## How to set limits for axes in ggplot2 R plots?

Basically you have two options

`scale_x_continuous(limits = c(-5000, 5000))`

or

`coord_cartesian(xlim = c(-5000, 5000)) `

Where the first removes all data points outside the given range and the second only adjusts the visible area. In most cases you would not see the difference, but if you fit anything to the data it would probably change the fitted values.

You can also use the shorthand function `xlim`

(or `ylim`

), which like the first option removes data points outside of the given range:

`+ xlim(-5000, 5000)`

For more information check the description of ** coord_cartesian**.

The RStudio cheatsheet for `ggplot2`

makes this quite clear visually. Here is a small section of that cheatsheet:

*Distributed under CC BY*.

## Adjusting y axis limits in ggplot2 with facet and free scales

First, reproducibility with random data needs a seed. I started using `set.seed(42)`

, but that generated negative values which caused completely unrelated warnings. Being a little lazy, I changed the seed to `set.seed(2021)`

, finding all positives.

For #1, we can add `limits=`

, where the help for `?scale_y_continuous`

says that

` limits: One of:`

• 'NULL' to use the default scale range

• A numeric vector of length two providing limits of the

scale. Use 'NA' to refer to the existing minimum or

maximum

• A function that accepts the existing (automatic) limits

and returns new limits Note that setting limits on

positional scales will *remove* data outside of the

limits. If the purpose is to zoom, use the limit argument

in the coordinate system (see 'coord_cartesian()').

so we'll use `c(0, NA)`

.

For Q2, we'll add `expand=`

, documented in the same place.

`data %>%`

gather(Gene, Levels, -Patient, -Treatment) %>%

mutate(Treatment = factor(Treatment, levels = c("Pre", "Post"))) %>%

mutate(Patient = as.factor(Patient)) %>%

ggplot(aes(x = Treatment, y = Levels, color = Patient, group = Patient)) +

geom_point() +

geom_line() +

facet_wrap(. ~ Gene, scales = "free") +

theme_bw() +

theme(panel.grid = element_blank()) +

scale_y_continuous(limits = c(0, NA), expand = expansion(mult = c(0, 0.1)))

## R ggplot cannot set log axis limits

I think your problem is that log(0) is undefined (or -Inf for R), so you can't set the x limit to 0 on a log transformed axis without getting an error.

My usual workaround is to set the axis limit to 1 (because log(1) = 0), as below.

`ggplot(s1_to_5_adj, aes(x = PfMSP119_adj))+`

geom_histogram(bins = 1500) +

ylim(c(0,150)) +

scale_x_log10(limit = c(1,25000)) +

xlab("MFI value") +

ylab("Frequency") +

labs(title = "Age 1-5") +

theme(plot.title = element_text(hjust = 0.5)) +

theme(panel.grid.minor=element_blank(),

panel.grid.major=element_blank())

## Limit the X and Y axes of ggplot2 plot

Add limits and expand arguments in scale_x_continuous and scale_y_continuous. You can add breaks as well.

`ggplot(as.data.table(mtcars)) + `

geom_line(aes(x = wt, y = mpg, color= factor(cyl))) +

ylab('Fuel Economy (mpg)') +

scale_y_continuous(limits = c(10, 35), expand = c(0, 0),

sec.axis = sec_axis(~.*1.6/3.7854, name = 'Fuel Economy (kmpl)')

) +

xlab('Weight (lbs)') +

scale_x_continuous(limits = c(0, 5), expand = c(0, 0),

sec.axis = sec_axis(~./2.20462, name = 'Weight (kg)'), position = 'bottom') +

theme_light() +

theme(

legend.position = c(0.15, 0.75),

legend.title = element_blank(),

axis.title.y.right = element_text(

angle = 90,

margin = margin(r = 0.8 * 11,

l = 0.8 * 11 / 2)

)

)

## Conditionally set the xlim or axis limits when making plots in a loop in ggplot2

This could be achieved by setting the limits conditionally via an `if`

-statement. Personally I prefer to use lists and `lapply`

or `purrr::map`

or `purrr::walk`

to make plots in a loop instead of using `for`

but the approach could also be used with a `for`

-loop:

