Data imputation based on the mean of the numeric variable and the frequency count of a categorical variable

Question

I have a data frame having many rows that contain random missing variable of Gender and Age. A similar count of Gender and Age together with the missing values is represented below using the below DF. From the DF, the % population of females is 60%, & the average mean of males and females is 33 and 39 respectively.

Gender <- c("Male", " ", " ", "Female", "Female", " ",  " ", "Male", " ", "Female")
Age <- c(' ', 33, 33, 39, 39, 33,33, 33, 32, 39)
Data2 <- data.frame(Gender, Age)
Data2$Age <- as.numeric(Data2$Age)
Data2$Gender <- as.character(Data2$Gender)

I'd like to impute the missing values according to the count proportion of males and females and the mean values of males and females.

How do I do that in R?