Weighted mean with by function

Question

Trying to get weighted mean for a couple of categories want to use by(df$A,df$B,function(x) weighted.mean(x,df$C)) This doesn\'t work of course. Is there a way to do this using

Answer 1

You need to pass the weights along with the values to be averaged in by():

by(df[c("A","C")], df$B, function(x) weighted.mean(x$A, x$C))
# df$B: gb
# [1] 4
# ------------------------------------------------------------ 
# df$B: hi
# [1] 25.44444
# ------------------------------------------------------------ 
# df$B: yo
# [1] 3

Answer 2

Here's a simple and efficient solution using data.table

library(data.table)
setDT(df)[, .(WM = weighted.mean(A, C)), B]
#     B       WM
# 1: hi 25.44444
# 2: gb  4.00000
# 3: yo  3.00000

Or using split and apply combination from base R

sapply(split(df, df$B), function(x) weighted.mean(x$A, x$C))
#      gb       hi       yo 
# 4.00000 25.44444  3.00000 

Or

library(dplyr)
df %>%
  group_by(B) %>%
  summarise(WM = weighted.mean(A, C))
# Source: local data frame [3 x 2]
# 
# B       WM
# 1 gb  4.00000
# 2 hi 25.44444
# 3 yo  3.00000

Answer 3

Or simply recreate the calculation used by weighted.mean():

by(df,df$B,function(df)with(df,sum(A*C)/sum(C)))

df$B: gb
[1] 4
------------------------------------------------------------ 
df$B: hi
[1] 25.44444
------------------------------------------------------------ 
df$B: yo
[1] 3