You can use the following basic syntax to sum columns based on condition in R:
#sum values in column 3 where col1 is equal to 'A' sum(df[which(df$col1=='A'), 3])
The following examples show how to use this syntax in practice with the following data frame:
#create data frame df <- data.frame(conference = c('East', 'East', 'East', 'West', 'West', 'East'), team = c('A', 'A', 'A', 'B', 'B', 'C'), points = c(11, 8, 10, 6, 6, 5), rebounds = c(7, 7, 6, 9, 12, 8)) #view data frame df conference team points rebounds 1 East A 11 7 2 East A 8 7 3 East A 10 6 4 West B 6 9 5 West B 6 12 6 East C 5 8
Example 1: Sum One Column Based on One Condition
The following code shows how to find the sum of the points column for the rows where team is equal to ‘A’:
#sum values in column 3 (points column) where team is equal to 'A' sum(df[which(df$team=='A'), 3]) [1] 29
The following code shows how to find the sum of the rebounds column for the rows where points is greater than 9:
#sum values in column 4 (rebounds column) where points is greater than 9 sum(df[which(df$points > 9), 4]) [1] 13
Example 2: Sum One Column Based on Multiple Conditions
The following code shows how to find the sum of the points column for the rows where team is equal to ‘A’ and conference is equal to ‘East’:
#sum values in column 3 (points column) where team is 'A' and conference is 'East' sum(df[which(df$team=='A' & df$conference=='East'), 3]) [1] 29
Note that the & operator stands for “and” in R.
Example 3: Sum One Column Based on One of Several Conditions
The following code shows how to find the sum of the points column for the rows where team is equal to ‘A’ or ‘C’:
#sum values in column 3 (points column) where team is 'A' or 'C'
sum(df[which(df$team == 'A' | df$team =='C'), 3])
[1] 34
Note that the | operator stands for “or” in R.
Additional Resources
The following tutorials explain how to perform other common functions in R:
How to Sum Specific Columns in R
How to Sum Specific Rows in R
How to Calculate Sum by Group in R
Hi Zach
Let’s say I have this dataset
df1=data.frame(team = c(‘A’, ‘A’, ‘A’, ‘B’, ‘B’, ‘C’,’C’,’F’,’G’),
points = c(11, 8, 10, 6, 6, 5,12,4,17))
and this
dfsum <- data.frame(team = c('A', 'B', 'C', 'D', 'E', 'F'), points=c(0,0,0,0,0,0))
I want to make conditional sum in dfsum, column points so that it sums points from df1 if team in dfsum equals team in df1. I know I can group df1 based on team and perform merge, but I would like to do it with sumif.
I tried with nested for loop but it does not work…
nrow1=nrow(df1)
nrow2=nrow(dfsum)
for(i in 1:nrow2){
for(j in 1:nrow1){
if (dfsum[i,1]==df1[j,1]){
dfsum[i,2]=cumsum(df1[j,2])
}
}
}