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# Find the sum of a column values based on another numerical column in R.

To find the sum of a column values based on another numerical column in R, we can use with function and define the sum by subsetting the column with the help of single square brackets.

For Example, if we have a data frame called df that contains two columns say X and Y then we can find the sum of values in X when Y is greater than 10 by using the command with the following −

(df,sum(X[Y10]))

## Example 1

Following snippet creates a sample data frame −

x1<-rpois(20,2) y1<-rpois(20,2) df1<-data.frame(x1,y1) df1

The following dataframe is created

x1 y1 1 1 1 2 0 1 3 0 1 4 2 3 5 3 1 6 0 2 7 7 2 8 3 1 9 2 3 10 2 1 11 3 5 12 3 2 13 4 2 14 0 4 15 1 5 16 2 1 17 3 3 18 2 0 19 3 1 20 1 2

To find the sum of y1 values when x1 is between 1 and 4 on the above created data frame, add the following code to the above snippet −

x1<-rpois(20,2) y1<-rpois(20,2) df1<-data.frame(x1,y1) with(df1,sum(y1[x1>1 & x1<4]))

## Output

If you execute all the above given snippets as a single program, it generates the following Output −

[1] 23

## Example 2

Following snippet creates a sample data frame −

x2<-rnorm(20) y2<-rnorm(20) df2<-data.frame(x2,y2) df2

The following dataframe is created

x2 y2 1 1.14755939 0.2739985 2 0.33167239 -0.2753514 3 -0.01889732 2.0004839 4 -0.21294107 -1.2277250 5 -1.01230915 -0.4567277 6 0.30736328 0.8563572 7 0.59352845 0.7922568 8 -1.52657337 0.6147363 9 1.43228181 -0.7891716 10 0.15651466 -1.0415412 11 0.01792464 -0.3184454 12 -0.39428864 1.8005928 13 -0.48033841 -1.2787737 14 -0.51845529 0.2815327 15 0.33342239 -0.1313864 16 0.80461529 -0.2456082 17 0.30222411 -1.0134336 18 -0.83910609 -0.8805410 19 -0.06040907 1.4582650 20 0.12855851 -0.3424985

To find the sum of y2 values when x2 is between 1 and 1.2 on the above created data frame, add the following code to the above snippet −

x2<-rnorm(20) y2<-rnorm(20) df2<-data.frame(x2,y2) with(df2,sum(y2[x>21 & x2<1.2]))

## Output

If you execute all the above given snippets as a single program, it generates the following Output −

[1] 0.2739985

## Example 3

Following snippet creates a sample data frame −

x3<-sample(0:9,20,replace=TRUE) y3<-sample(0:9,20,replace=TRUE) df3<-data.frame(x3,y3) df3

The following dataframe is created

x3 y3 1 9 0 2 2 3 3 2 1 4 1 2 5 2 0 6 1 6 7 3 1 8 1 0 9 9 5 10 6 9 11 1 5 12 6 6 13 7 3 14 9 7 15 9 8 16 5 8 17 0 1 18 6 9 19 3 4 20 1 3

To find the sum of y3 values when x3 is between 8 and 10 on the above created data frame, add the following code to the above snippet −

x3<-sample(0:9,20,replace=TRUE) y3<-sample(0:9,20,replace=TRUE) df3<-data.frame(x3,y3) with(df3,sum(y3[x>38 & x3<10]))

## Output

If you execute all the above given snippets as a single program, it generates the following Output −

[1] 20

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