4 y5
19 S 19 0 2 0.1120801
$`20`
y1 y2 y3 y4 y5
20 T 20 8 5 0.2727685
is.list(df2_row_list) [1] TRUE