How do I explain this density plot?

How do I interpret and explain this density plot?

I dont see how this is an R related question.

Not R, but definitely a data visualization question atleast! This was made in R, so thought to ask here.

The first thing I notice is that the title for the x legend is not really meaningful... "% old population". Therefore I wouldnt know to proceed with an interpretation

% old population is the the percentage of old people out of the total population in that particular country or region.

I dont see how that would make sense for a density plot.
What is the source of the chart ? maybe you should consult the author to ask them.

I would encourage you to think how a plot may be constructed, here is an example.

# mycountry has a population of 12,333,541, they have ages

ages_0_a<-rnorm(1233541,mean = 60,25)
ages_0_b<-rnorm(1233541,mean = 25,5)
ages_0 <- sample(c(ages_0_a,ages_0_b),size = 1233541,replace = FALSE)
ages_1 <- ifelse(ages_0<1,1,ages_0)
ages  <- ifelse(ages_1>120,,1),ages_1)
(my_country <- enframe(ages))

# we can plot this as a density plot, the interpretation is very natural
       mapping = aes(x=value))+


#are we simply normalising the age range and calling it a percentage ...
ggplot(data=my_country %>% mutate(v2=100*value/max(value)),
       mapping = aes(x=v2))+


# Finally,
# do we want to plot something about the age at percentile? 
 # because perhaps thats what it might mean to show how age is ditributed in a population..
 # but such a chart would look entirely different, i.e. not a density chart

(my_country2 <-mutate(my_country,
                      prank = round(percent_rank(value),2)))

(my_country3 <- group_by(my_country2,
                         prank) %>% summarise(mean_v = mean(value)))

       mapping = aes(x=prank,y=mean_v))+


This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.

If you have a query related to it or one of the replies, start a new topic and refer back with a link.