This is an example script for how to compute weights in base R using demographic variables like age & gender and then how to calculate frequencies while applying those weights

survey_data_weighting.R

#
#You have a dataframe "df", with variables gender and age, and other variables of interest about radio listenership
#

#Add weights below. The population parameter over the prop.table(..) portion calculating sample statistics.

weight_male = .49500764/(prop.table(table(df$Gender))["Male"])
weight_male
weight_female = .50499236/(prop.table(table(df$Gender))["Female"])
weight_female

weight_15to24 = .31/prop.table(table(df$agecat))["15 to 24"]
weight_15to24
weight_25to34 = .25/prop.table(table(df$agecat))["25 to 34"]
weight_25to34
weight_35plus = .45/prop.table(table(df$agecat))["35+"]
weight_35plus

#Multiply weights to achieve total weight for each record in your dataset

df$weight = 1.0
 
df$weight[df$Gender == "Male"] = sapply(
                                 df$weight[df$Gender == "Male"], function(x) x*weight_male)
df$weight[df$Gender == "Female"] = sapply(
                                 df$weight[df$Gender == "Female"], function(y) y*weight_female)

df$weight[df$agecat == "15 to 24"] = sapply(
                                     df$weight[df$agecat == "15 to 24"], function(x) x*weight_15to24)
df$weight[df$agecat == "25 to 35"] = sapply(
                                     df$weight[df$agecat == "25 to 35"], function(x) x*weight_25to34)
df$weight[df$agecat == "35+"] = sapply(
                                df$weight[df$agecat == "35+"], function(x) x*weight_35plus)


#turn back into vector
df$weight = unlist(df$weight)

first_weight = sum(df$weight)
table(df$weight)

first_weight

#plus one last rebalancing to bring the N back to the total N, if needed
df$weight = sapply(df$weight, function(x) x*nrow(df)/first_weight)

#turn back into vector
df$weight = unlist(df$weight)

#these two should now be the same
sum(df$weight)
table(df$weight)

#Weighted frequency function
table_wght<- function (x){
  z=df$weight
  N<-xtabs(z~x)
  return(N)
}

#Radio listenership analysis

table(df$RadioHr2)
table(df$RadioHr4)

table_wght(df$RadioHr2)
table_wght(df$RadioHr4)