How to sum a variable by group in R?
A straightforward way to compute sums by group is to use tapply()
:
# Example data df <- data.frame( group = c("A", "A", "B", "B", "A"), value = c(10, 5, 7, 3, 12) ) # Sum of 'value' grouped by 'group' tapply(df$value, df$group, sum)
tapply()
splits df$value
by df$group
and applies the sum
function, returning the sums for each group as a named vector.
Using dplyr
The dplyr
package offers a clear, pipe-friendly syntax:
library(dplyr) df %>% group_by(group) %>% summarize(total_value = sum(value))
Here, group_by(group)
partitions the data by the group
column, and summarize(total_value = sum(value))
calculates the sum in each group.
Using data.table
If you prefer the data.table
package:
library(data.table) dt <- as.data.table(df) dt[, .(total_value = sum(value)), by = group]
data.table
is known for its efficiency with large datasets.
More Resources
If you’re preparing for technical interviews or want to build solid data manipulation skills, check out:
- Grokking the Coding Interview: Patterns for Coding Questions
- Grokking Data Structures & Algorithms for Coding Interviews
For mastering system architecture concepts, explore Grokking System Design Fundamentals. If you want personalized feedback, consider a Coding Mock Interview with ex-FAANG engineers. Finally, check out the DesignGurus.io YouTube channel for more tutorials.