How to preserve data frame structure after applying a function in R?

R ProgrammingServer Side ProgrammingProgramming

When we apply a function using apply family, by default the output is not in the form of a data frame. If we want to preserve the original data frame structure then we need to set the application of the apply family by setting it to the original data frame with single brackets and no arguments as shown in the below examples.

Example1

Consider the below data frame −

Live Demo

> df1<-data.frame(x1=rpois(20,5),x2=rpois(20,2))
> df1

Output

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

Applying a function paste with lapply to df1 −

> lapply(df1, function(x) paste(x,"%",sep=""))

Output

$x1
[1] "4%" "6%" "5%" "2%" "8%" "7%" "5%" "5%" "4%" "6%" "5%" "6%" "3%" "2%" "7%"
[16] "6%" "8%" "3%" "6%" "5%"

$x2
[1] "2%" "2%" "2%" "1%" "4%" "2%" "3%" "1%" "2%" "1%" "2%" "1%" "2%" "4%" "2%"
[16] "1%" "2%" "5%" "3%" "2%"

Applying a function paste with lapply to df1 and preserving the data frame structure −

> df1[]<-lapply(df1, function(x) paste(x,"%", sep=""))
> df1

Output

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

Example2

Live Demo

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

Output

        y1         y2
1  -0.752047670  1.13712713
2  -0.128263190 -0.32853561
3  -0.302105388  0.13927555
4  -0.962792837 -0.11345683
5  -0.792733177 -0.44710830
6  -0.374832959 -0.11577915
7   0.006232538  1.69377281
8  -0.248837346  1.53856740
9  -1.329142492 -0.93981148
10 -0.800394342  0.23268426
11 -0.024673008 -1.45167348
12 -0.798652443  0.56592880
13  0.752464819  0.26117631
14  0.356222254  1.09788129
15 -0.189963724  0.04015303
16  1.237747888  0.30426806
17 -0.079703224 -1.19632730
18  0.610445704 -0.09226399
19  1.312108743  0.59445517
20  0.117974479  0.31822741

Applying a function paste with lapply to df2 −

> lapply(df2, function(x) paste(x,"*100",sep=""))

Output

$y1
[1] "-0.75204767044446*100" "-0.128263189709441*100"
[3] "-0.302105388264774*100" "-0.962792837263563*100"
[5] "-0.792733176975126*100" "-0.37483295904029*100"
[7] "0.0062325380738995*100" "-0.24883734622218*100"
[9] "-1.32914249184804*100" "-0.800394341521099*100"
[11] "-0.0246730078659625*100" "-0.798652442767393*100"
[13] "0.752464818654371*100" "0.356222253519168*100"
[15] "-0.189963724365201*100" "1.23774788828591*100"
[17] "-0.0797032238997077*100" "0.61044570354826*100"
[19] "1.31210874294046*100" "0.117974478781838*100"

$y2
[1] "1.13712713179116*100" "-0.328535609444004*100"
[3] "0.139275554888166*100" "-0.113456833535264*100"
[5] "-0.447108300367073*100" "-0.115779145719786*100"
[7] "1.69377280937111*100" "1.53856740099674*100"
[9] "-0.939811483903564*100" "0.232684264342039*100"
[11] "-1.45167347644544*100" "0.565928797260725*100"
[13] "0.261176305488481*100" "1.09788129483035*100"
[15] "0.0401530283786003*100" "0.304268061193212*100"
[17] "-1.1963272953655*100" "-0.0922639906523411*100"
[19] "0.594455172315153*100" "0.318227406098396*100"

Applying a function paste with lapply to df2 and preserving the data frame structure −

> df2[]<-lapply(df2, function(x) paste(x,"*100",sep=""))
> df2

Output

           y1                   y2
1  -0.75204767044446*100     1.13712713179116*100
2  -0.128263189709441*100   -0.328535609444004*100
3  -0.302105388264774*100    0.139275554888166*100
4  -0.962792837263563*100   -0.113456833535264*100
5  -0.792733176975126*100   -0.447108300367073*100
6  -0.37483295904029*100    -0.115779145719786*100
7   0.0062325380738995*100   1.69377280937111*100
8  -0.24883734622218*100     1.53856740099674*100
9  -1.32914249184804*100    -0.939811483903564*100
10 -0.800394341521099*100    0.232684264342039*100
11 -0.0246730078659625*100  -1.45167347644544*100
12 -0.798652442767393*100    0.565928797260725*100
13  0.752464818654371*100    0.261176305488481*100
14  0.356222253519168*100    1.09788129483035*100
15 -0.189963724365201*100    0.0401530283786003*100
16  1.23774788828591*100     0.304268061193212*100
17 -0.0797032238997077*100  -1.1963272953655*100
18  0.61044570354826*100    -0.0922639906523411*100
19  1.31210874294046*100     0.594455172315153*100
20  0.117974478781838*100    0.318227406098396*100
raja
Published on 04-Mar-2021 08:17:18
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