R: Error when using Aggregate function to compile monthly means into yearly means

Question

Disclaimer: I'm extremely new to R and have been getting by with using google as my professor.

I have a somewhat large collection of monthly values over a period of several years from several different locations. I am attempting to use the aggregate function to calculate the yearly means for each location so that yearly rates of change can be calculated. However, when I run the code

read_csv_filename <- function(filename){
  ret <- read.csv(filename)
  ret$Source <- filename #EDIT
  ret
}

import.list <- ldply(filenames, read_csv_filename)
by1 <- import.list$Source
by2 <- import.list$Result
by3 <- import.list$Year
Yearly_Mean <- aggregate(import.list, by==list(by1, by2, by3), FUN= "mean")

I get an error like this

> Yearly_Mean <- aggregate(import.list, by==list(by1, by2, by3), FUN= "mean")
Error in by == list(by1, by2, by3) : 
  comparison (1) is possible only for atomic and list types

I've spent quite a bit of time looking here and elsewhere for similar issues, but haven't found a case that helped me out at all. Any advice on how to fix this (or a completely new, easier method) would be appreciated.

Thanks!

Answer 1

You can use the group_by() and summarize function from the dplyr package to achieve the above easily:

library(dplyr)
import.list <- ldply(filenames, read_csv_filename)

# No need to create b1, b2 and b3
#by1 <- import.list$Source
#by2 <- import.list$Result
#by3 <- import.list$Year

# here you want to group by the data based on 'Year' as you mentioned you want the yearly mean and you want to calculate mean of 'Result' right?.

import.list %>%
  group_by(Year) %>%
  summarize(Mean = mean(Result, na.rm=TRUE))->Final_Output

The above will group_by the data based on Year and calculate mean of Result column.