Using `mtcars`

as example dataset:

`library(ggplot2)`

mtcars_split <- split(mtcars, mtcars$cyl)

plot_function <- function(df, i) {

xlim <- if (max(df$mpg) < 20) {

xlim(0, 20)

} else if (max(df$mpg) < 30) {

xlim(0, 30)

} else {

xlim(0, 40)

}

ggplot(df, aes(x=mpg ,y=hp))+

geom_point(aes(colour=am)) +

xlim +

ggtitle("Point", i)

ggsave(filename = paste("plot_cyl_", i,".png"), width = 20, height = 20, units = "cm")

}

Loop over the splitted dataframe using `purrr::iwalk`

`purrr::iwalk(mtcars_split, plot_function)`

or using a `for`

loop:

`for (i in seq_along(mtcars_split)) {`

plot_function(mtcars_split[[i]], names(mtcars_split)[[i]])

}

## How to set just one limit for axes in ggplot2 with facets?

Set limits one-sided with NA. Works both in `coord_`

and `scale_`

functions

I generally prefer coord_ because it does not remove data. For the example below you would additionally need to remove the margin at 0, e.g. with expand.

`library(ggplot2) `

carrots <- data.frame(length = rnorm(500000, 10000, 10000))

cukes <- data.frame(length = rnorm(50000, 10000, 20000))

carrots$veg <- 'carrot'

cukes$veg <- 'cuke'

vegLengths <- rbind(carrots, cukes)

ggplot(vegLengths, aes(length, fill = veg)) +

geom_density(alpha = 0.2) +

scale_x_continuous(limits = c(0, NA))

#> Warning: Removed 94542 rows containing non-finite values (stat_density).

ggplot(vegLengths, aes(length, fill = veg)) +

geom_density(alpha = 0.2) +

coord_cartesian(xlim = c(0, NA))

^{Created on 2020-04-30 by the reprex package (v0.3.0)}

remove the margin with expand. Also one sided possible. the right margin is set to the default mult expansion of 0.05 for continous axis.

`ggplot(vegLengths, aes(length, fill = veg)) +`

geom_density(alpha = 0.2) +

scale_x_continuous(expand = expansion(mult = c(0, 0.05))) +

coord_cartesian(xlim = c(0, NA))

## Manually setting limits and ticks on x-axis after coord_flip() in ggplot2

You want to define a continuous variable's axis, so you should use the `scale_y_continuous()`

function for your plot, and define the breaks you want.

Here's a dummy example :

`library(ggplot2)`

data(iris)

p <- ggplot(data = iris[c(1:3, 52:55, 102:105),], mapping = aes(x = reorder(Species,-Petal.Width), y = Petal.Width))

p + geom_pointrange(mapping = aes(ymin = 0, ymax = 3)) +

labs(x= "", y= "yvar_label") + coord_flip() +

geom_hline(yintercept = 5, linetype="dotted", color = "red", size=1.5) +

scale_y_continuous(breaks = seq(from = 0, to = 3, by = 0.5), limits = c(0,3)) +

theme_bw()

Edit: For plot limits, you should give the `limits`

arguments to the `scale_x/y_continuous()`

function.

## Can't set limits for a graph with two y scales

You can't set limits for the secondary axis via the `limits`

argument.

If you want a different scale or limits for the secondary axis you have to scale your data accordingly. My code below makes use of `scales::rescale`

to do the (re-)scaling of your AUC data:

`library(ggplot2)`

from <- c(0.8, 1)

to <- range(plot_df_AIC$AIC)

plot_df_AUC$AUC <- scales::rescale(plot_df_AUC$AUC, from = from, to = to)

ggplot()+

geom_line(data=plot_df_AIC, aes(x=x, y=AIC), color="red") +

geom_line(data=plot_df_AUC, aes(x=x, y=AUC), color="blue")+

scale_y_continuous(sec.axis = sec_axis(

~ scales::rescale(.x, to = from, from = to), name = "AUC"))+

theme(

axis.title.y = element_text(color = "red"),

axis.text.y = element_text(color = "red"),

axis.title.y.right = element_text(color = "blue"),

axis.text.y.right = element_text(color = "blue")

)

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