Aggregate using weighted mean

Asked Jan 29 '18 at 15:01

Active Jan 29 '18 at 15:55

Viewed 60 times

I am trying to calculate average age of each US county weighted by the population of each age group in my data.

My data set looks like this:

state                  county    age    population   
   AL                 Autauga      1       2366         
   AL                 Autauga      2       3029         
   AL                 Autauga      3       3619          
   AL                 Autauga      4       3043          
   AL                 Autauga      5       3776

I'm trying to run something like this:

agedata <- aggregate(data$age, list(data$state, data$county), weighted.mean(data$age, data$population))

Whenever I run this command I get the following error:

Error in match.fun(FUN) : 'weighted.mean(fulldata$age, fulldata$population)' is not a function, character or symbol

edited Jan 29 '18 at 15:55

vaettchen

7,299
22
41

asked Jan 29 '18 at 15:01

CiaranM

1

`data %>% group_by(state, county) %>% summarize(weighted.mean(age, population))` – IceCreamToucan Jan 29 '18 at 15:07
2

You can use `by`, i.e. `by(df, list(df$state, df$country), function(i) weighted.mean(i$Age, i$population))` – Sotos Jan 29 '18 at 15:08
aggregate(.~state+country,df,weighted.mean) – Onyambu Jan 29 '18 at 15:30
@Onyambu `county` not `country` – Imran Ali Jan 29 '18 at 15:31
`agedata <- aggregate( cbind( data$age, data$population), list(data$state, data$county), weighted.mean)` – vaettchen Jan 29 '18 at 16:04

Aggregate using weighted mean

0 Answers0