Using ggplot's facet_wrap with autocorrelation plot

Question

I want to create a ggplot figure of autocorrelations for different subgroups of my data.

Using the forecast package, I manage to produce a ggplot figure for the whole sample like this:

library(tidyverse)
library(forecast)

df <- data.frame(val = runif(100),
                key = c(rep('a', 50), key = rep('b', 50)))

ggAcf(df$val) 

Which produces:

But now I'm trying the following to produce the facets and it doesn't work:

ggplot(df) +
  ggAcf(aes(val)) +
  facet_wrap(~key) 

Any ideas?

Answer 1

A possible solution building out the acf values and plot manually.

library(tidyverse)
library(forecast)

df <- data.frame(val = runif(100),
                 key = c(rep('a', 50), key = rep('b', 50)))

df_acf <- df %>% 
  group_by(key) %>% 
  summarise(list_acf=list(acf(val, plot=FALSE))) %>%
  mutate(acf_vals=purrr::map(list_acf, ~as.numeric(.x$acf))) %>% 
  select(-list_acf) %>% 
  unnest() %>% 
  group_by(key) %>% 
  mutate(lag=row_number() - 1)

df_ci <- df %>% 
  group_by(key) %>% 
  summarise(ci = qnorm((1 + 0.95)/2)/sqrt(n()))

ggplot(df_acf, aes(x=lag, y=acf_vals)) +
  geom_bar(stat="identity", width=.05) +
  geom_hline(yintercept = 0) +
  geom_hline(data = df_ci, aes(yintercept = -ci), color="blue", linetype="dotted") +
  geom_hline(data = df_ci, aes(yintercept = ci), color="blue", linetype="dotted") +
  labs(x="Lag", y="ACF") +
  facet_wrap(~key)

Answer 2

library(forecast)
df <- data.frame(val = runif(100),
                 key = c(rep('a', 50), key = rep('b', 50)))


a = subset(df, key == "a")
ap = ggAcf(a$val)

b = subset(df, key == "b")
bp = ggAcf(b$val)


library(grid)
grid.newpage()
pushViewport(viewport(layout=grid.layout(1,2)))
print(ap, vp=viewport(layout.pos.row = 1, layout.pos.col = 1))
print(bp, vp=viewport(layout.pos.row = 1, layout.pos.col = 2))

Or:

grid.newpage()
pushViewport(viewport(layout=grid.layout(1,2)))
print(ap, vp=viewport(layout.pos.row = 1, layout.pos.col = 1))
print(bp, vp=viewport(layout.pos.row = 1, layout.pos.col = 2))

Answer 3

Adam Spannbauer's answer is excellent and the output is very similar to that of forecast::ggAcf , with possibly just the dotted confidence limits lines differing from the dashed ones produced by ggAcf (something very easy to fix if desired).

A quick and perhaps simpler alternative is to use ggfortify::autoplot with a list for your different facet values as in the example below:

# Load ggfortify
require(ggfortify)

# Create sample data frame
df <- data.frame(val = runif(100),
                 key = c(rep('a', 50), key = rep('b', 50)))

# Create list with ACF objects for different key values
acf.key <- list()
for (i in 1:length(unique(df$key))) {
  acf.key[[i]] <- acf(df$val[df$key==unique(df$key)[[i]]])
}

# Plot using ggfortify::autoplot
autoplot(acf.key, ncol=2)

Unfortunately it doesn't seem to be possible to get the banners with the facet titles above the plots as in standard ggplot , so the final result is not as polished as that of the answer above. I was also unable to remove the y-axis label of the right-hand-side plot while keeping the label of the left-hand-side plot.