Plotting binned data using sum instead of count

Question

I\'ve tried to search for an answer, but can\'t seem to find the right one that does the job for me.

I have a dataset (data) with two variables: people\

Answer 1

We can use the aggregate function and then use the ggplot2 package. I don't make too many barplots in base R these days so I'm not sure of the best way to do it without loading ggplot2:

create sample data

#data
set.seed(123)
dat <- data.frame(age = sample(20:50, 200, replace = TRUE),
                  awards = rpois(200, 3))
head(dat)
  age awards
1  28      2
2  44      6
3  32      3
4  47      3
5  49      2
6  21      5

By age

#aggregate

sum_by_age <- aggregate(awards ~ age, data = dat, FUN = sum)

library(ggplot2)

ggplot(sum_by_age, aes(x = age, y = awards))+
    geom_bar(stat = 'identity')

By age group

#create groups

dat$age_group <- ifelse(dat$age <= 30, '20-30',
                        ifelse(dat$age <= 40, '30-40',
                               '41 +'))

sum_by_age_group <- aggregate(awards ~ age_group, data = dat, FUN = sum)

ggplot(sum_by_age_group, aes(x = age_group, y = awards))+
    geom_bar(stat = 'identity')

Note

We could skip the aggregate step altogether and just use:

ggplot(dat, aes(x = age, y = awards)) + geom_bar(stat = 'identity')

but I don't prefer that way because I think having an intermediate data step may be useful within your analytical pipeline for comparisons other than visualizing.