name variable at the same time using complete - r

Question

I would like to get a sub total by age group. The sample data and the codes are:
set.seed(12345)
#create a numeric variable Age
AGE <- sample(0:110, 100, replace = TRUE)
# Creat Data fame
Sample.data <-data.frame(AGE)
summary_data<- Sample.data %>%
group_by(grp = cut(
AGE,
breaks=c(-Inf, 0,0.001, 0.083, 2, 13, 65,1000),
right=TRUE,
labels = c("Foetus(0 yr)","Neonate (0.001 - 0.082 yr)","Infant(0.083-1.999 yrs)","Child(2-12.999 yrs)", "Adolescent(13-17.999 yrs)","Adult(18-64.999 yrs.)","Elderly(65-199 yrs)")
)) %>% summarise("Total People" = n())%>% complete(grp = levels(grp), fill = list("Total People = 0))
which gave the results that looks like this:
Is it possible to label grp as "Age Group"? and sort it by age?
I tried to define the name as follow and the results are strange. What did I do wrong?
summary_data<- Sample.data %>%
group_by("Age Group" = cut(
AGE,
breaks=c(-Inf, 0,0.001, 0.083, 2, 13, 65,1000),
right=TRUE,
labels = c("Foetus(0 yr)","Neonate (0.001 - 0.082 yr)","Infant(0.083-1.999 yrs)","Child(2-12.999 yrs)", "Adolescent(13-17.999 yrs)","Adult(18-64.999 yrs.)","Elderly(65-199 yrs)")
)) %>% summarise("Total People" = n())%>% complete("Age Group" = levels("Age Group"), fill = list("Total People" = 0))
The new results are:
The variable now has name "Age Group", but table doesn't fill 0 for the age category that do not have observation. What should I do.
The ideal results should look like this:

Answer 1

We can change the double quotes to backquotes in levels to evaluate the column in complete. The column name is non-standard i.e. it includes a space.
...
%>%
complete("Age Group" = levels(`Age Group`), fill = list("Total People" = 0))
# A tibble: 7 x 2
# `Age Group` `Total People`
# <chr> <dbl>
#1 Adolescent(13-17.999 yrs) 14
#2 Adult(18-64.999 yrs.) 37
#3 Child(2-12.999 yrs) 2
#4 Elderly(65-199 yrs) 46
#5 Foetus(0 yr) 1
#6 Infant(0.083-1.999 yrs) 0
#7 Neonate (0.001 - 0.082 yr) 0
If we want to arrange
Sample.data %>%
group_by("Age Group" = cut(
AGE,
breaks=c(-Inf, 0,0.001, 0.083, 2, 13, 65,1000),
right=TRUE,
labels = c("Foetus(0 yr)","Neonate (0.001 - 0.082 yr)","Infant(0.083-1.999 yrs)","Child(2-12.999 yrs)", "Adolescent(13-17.999 yrs)","Adult(18-64.999 yrs.)","Elderly(65-199 yrs)")
)) %>%
summarise("Total People" = n()) %>%
complete("Age Group" = levels(`Age Group`), fill = list("Total People" = 0)) %>%
arrange(`Total People`)