# Create sample data
my_df <- data.frame(seq(1, 100), rep(c("ind_1", "", "", ""), times = 25), rep(c("", "ind_2", "", ""), times = 25), rep(c("", "", "ind_3", ""), times = 25), rep(c("", "", "", "ind_4"), times = 25))

# Rename columns
names(my_df)[names(my_df)=="seq.1..100."] <- "value"
names(my_df)[names(my_df)=="rep.c..ind_1................times...25."] <- "ind_1"
names(my_df)[names(my_df)=="rep.c......ind_2............times...25."] <- "ind_2"
names(my_df)[names(my_df)=="rep.c..........ind_3........times...25."] <- "ind_3"
names(my_df)[names(my_df)=="rep.c..............ind_4....times...25."] <- "ind_4"

# Replace empty elements with NA
my_df[my_df==''] = NA

# Create a vector with all individuals
individuals <- c("ind_1", "ind_2", "ind_3", "ind_4")

# Calculate aggregates for each individual
for (i in individuals){
    ind <- 1
    sum_i <- aggregate(value~ind_1, data = my_df, sum)
    print(paste("Individual", i, "possesses an aggregated value of", sum_i$value))
    ind <- ind + 1
}