Multiple Ggplots of Different Sizes

Multiple ggplots of different sizes

I appreciate all the other answers, but Didzis Elferts's comment on the OP connected to the answer that I found easiest to implement.

library(ggplot2)
p1 <- qplot(x=wt,y=mpg,geom="point",main="Scatterplot of wt vs. mpg", data=mtcars)
p2 <- qplot(x=wt,y=disp,geom="point",main="Scatterplot of wt vs disp", data=mtcars)
p3 <- qplot(wt,data=mtcars)
p4 <- qplot(wt,mpg,data=mtcars,geom="boxplot")
p5 <- qplot(wt,data=mtcars)
p6 <- qplot(mpg,data=mtcars)
p7 <- qplot(disp,data=mtcars)
p8 <- qplot(disp, y=..density.., geom="density", data=mtcars)
p9 <- qplot(mpg, y=..density.., geom="density", data=mtcars)

vplayout <- function(x, y) viewport(layout.pos.row = x, layout.pos.col = y)

grid.newpage()
pushViewport(viewport(layout = grid.layout(3, 5))) # 3 rows, 5 columns
print(p1, vp = vplayout(1:2, 1:3))  # the big plot covers rows 1:2 and cols 1:3
print(p2, vp = vplayout(1, 4))
print(p3, vp = vplayout(1, 5))
print(p4, vp = vplayout(2, 4))
print(p5, vp = vplayout(2, 5))
print(p6, vp = vplayout(3, 1))
print(p7, vp = vplayout(3, 2))
print(p8, vp = vplayout(3, 3))
print(p9, vp = vplayout(3, 4:5))

multiple different sized plots in same window in R?

EDIT -- fixed to shrink third chart per OP.

library(patchwork)
design <- c(         # we specify the top, left, bottom, and right
  area(1, 1, 4, 4),  # coordinates for each of the three plots
  area(1, 5, 2, 6),
  area(3, 5)
)
allPlots[[1]] +  allPlots[[2]] + allPlots[[3]] + 
  plot_layout(design = design)

combine ggplots from dataframes with different lengths

We don't have your data, so here's an example with a dataset included in ggplot2:

library(ggplot2)
df1 <- diamonds[1:10,7]
df2 <- diamonds[100:2100,7]

For this example, the data in df1 is much less varied and so the density spike is ~25x higher.

ggplot() +
  geom_density(data = df1, aes(x = price)) +
  geom_vline(data = df1, aes(xintercept = mean(price)), 
             linetype = "dashed", size = 0.6) +
  geom_density(data = df2, aes(x = price), color = "red") +
  geom_vline(data = df2, aes(xintercept = mean(price)), 
             linetype = "dashed", color = "red", size = 0.6) 

One way to deal with this would be to scale the df2 density up 25x and to create a secondary axis with the inverse adjustment. (This is how secondary axes work in ggplot2; you first scale the data into the primary axis, and then create a secondary axis as an annotation that helps the reader interpret it.)

ggplot() +
  geom_density(data = df1, aes(x = price)) +
  geom_vline(data = df1, aes(xintercept = mean(price)), 
             linetype = "dashed", size = 0.6) +
  geom_density(data = df2, aes(x = price, y = ..density.. * 25), color = "red") +
  geom_vline(data = df2, aes(xintercept = mean(price)), 
             linetype = "dashed", color = "red", size = 0.6) +
  scale_y_continuous(sec.axis = ~ . / 25) +
  theme(axis.text.y.right = element_text(color = "red"))

R: Plotting Columns of Different Sizes on Same Graph

Well, from code you provide, I didn't need to change shape of data. Just use guides(... = guide_legend(title = ...)) and scale_colour_discrete to manually change the legend's components.

ggplot() + 
  geom_density(data=my_data_1, aes(x=height), color='green') + 
  stat_density(data = my_data_1, aes(x=height, colour="red"), geom="line",position="identity") + 
  geom_density(data=my_data_2, aes(x=prior_height), color='red') + 
  stat_density(aes(x=prior_height, colour='green'), geom="line",position="identity") +
  guides(colour = guide_legend(title = "new title"),) +
  scale_colour_discrete(labels = c( "prior", "measurements"))

Error when combining ggplots from different datasets (of different sizes) using grid.arrange

Removing the reference to the dataframe in the aes() inside the ggplot calls seems to fix the issue.

So instead of writing

ggplot(dataset,aes(dataset$PC1w1)

writing

ggplot(dataset,aes(PC1w1)

for each ggplot call does the trick.
I am not quite sure why this fixes it, however, and got the answer from a different blog

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