How to find the difference of values of each row from previous by group in an R data frame?

In Data Analysis, sometimes we need to find the difference of the current value from the previous value and it can be also needed for groups. It helps us to compare the differences among the values. In R, we can use dplyr package’s group_by and mutate function with lag.

Example

Consider the below data frame −

 Live Demo

> Group<-rep(LETTERS[1:5],each=4)
> Frequency<-sample(1:20,20,replace=TRUE)
> df1<-data.frame(Group,Frequency)
> df1

Output

 Group Frequency
1 A    7
2 A    6
3 A    9
4 A    12
5 B    19
6 B    19
7 B    4
8 B    6
9 C    14
10 C    6
11 C    6
12 C    20
13 D    2
14 D    11
15 D    14
16 D    19
17 E    14
18 E    7
19 E    3
20 E    1

Loading dplyr package −

> library(dplyr)

Subtracting Frequencies of each row from previous by Group −

> df1%>%group_by(Group)%>%mutate(Difference=Frequencylag(Frequency,default=first(Frequency)))
# A tibble: 20 x 3
# Groups: Group [5]

Output

Group Frequency Difference
<fct> <int> <int>
1 A    7    0
2 A    6    -1
3 A    9    3
4 A    12    3
5 B    19    0
6 B    19    0
7 B    4    -15
8 B    6    2
9 C    14    0
10 C    6    -8
11 C    6    0
12 C    20    14
13 D    2    0
14 D    11    9
15 D    14    3
16 D    19    5
17 E    14    0
18 E    7    -7
19 E    3    -4
20 E    1    -2

Let’s have a look at another example −

Example

 Live Demo

> x<-rep(c("S1","S2","S3","S4","S5"),times=4)
> y<-rnorm(20)
> df2<-data.frame(x,y)
> df2

Output

   x    y
1 S1 -0.2648554
2 S2 -1.6024447
3 S3 -0.3668267
4 S4 0.6439787
5 S5 1.9406125
6 S1 1.8398485
7 S2 1.5151748
8 S3 -0.7975164
9 S4 -1.4744469
10 S5 -0.4300237
11 S1 -1.2181901
12 S2 -0.9504064
13 S3 1.0594684
14 S4 -0.3190330
15 S5 -0.4186285
16 S1 0.2418591
17 S2 0.4273363
18 S3 1.2725779
19 S4 0.1008520
20 S5 0.0362863
> df2%>%group_by(x)%>%mutate(Difference=y-lag(y,default=first(y)))
# A tibble: 20 x 3
# Groups: x [5]

Output

   x       y    Difference
<fct>    <dbl>    <dbl>
1 S1    -0.265       0
2 S2    -1.60       0
3 S3    -0.367       0
4 S4    0.644       0
5 S5    1.94       0
6 S1    1.84       2.10
7 S2    1.52       3.12
8 S3    -0.798    -0.431
9 S4    -1.47    -2.12
10 S5    -0.430    -2.37
11 S1    -1.22    -3.06
12 S2    -0.950    -2.47
13 S3    1.06       1.86
14 S4    -0.319    1.16
15 S5    -0.419    0.0114
16 S1    0.242    1.46
17 S2    0.427    1.38
18 S3    1.27    0.213
19 S4    0.101    0.420
20 S5    0.0363    0.455

Updated on: 04-Sep-2020

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