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# How to find total of an integer column based on two different character columns in R?

The calculation of total for integer column based on two different character columns simply means that we need to create a contingency table for the available data. For this purpose, we can use with and tapply function. For example, if we have a data frame df that contains two categorical columns defined as gender and ethnicity and an integer column defined as Package then the contingency table can be created as:

with(df,tapply(Package,list(gender,ethnicity),sum))

## Example

Consider the below data frame −

set.seed(777) Class<−sample(c("First","Second","Third"),20,replace=TRUE) Group<−sample(c("GP1","GP2","GP3","GP4"),20,replace=TRUE) Rate<−sample(0:10,20,replace=TRUE) df1<−data.frame(Class,Group,Rate) df1

## Output

Class Group Rate 1 First GP1 7 2 Second GP2 1 3 Second GP4 1 4 Second GP4 0 5 Third GP2 10 6 Second GP2 8 7 First GP1 7 8 First GP4 4 9 Second GP1 4 10 Third GP3 8 11 Second GP2 8 12 First GP2 4 13 Third GP2 6 14 Third GP4 4 15 Third GP4 5 16 Second GP1 2 17 Second GP1 9 18 Second GP3 2 19 Second GP3 1 20 Third GP4 10

## Example

str(df1) 'data.frame': 20 obs. of 3 variables: $ Class: chr "First" "Second" "Second" "Second" ... $ Group: chr "GP1" "GP2" "GP4" "GP4" ... $ Rate : int 7 1 1 0 10 8 7 4 4 8 ...

Finding the total of Rate based on Class and Group −

with(df1,tapply(Rate,list(Class,Group),sum)) GP1 GP2 GP3 GP4 First 14 4 NA 4 Second 15 17 3 1 Third NA 16 8 19

Let’s have a look at another example −

## Example

Gender<−sample(c("Male","Female"),20,replace=TRUE) Centering<−sample(c("Yes","No"),20,replace=TRUE) Percentage<−sample(1:100,20) df2<−data.frame(Gender,Centering,Percentage) df2

## Output

Gender Centering Percentage 1 Male No 28 2 Male No 89 3 Female Yes 38 4 Male No 78 5 Male Yes 19 6 Female No 46 7 Female Yes 94 8 Male No 4 9 Male Yes 92 10 Male No 90 11 Male Yes 66 12 Female No 57 13 Female No 74 14 Female No 48 15 Female Yes 20 16 Male Yes 51 17 Male No 82 18 Male No 7 19 Male No 53 20 Male No 55

Finding the total of Percentage based on Gender and Centering −

with(df2,tapply(Percentage,list(Gender,Centering),sum)) No Yes Female 225 152 Male 486 228

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