One of most common things one might do while making plots is to change tiny details of the plot to make them better. Often, one of such adjustments are changing x-axis tick mark label/text on a plot made with ggplot2 in R.
Let us use ggplot2 to make plot first and then fix its x-axis tick mark labels.
library(ggplot2) library(tibble)
We will create a toy data frame using tibble with two column variables.
n <- 4
# create a tibble
df <- tibble(gender = c(rep("0",n), rep("1",n)),
weight = c(rnorm(n,100,sd=5), rnorm(n,150,sd=5)))
A glimpse at the data frame shows that first column is a characeter variable and second is numeric.
>head(df) gender weight <chr> . <dbl> 0 106.85479 0 97.17651 0 101.81564 0 103.16431 1 152.02134 1 149.46938
Let us make a boxplot with ggplot2 using the above dataframe.
# make boxplot with ggplot2 df %>% ggplot(aes(x=gender,y=weight))+ geom_boxplot(width=0.25)
Note that in the boxplot we made right now, the x-axis variable gender has two levels, coded as 0 and 1. ggplot automatically found these levels and marked the X-axis tick mark labels as 0 and 1. You might know that the codes 0 & 1 correspond to Female and Male. And the plot is much easier read with Female and Male on the x-axis tick mark instead of 0 and 1.
To change the x-axis tick mark label, from 0 & 1 to Female and Male here, we can add a layer scale_x_discrete() and specify the breaks currently used and specify the labels that we actually want, as shown below.
df %>%
ggplot(aes(x=gender,y=weight)) +
geom_boxplot(width=0.25) +
scale_x_discrete(breaks=c("0", "1"),
labels=c("Female", "Male"))
Voila, now the x-axis tick label text is Female and Male as we wanted.
If you want to change y-axis tick mark labels, you can use scale_y_discrete().
