Multi-row x-axis labels in ggplot line chart

RGgplot2

R Problem Overview


Edit: This question has been marked as duplicated, but the responses here have been tried and did not work because the case in question is a line chart, not a bar chart. Applying those methods produces a chart with 5 lines, 1 for each year - not useful. Did anyone who voted to mark as duplicate actually try those approaches on the sample dataset supplied with this question? If so please post as an answer.

Original Question:

There's a feature in Excel pivot charts which allows multilevel categorical axes.I'm trying to find a way to do the same thing with ggplot (or any other plotting package in R).

Consider the following dataset:

set.seed(1)
df=data.frame(year=rep(2009:2013,each=4),
              quarter=rep(c("Q1","Q2","Q3","Q4"),5),
              sales=40:59+rnorm(20,sd=5))

If this is imported to an Excel pivot table, it is straightforward to create the following chart:

Note how the x-axis has two levels, one for quarter and one for the grouping variable, year. Are multilevel axes possible with ggplot?

NB: There is a hack with facets that produces something similar, but this is not what I'm looking for.

library(ggplot2)
ggplot(df) +
  geom_line(aes(x=quarter,y=sales,group=year))+
  facet_grid(.~year,scales="free")

R Solutions


Solution 1 - R

New labels are added using annotate(geom = "text",. Turn off clipping of x axis labels with clip = "off" in coord_cartesian.

Use theme to add extra margins (plot.margin) and remove (element_blank()) x axis text (axis.title.x, axis.text.x) and vertical grid lines (panel.grid.x).

library(ggplot2)

ggplot(data = df, aes(x = interaction(year, quarter, lex.order = TRUE), 
                      y = sales, group = 1)) +
  geom_line(colour = "blue") +
  annotate(geom = "text", x = seq_len(nrow(df)), y = 34, label = df$quarter, size = 4) +
  annotate(geom = "text", x = 2.5 + 4 * (0:4), y = 32, label = unique(df$year), size = 6) +
  coord_cartesian(ylim = c(35, 65), expand = FALSE, clip = "off") +
  theme_bw() +
  theme(plot.margin = unit(c(1, 1, 4, 1), "lines"),
        axis.title.x = element_blank(),
        axis.text.x = element_blank(),
        panel.grid.major.x = element_blank(),
        panel.grid.minor.x = element_blank())

enter image description here


See also the nice answer by @eipi10 here: Axis labels on two lines with nested x variables (year below months)

Solution 2 - R

The suggested code by Henrik does work and helped me a lot! I think the solution has a high value. But please be aware, that there is a small misstake in the first line of the code, which results in a wrong order of the data. Instead of

... aes(x = interaction(year,quarter), ...

it should be

... aes(x = interaction(quarter,year), ...

The resulting graphic has the data in the right order.

enter image description here

P.S. I suggested an edit (which was rejected until now) and, due to a small lack of reputation, I am not allowed to comment, what I rather would have done.

Solution 3 - R

User Tung had a great answer on this thread

library(tidyverse)
library(lubridate)
library(scales)

set.seed(123)
df <- tibble(
  date = as.Date(41000:42000, origin = "1899-12-30"), 
  value = c(rnorm(500, 5), rnorm(501, 10))
)

# create year column for facet
df <- df %>% 
  mutate(year = as.factor(year(date)))

p <- ggplot(df, aes(date, value)) + 
  geom_line() + 
  geom_vline(xintercept = as.numeric(df$date[yday(df$date) == 1]), color = "grey60") + 
  scale_x_date(date_labels = "%b", 
               breaks = pretty_breaks(),
               expand = c(0, 0)) +
  # switch the facet strip label to the bottom
  facet_grid(.~ year, space = 'free_x', scales = 'free_x', switch = 'x') +
  labs(x = "") +
  theme_classic(base_size = 14, base_family = 'mono') +
  theme(panel.grid.minor.x = element_blank()) + 
  # remove facet spacing on x-direction
  theme(panel.spacing.x = unit(0,"line")) +
  # switch the facet strip label to outside 
  # remove background color
  theme(strip.placement = 'outside',
        strip.background.x = element_blank())
p

Image

Attributions

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Content TypeOriginal AuthorOriginal Content on Stackoverflow
QuestionjlhowardView Question on Stackoverflow
Solution 1 - RHenrikView Answer on Stackoverflow
Solution 2 - RVDKView Answer on Stackoverflow
Solution 3 - RstackinatorView Answer on Stackoverflow