Align Ggplot2 Plots Vertically

Align ggplot2 plots vertically

Here's an example to align more basic grobs,

library(ggplot2)
library(grid)
library(gtable)

p <- qplot(1,1)
g <- ggplotGrob(p)

panel_id <- g$layout[g$layout$name == "panel",c("t","l")]
g <- gtable_add_cols(g, unit(1,"cm"))

g <- gtable_add_grob(g, rectGrob(gp=gpar(fill="red")),
                     t = panel_id$t, l = ncol(g))

g <- gtable_add_rows(g, unit(1,"in"), 0)
g <- gtable_add_grob(g, rectGrob(gp=gpar(fill="blue")),
                     t = 1, l = panel_id$l)

grid.newpage()
grid.draw(g)

and with your grobs

How to align bar plots vertically to get same width for each bar with different numbers of x

First, I don't believe this is possible without some serious hack. I think you will fare better with a bit of a workaround.

My first answer (now second option here) was to create fake factor levels. This certainly brings perfect alignment of the categories.

Another option (now option 1 here) would be to play around with the expand argument. Below a programmatic approach to it.

I added a rectangle to make it seem as if there was no further plot. This could be done with the respective background fill of your theme.

But in the end, I still think you could get nicer and much easier results with faceting.

One option

library(ggplot2)
library(cowplot)

d1 = data.frame(length = c('large', 'medium', 'small'), meters = c(100, 50, 30))

d2 = data.frame(speed = c('high', 'slow'), value =c(200, 45))

d3 = data.frame(key = c('high', 'slow', 'veryslow', 'superslow'), value = 1:4)

n_unq1 <- length(d1$length)
n_unq2 <- length(d2$speed)
n_unq3 <- length(d3$key)
n_x <- max(n_unq1, n_unq2, n_unq3)
#p1 = 
expand_n <- function(n_unq){
  if((n_x - n_unq)==0 ){
  waiver()
} else {
  expansion(add = c(0.6, (n_x-n_unq+0.56)))
}
}

p1 <- 
  ggplot(d1, aes(x = length, y = meters, fill = length)) +
  geom_col() +
  scale_fill_viridis_d() +
  scale_x_discrete(expand= expand_n(n_unq1)) +
  annotate(geom = 'rect', xmin = n_unq1+0.5, xmax = Inf, ymin = -Inf, ymax = Inf, fill = 'white')

p2 <- 
  ggplot(d2, aes(x = speed, y = value, fill = speed)) +
  geom_col() +
  scale_fill_viridis_d() +
  scale_x_discrete(expand= expand_n(n_unq2)) +
  annotate(geom = 'rect', xmin = n_unq2+0.5, xmax = Inf, ymin = -Inf, ymax = Inf, fill = 'white')

p3 <- 
  ggplot(d3, aes(x = key, y = value, fill = key)) +
  geom_col() +
  scale_fill_viridis_d() +
  scale_x_discrete(expand= expand_n(n_unq3)) +
  annotate(geom = 'rect', xmin = n_unq3+0.5, xmax = Inf, ymin = -Inf, ymax = Inf, fill = 'white')

p_ls = list(p1, p2,p3)

plot_grid(plotlist = p_ls, align = 'v', ncol = 1)

^{Created on 2020-04-24 by the reprex package (v0.3.0)}

Option 2, create n fake factor levels up to the maximum level of the plot and then use drop = FALSE . Here a programmatic approach to it

library(tidyverse)
library(cowplot)

n_unq1 <- length(d1$length)
n_unq2 <- length(d2$speed)
n_unq3 <- length(d3$key)
n_x <- max(n_unq1, n_unq2, n_unq3)

make_levels <- function(x, value) {
  x[[value]] <- as.character(x[[value]])
  l <- length(unique(x[[value]]))

  add_lev <- n_x - l

  if (add_lev == 0) {
    x[[value]] <- as.factor(x[[value]])
    x
  } else {
    dummy_lev <- map_chr(1:add_lev, function(i) paste(rep(" ", i), collapse = ""))
    x[[value]] <- factor(x[[value]], levels = c(unique(x[[value]]), dummy_lev))
    x
  }
}

list_df <- list(d1, d2, d3)
list_val <- c("length", "speed", "key")

fac_list <- purrr::pmap(.l = list(list_df, list_val), function(x, y) make_levels(x = x, value = y))

