Create a ggplot with grouped factor levels - r

Question

This is variation on a question asked here: Group factor levels in ggplot.
I have a dataframe:
df <- data.frame(respondent = factor(c(1, 2, 3, 4, 5, 6, 7)),
location = factor(c("California", "Oregon", "Mexico",
"Texas", "Canada", "Mexico", "Canada")))
There are three separate levels related to the US. I don't want to collapse them as the distinction between states is useful for data analysis. I would like to have, however, a basic barplot that combines the three US states and stacks them on top of one another, so that there are three bars in the barplot--Canada, Mexico, and US--with the US bar divided into three states like so:
If the state factor levels had the "US" in their names, e.g. "US: California", I could use
library(tidyverse)
with_states <- df %>%
separate(location, into = c("Country", "State"), sep = ": ") %>%
replace_na(list(State = "Other")) %>%
mutate(State = as.factor(State)
%>% fct_relevel("Other", after = Inf))
to achieve the desired outcome. But how can this be done when R doesn't know that the three states are in the US?

Answer 1

If you look at the previous example, all the separate and replace_na functions do is separate the location variable into a country and state variable:
df
respondent location
1 1 US: California
2 2 US: Oregon
3 3 Mexico
...
df %>%
separate(location, into = c("Country", "State"), sep = ": ") %>%
replace_na(list(State = "Other"))
respondent Country State
1 1 US California
2 2 US Oregon
3 3 Mexico Other
...
So really all you need to do if get your data into this format: with a column for country and a column for state/provence.
There are many ways to do this yourself. Many times your data will already be in this format. If it isn't, the easiest way to fix it is to do a join to a table which maps location to country:
df
respondent location
1 1 California
2 2 Oregon
3 3 Mexico
4 4 Texas
5 5 Canada
6 6 Mexico
7 7 Canada
state_mapping <- data.frame(state = c("California", "Oregon", "Texas"),
country = c('US', 'US', 'US'),
stringsAsFactors = F)
df %>%
left_join(state_mapping, by = c('location' = 'state')) %>%
mutate(country = if_else(is.na(.$country),
location,
country))
respondent location country
1 1 California US
2 2 Oregon US
3 3 Mexico Mexico
4 4 Texas US
5 5 Canada Canada
6 6 Mexico Mexico
7 7 Canada Canada
Once you've got it in this format, you can just do what the other question suggested.