In this example, I want compare population in USA versus China, over time.
library(tidyverse)
population %>%
filter(country %in% c("United States of America", "China")) %>%
pivot_wider(names_from = country, values_from = population) %>%
rename(USA = `United States of America`) %>%
ggplot(aes(x = China, y = USA)) geom_point(aes(col = year))
Is there a better way to do this (without using pivot_wider
)? Or is this the right way?
Thanks in advance
CodePudding user response:
Not sure if this is still what you want, but I'd expect th comparison between two population sizes over time to look something like this:
library(ggplot2)
library(dplyr)
population %>%
filter(country %in% c("United States of America", "China")) %>%
ggplot(aes(x = year, y = population, color=country))
geom_line()
expand_limits(y=0)
Returns:
CodePudding user response:
It is the right way if you want to show how the population of USA varies as a function of the population of China... but what's the sense of it? Probably what you want is to compare how the two population change as a function of time, then I think you'd be better off with a bar chart:
library(tidyverse)
population %>%
filter(country %in% c("United States of America", "China")) %>%
ggplot(aes(x = year, y=population, fill=country))
geom_col(position="dodge")
Created on 2021-09-28 by the reprex package (v2.0.1)