p1 <-
  ggplot(fac_list[[1]], aes(x = length, y = meters, fill = length)) +
  geom_col() +
  scale_fill_viridis_d() +
  scale_x_discrete(drop = FALSE) +
  annotate(geom = "rect", xmin = n_unq1 + 0.56, xmax = Inf, ymin = -Inf, ymax = Inf, fill = "white") +
  theme(axis.ticks.x = element_blank())
p2 <-
  ggplot(fac_list[[2]], aes(x = speed, y = value, fill = speed)) +
  geom_col() +
  scale_fill_viridis_d() +
  scale_x_discrete(drop = FALSE) +
  annotate(geom = "rect", xmin = n_unq2 + 0.56, xmax = Inf, ymin = -Inf, ymax = Inf, fill = "white") +
  theme(axis.ticks.x = element_blank())
p3 <-
  ggplot(fac_list[[3]], aes(x = key, y = value, fill = key)) +
  geom_col() +
  scale_fill_viridis_d() +
  scale_x_discrete(drop = FALSE) +
  annotate(geom = "rect", xmin = n_unq3 + 0.56, xmax = Inf, ymin = -Inf, ymax = Inf, fill = "white") +
  theme(axis.ticks.x = element_blank())

p_ls <- list(p1, p2, p3)

plot_grid(plotlist = p_ls, align = "v", ncol = 1)

^{Created on 2020-04-24 by the reprex package (v0.3.0)}

How to align vertically combined plots which are build with viewport

You can use cowplot::plot_grid

# figures
library(cowplot)
tiff("test0.tiff", width=5, height=10, units="cm", res=300, compression = 'lzw')
grid.newpage()
plot_grid(p1, p2, align = "v", nrow = 2, rel_heights = c(1/2, 1/2))
dev.off()

Note: I don't know how you set up df0 so cannot present exported plot.

Align plot with different axes vertically using Cowplot

A cowplot solution by Claus O. Wilke is presented here.

It is based on the align_plot function, which first aligns the top plot with the left bottom plot along the y-axis. Then the aligned plots are passed to the plot_grid function.

# Libraries
library(tidyverse)
library(cowplot)

df1 <- data.frame(x = seq(0, 100, 1), 
                  y = seq(100, 0, -1))

df2 <- data.frame(x = seq(0, 10, 0.1), 
                  y = seq(1, 10^9, length.out = 101 ) )

p1 <- ggplot(data = df1) + 
  geom_line(aes(x = x, y = y))

p2 <- ggplot(data = df2) + 
  geom_line(aes(x = x, y = y))

plots <- align_plots(p1, p2, align = 'v', axis = 'l')
bottom_row <- plot_grid(plots[[2]], p2, nrow = 1)

plot_grid(plots[[1]], bottom_row, ncol = 1)

Cowplot Package: How to align legends vertically downwards after arranging many plots into one plot using plot_grid() in R

Condensing your over-long example to a simpler version with just 2 panels that shows the problem:

plot_grid(Urban1, Stand1, align = "v", ncol = 1)

we can align the legends using theme(legend.justification = ...

plot_grid(
  Urban1 + theme(legend.justification = c(0,1)), 
  Stand1 + theme(legend.justification = c(0,1)), 
  align = "v", ncol = 1)

Align vertically and horizontally plot R ggplot2

As @Axeman mentioned, it is caused by legends, cowplot::get_legend() can fix this (see ?cowplot::get_legend() for your exact case):

legend_p1 <- get_legend(p1)
legend_p3 <- get_legend(p3)

p1 <- p1 + theme(legend.position='none')
p3 <- p3 + theme(legend.position='none')

cowplot::plot_grid(
  cowplot::plot_grid(legend_p1, legend_p3, ncol = 1),
  cowplot::plot_grid(p3, NULL, p1, p2,  ncol = 2, nrow = 2, rel_widths = c(1, 0.75, 1, 0.75), labels = c('A', '', 'C', 'D'), align = "hv"),
  rel_widths = c(0.1, 1))

but it needs quite a lot of work to make it "readable".

