I have an issue where I am trying to transform a data frame into a summarized data frame with total sums and weighted averages based on multiple columns...

Below is an example of what I am doing...

df <- data.frame('title' = c("X", "Y", "Z", "X", "Y", "Z"),'date' = c("2020-01-01", "2020-01-01", "2020-01-01", "2020-01-02", "2020-01-03", "2020-01-02"),'weight1' = c(84024, 54241, 106601, 65382, 337007, 687682),'weight2' = c(30, 30, 30, 15, 15, 15),'metric1' = c(3.08, 0.964, 0.839, 1.60, 0.839, 0.648),'metric2' = c(588.03, 298.26, 13.95, 104.29, 10.51, 72.53))

agg = df %>% 
          group_by(df$date, df$title) %>%
          summarise(total_weight1 = sum(weight1, na.rm=TRUE), # total sum
          total_weight1 = sum(weight2, na.rm=TRUE), # total sum
          mean_metric1 = weighted.mean(x = metric1, w = c(weight1, weight2), na.rm=T), # weighted avg
          mean_metric2 = weighted.mean(x = metric2, w = c(weight1, weight2), na.rm=T)) # weighted avg

But of course, I get an error message:

Error in summarise():

Problem while computing mean_metric1 = weighted.mean(x = metric1, w = c(weight1, weight2), na.rm = T). The error occurred in group 1: df$date = "2020-01-01", df$title = "X".

Caused by error in weighted.mean.default():

! 'x' and 'w' must have the same length

Is it possible to calculate the weighted average of a value based on two columns? I've tried finding other sources to validate this calculation manually but have failed...

I'm also not sure if calculating this all in the same data frame is the right way to go. Any guidance would be appreciated.

I've tried other sources and functions including rowwise() and mutate() but I keep running into the same issue that my 'x' and 'w' need to have the same length...