How to sort each row of an R data frame in increasing order?

To sort each row of an R data frame in increasing order, we can use apply function for sorting the columns and then transpose the output. For example, if we have a data frame called df that contains 5 columns then each row of df can be sorted in increasing order by using the command t(apply(df,1,sort)).

Example1

Consider the below data frame −

 Live Demo

x1<-rpois(20,5)
x2<-rpois(20,5)
x3<-rpois(20,5)
x4<-rpois(20,5)
df1<-data.frame(x1,x2,x3,x4)
df1

Output

   x1 x2 x3 x4
1  4  3  6  8
2  4  4  5  3
3  1  6  4  4
4  5  3  7  5
5  4  7  3  7
6  7  7  8  3
7  4 13  5  2
8  5  4  4  5
9  7  4  1  5
10 5  4  6  7
11 6  3  2  2
12 3  0  6  5
13 4  5  5  2
14 7 12  6  8
15 6  4  6  3
16 8  7  3  3
17 7  6  5  3
18 5  5  5  8
19 6  3  1  9
20 2  4  3  4

Sorting each row in df1 in increasing order −

t(apply(df1,1,sort))

    [,1] [,2] [,3] [,4]
[1,]  3    4    6    8
[2,]  3    4    4    5
[3,]  1    4    4    6
[4,]  3    5    5    7
[5,]  3    4    7    7
[6,]  3    7    7    8
[7,]  2    4    5   13
[8,]  4    4    5    5
[9,]  1    4    5    7
[10,] 4    5    6    7
[11,] 2    2    3    6
[12,] 0    3    5    6
[13,] 2    4    5    5
[14,] 6    7    8   12
[15,] 3    4    6    6
[16,] 3    3    7    8
[17,] 3    5    6    7
[18,] 5    5    5    8
[19,] 1    3    6    9
[20,] 2    3    4    4

Example2

 Live Demo

y1<-rnorm(20)
y2<-rnorm(20)
y3<-rnorm(20)
df2<-data.frame(y1,y2,y3)
df2

Output

         y1           y2          y3
1   0.98162958  -0.2989471  -0.2254131
2   1.17064693  -1.9476458  -0.3945834
3   0.73691436  -1.8172343  -0.5653013
4   0.97507754   1.2841860   0.6290046
5  -0.84053056   1.2600141  -0.1827997
6   0.99946765  -0.7165685   0.2499400
7   0.01351743   0.2432559   0.7501626
8   0.60395966  -1.9376705  -0.6750133
9   1.92813786  -1.2536224  -0.3118962
10 -0.03692577  -0.9030202   0.9266927
11  0.60933676   0.3523446  -1.6367644
12 -0.77165402   0.6806964  -0.8524336
13 -1.62599096   2.1177609  -0.7749328
14  0.60632948   0.2074926   0.2615405
15  0.23464045   1.3825833   0.3813821
16 -0.27508014   0.6975645  -0.6448739
17 -0.30863343   0.9172400   1.6155362
18 -0.53579916  -0.5614784   0.8595362
19 -0.08786005  -1.0634296   0.9763744
20  0.66566923   0.2453712   1.1790946

Sorting each row in df2 in increasing order −

t(apply(df2,1,sort))

           [,1]        [,2]         [,3]
[1,]  -0.29894710  -0.22541313   0.9816296
[2,]  -1.94764575  -0.39458339   1.1706469
[3,]  -1.81723426  -0.56530126   0.7369144
[4,]   0.62900459   0.97507754   1.2841860
[5,]  -0.84053056  -0.18279967   1.2600141
[6,]  -0.71656845   0.24994000   0.9994676
[7,]   0.01351743   0.24325586   0.7501626
[8,]  -1.93767048  -0.67501331   0.6039597
[9,]  -1.25362238  -0.31189625   1.9281379
[10,] -0.90302017  -0.03692577   0.9266927
[11,] -1.63676440   0.35234462   0.6093368
[12,] -0.85243362  -0.77165402   0.6806964
[13,] -1.62599096  -0.77493280   2.1177609
[14,]  0.20749255   0.26154053   0.6063295
[15,]  0.23464045   0.38138210   1.3825833
[16,] -0.64487386  -0.27508014   0.6975645
[17,] -0.30863343   0.91724003   1.6155362
[18,] -0.56147837  -0.53579916   0.8595362
[19,] -1.06342956  -0.08786005   0.9763744
[20,]  0.24537124   0.66566923   1.1790946