How to find the total of frequency based on the values of a factor column in R?

R Programming Server Side Programming Programming

Often, we have duplicate values in a factor column that means a factor column has many levels and each of these levels occur many times. In this situation, if we have a frequency column then we want to find the total of that frequency based on the values of a factor column and this can be done by using aggregate function.

Example

Live Demo

Consider the below data frame −

> set.seed(109)
> Class<-rep(sample(LETTERS[1:5],4),times=5)
> Frequency<-sample(1:10,20,replace=TRUE)
> df1<-data.frame(Class,Frequency)
> df1

Output

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

Finding the sum of frequency for each class −

> aggregate(df1["Frequency"],by=df1["Class"],sum)

Output

   Class Frequency
1    B    24
2    C    30
3    D    35
4    E    38

Lets’ have a look at another example −

Example

> Metal<-rep(c("Iron","Nickel","Lead","Zinc","Tin","Sodium","Silver"),times=5)
> Quantity<-sample(20:50,35,replace=TRUE)
> df2<-data.frame(Metal,Quantity)
> head(df2,10)

   Metal    Quantity
1    Iron    43
2    Nickel  33
3    Lead    25
4    Zinc    24
5    Tin    27
6    Sodium  34
7    Silver   31
8    Iron    37
9    Nickel   36
10    Lead    24
> tail(df2,10)
      Metal Quantity
26    Tin    49
27    Sodium 43
28    Silver 47
29    Iron    28
30    Nickel 41
31    Lead    21
32    Zinc    33
33    Tin    44
34    Sodium 34
35    Silver 33

> aggregate(df2["Quantity"],by=df2["Metal"],sum)

Output

   Metal    Quantity
1    Iron     157
2    Lead     148
3    Nickel   174
4    Silver   165
5    Sodium   161
6    Tin      192
7    Zinc     155

Nizamuddin Siddiqui

Published on 04-Sep-2020 08:44:24

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