R: summarise multiple columns with different summation functions using dplyr results in error?

Question

I am transforming a customer journey dataset from user aggregation level to a day level aggregation. The problem is that I cannot simply sum or mean all columns, as not all variables can be aggregated in the same way. For example, duration is a variable that I want to summarise via mean, while purchase_own is a variable that I want to summarise via sum.

I used dplyr to get this working, but it gives me an error. I tried the following code:

CJd <- CJre %>% group_by(date) %>% summarise_at(vars(purchase_own, purchase_any, CIT, 
FIT, T1:T22, devicemobile, devicefixed, purchase_comp, POS_comp, POS_own, POS_any, 
markov, first_touch, last_touch, linear_touch), sum) 
%>% summarise_at(vars(duration, difference), mean) %>% summarise_at(CountTP, max)

This results in an error:

Error in .f(.x[[i]], ...) : object 'duration' not found

I suspect that this means that summarise_at(vars(duration, difference), mean) is not allowed as second summarise code. Now my question is, how can I write the summarise function so that summation is different for some variables?

Actual results is that only the first summarise_at gets executed, which results in missing variables in my dataset. The missing variables need to be summarised with mean and max , respectively. The expected outcome is these variables grouped by date and summarised by the named functions mean or max are added to the dataset.

Answer 1

The issue is that after the first summarise_at which didn't include 'duration', therefore, the column is not there in the summarised data. Instead, if we use mutate_at , and create a column, then get the distinct rows of the data and summarise

CJre %>%
  group_by(date) %>%
  mutate_at(vars(purchase_own, purchase_any, CIT, 
               FIT, T1:T22, devicemobile, devicefixed, purchase_comp, 
               POS_comp, POS_own, POS_any, 
              markov, first_touch, last_touch, linear_touch), sum) %>%
  group_by(purchase_own, purchase_any, CIT, 
           FIT, T1:T22, devicemobile, devicefixed, purchase_comp,
            POS_comp, POS_own, POS_any, 
            markov, first_touch, last_touch, linear_touch, add = TRUE) %>%
  summarise_at(vars(duration, difference), mean)

markov, first_touch, last_touch, linear_touch), sum)