CODEWITHSUNDEEP
rplotggplot2
iago
iago

Reputation: 3256

How to set aside certain numeric values of x with ggplot?

I have a continuous scale including some values which codify different categories of missing (for example 998,999), and I want to make a plot excluding these numeric missing values.

Since the values are together, I can use xlim each time, but since it determines the domain of the plot I have to change the values for each different case.

Then, I ask for a solution. I think in two possibilities.

Thanks in advance.

Upvotes: 0

Views: 846

Answers (2)

GGamba
GGamba

Reputation: 13680

I would filter those missing values from the original dataset:

library(dplyr)

df <- data.frame(cat = rep(LETTERS[1:4], 3),
                 values = sample(10, 12, replace = TRUE)
)
# Add missing values
df$values[c(1,5,10)] <- 999
df$values[c(2,7)] <- 998

invalid_values <- c(998, 999)

library(ggplot2)

df %>% 
  filter(!values %in% invalid_values) %>% 
  ggplot() +
  geom_point(aes(cat, values))

Alternatively, if that's not possible for some reason, you can define a scale transformation:

df %>% 
  ggplot() +
  geom_point(aes(cat, values)) +
  scale_y_continuous(trans = scales::trans_new('remove_invalid',
                                               transform = function(d) {d <- if_else(d %in% invalid_values, NA_real_, d)},
                                               inverse = function(d) {if_else(is.na(d), 999, d)}
                                               )
                     )
#> Warning: Transformation introduced infinite values in continuous y-axis
#> Warning: Removed 5 rows containing missing values (geom_point).

Created on 2018-05-09 by the reprex package (v0.2.0).

Upvotes: 1

Lorenzo G
Lorenzo G

Reputation: 621

I think the simplest way is to exclude these values in the plot, either before or during the ggplot call.

MWE

library(tidyverse)

# Create data with overflowing data
mtcars2 <- mtcars
mtcars2[5:15, 'mpg'] <- 998

# Full plot
mtcars2 %>% ggplot() +
   geom_point(aes(x = mpg, y = disp))

Filtering before plot

mtcars2 %>% 
   filter(mpg < 250) %>% 
   ggplot() +
   geom_point(aes(x = mpg, y = disp))

Filtering during plot

mtcars2 %>% 
   ggplot() +
   geom_point(aes(x = mpg, y = disp), data = . %>% filter(mpg < 250))

Upvotes: 2

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