I am a beginner coder so bear with me

I have a (non-shareable) data frame of cases of disease (each row is a person with a disease) and columns corresponding to their age group (Age_Grp_15) and their quintile of marginalization (AGE_LABOURFORCE_Q_CSDUID).

I want to create a summary table of case counts based on age and marginalization. So far, I have:

count_age <- marg_data_1920 %>%
  group_by(Age_Grp_15, AGE_LABOURFORCE_Q_CSDUID) %>%
  summarise(count = n()) %>%
  spread(AGE_LABOURFORCE_Q_CSDUID, count, fill = 0)

Here is something I have done successfully with the same code. All cells fill with numbers as they should
https://i.sstatic.net/gwa4pLrI.png

However, my disease data frame does not have any cases in my first quintile (see: https://i.sstatic.net/oTolfWPA.png). I want to force R to list the first quintile column and fill it with zeroes in cases when there is no data. I would appreciate my code forcing any empty column to show up

I have tried the code below suggested by ChatGPT, which has not worked at all

count_age <- marg_data_1920 %>%
  group_by(Age_Grp_15, AGE_LABOURFORCE_Q_CSDUID) %>%
  summarise(count = n()) %>%
  complete(Age_Grp_15, nesting(AGE_LABOURFORCE_Q_CSDUID), fill = list(count = 0)) %>%
  spread(AGE_LABOURFORCE_Q_CSDUID, count, fill = 0) %>%
  rename(age = Age_Grp_15)

colnames(count_age) <- c("age", "q_1","q_2","q_3","q_4","q_5")