tapply() function dependent on multiple columns in R

Question

In R, I have a table with Location, sample_year and count. So,

Location sample_year count  
A        1995        1
A        1995        1  
A        2000        3  
B        2000        1  
B        2000        1  
B        2000        5

I want a summary table that examines both the 'Location' and 'sample_year' columns and sums 'count' dependent on this unique combination instead of just a single column. So, end result should be:

Location sample_year sum_count
A        1995        2
A        2000        3
B        2000        7

I could merge columns and data into a new column to create unique a Location-sample_year but this is not a clean solution, esp if I need to scale it up to three columns at some point. There must be a better approach.

Answer 1

You can use aggregate with a formula.

First the data:

x <- read.table(textConnection("Location sample_year count  
A        1995        1
A        1995        1  
A        2000        3  
B        2000        1  
B        2000        1  
B        2000        5"), header = TRUE)

Aggregate using sum with a formula specifying the grouping:

aggregate(count ~ Location+sample_year, data = x, sum)
    Location sample_year count
1        A        1995     2
2        A        2000     3
3        B        2000     7