Data ("raw", apply all transformations from the OP postt):

a <- data.frame(
  id = 1:15,
  GO = c(
    "phosphoglycerate kinase", "phosphoglycerate kinase", 
    "phosphoglycerate kinase", "phosphoglycerate kinase", "phosphoglycerate kinase", 
    "phenylalanine-tRNA ligase", "phenylalanine-tRNA ligase", "phenylalanine-tRNA ligase", 
    "phenylalanine-tRNA ligase", "phenylalanine-tRNA ligase", "allantoicase", 
    "allantoicase", "allantoicase", "allantoicase", "allantoicase"),
  variable = c(
    "d64", "d31", "d16", "d9", "d0", "d64", "d31", "d16", "d9", "d0", "d64", "d31", "d16", "d9", "d0"),
  value = c(
    154.28239, 226.04355, 245.67728, 271.82375, 270.83519, 289.01809, 491.66461,
    485.28291, 351.3759, 510.96043, 22.75253, 31.66546, 129.50564, 206.6651, 32.43769),
  relAbundByGO = c(
    13.201624, 19.342078, 21.022096, 23.259395, 23.174806, 13.57975, 23.101262,
    22.801413, 16.509683, 24.007892, 5.378513, 7.485456, 30.614078, 48.853948, 7.668005),
  GOd = c(
    "phosphoglycerate kinase", "phosphoglycerate kinase", 
    "phosphoglycerate kinase", "phosphoglycerate kinase", "phosphoglycerate kinase", 
    "phenylalanine-tRNA ligase", "phenylalanine-tRNA ligase", "phenylalanine-tRNA ligase", 
    "phenylalanine-tRNA ligase", "phenylalanine-tRNA ligase", "allantoicase", 
    "allantoicase", "allantoicase", "allantoicase", "allantoicase"
  ))
b <- data.frame(
  id = 1:15,
  Compound = c(
    "C5-C10", "C5-C10", "C5-C10", 
    "C5-C10", "C5-C10", "C10-C20", "C10-C20", "C10-C20", "C10-C20", 
    "C10-C20", "BTEX", "BTEX", "BTEX", "BTEX", "BTEX"),
  Degradation = c(
    100, 100, 23.5, 5.6, 0, 100, 100, 67.2, 19, 0.6, 100, 100, 88.7, 43.3, 0.1),
  st ()dev = c(
    0, 0, 35, 12.4, 0, 0, 0, 19.3, 13.1, 0.6, 0, 0, 33.4, 43.4, 0.2),
  day = c(
    "NSWOD-0", "NSWOD-64", "NSOD-9", 
    "NSOD-16", "NSOD-31", "NSWOD-0", "NSWOD-64", "NSOD-9", "NSOD-16", 
    "NSOD-31", "NSWOD-0", "NSWOD-64", "NSOD-9", "NSOD-16", "NSOD-31"))

Aligning a geom_text layer vertically on a bar chart

You can set a uniform label height for each group using if_else (or case_when for >2 groups). For a single plot, you can simply set a value, e.g., label_height = if_else(college_enrolled == "Enrolled", 20000, 3000). To make the relative height consistent across multiple plots, you can instead set label_height as a proportion of the y-axis range:

library(tidyverse)

# make a fake dataset
enroll_cohort <- expand_grid(
    chrt_grad = factor(2014:2021),
    college_enrolled = factor(c("Enrolled", "Not Enrolled")),
  ) %>%
  mutate(
    n = sample(18000:26000, 16),
    n = if_else(college_enrolled == "Enrolled", n, as.integer(n / 3))
  )

enroll_bar <- enroll_cohort %>% 
  group_by(chrt_grad) %>%            # find each bar's height by summing up `n`
  mutate(bar_height = sum(n)) %>%    # within each year
  ungroup() %>%
  mutate(label_height = if_else(
    college_enrolled == "Enrolled", 
    max(bar_height) * .6,            # axis height is max() of bar heights;
    max(bar_height) * .1             # set label_height as % of axis height
  )) %>%
  ggplot() +
  geom_col(aes(x = chrt_grad, y = n, fill = college_enrolled), color = NA) +
  geom_text(
    aes(x = chrt_grad, y = label_height, label = n), 
    color = "white"
  ) +
  scale_y_continuous(expand = expansion(mult = c(0, 0.1))) +
  labs(x = NULL, y = NULL) +
  scale_fill_manual(values = c("#00aeff", "#005488"))

If we generate another dataset with a different range of n values -- e.g., ~1200 - ~2000 -- the text labels stay at the same relative positions:

Aligning basic ggplots with faceted ggplots in ggarrange (R)

Here is a solution using the patchwork package. Assume we have setup the plots p1 and p3 as described in the original post. Then, with some patchwork magic, we combine the plots. The / operator indicates that p1 should be above p3.

library(patchwork)
p1 / p3

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