How to change the parameters of points (color, shape, etc.) corresponding to outliers in geom_jitter
?
There is a data
> dput(head(df, 20))
structure(list(variable = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L), .Label = c("W1",
"W3", "W4", "W5", "W12", "W13", "W14"), class = "factor"), value = c(68,
62, 174, 63, 72, 190, 73, 68, 62, 88, 81, 80, 79, 51, 73, 61,
NA, NA, 84, 87)), row.names = c(NA, 20L), class = "data.frame")
and a code
plot <-
ggplot(df, aes(factor(df$variable), df$value)) +
geom_jitter(position = position_jitter(width = .1, height = 0), size = 0.7) +
theme(legend.position = 'none') +
theme_classic() +
labs(x = '',
y = '',
title = "test")
And I get such plot.
For same data earlier has been created boxplot with default coef = 1.5
, so I know than there are outliers in this dataset. Now I just want to create dotplot and to color outliers points in red. With geom_boxplot
, this is done with the single function argument outlier.color
, but there are no such arguments for geom_jitter
.
You can define first your outliers using dplyr
:
library(dplyr)
new_df <- df %>% group_by(variable) %>% filter(!is.na(value)) %>%
mutate(Outlier = ifelse(value > quantile(value, 0.75)+1.50*IQR(value),"Outlier","OK")) %>%
mutate(Outlier = ifelse(value < quantile(value, 0.25)-1.50*IQR(value),"Outlier",Outlier))
head(new_df)
# A tibble: 6 x 3
# Groups: variable [1]
variable value Outlier
<fct> <dbl> <chr>
1 W1 68 OK
2 W1 62 OK
3 W1 174 Outlier
4 W1 63 OK
5 W1 72 OK
6 W1 190 Outlier
and then using this new column, you can lot subset of the dataset depending of the condition Outlier
:
library(ggplot2)
ggplot(subset(new_df, Outlier == "OK"), aes(x = variable, y = value))+
geom_jitter(width = 0.1, size = 0.7)+
geom_jitter(inherit.aes = FALSE, data = subset(new_df, Outlier == "Outlier"),
aes(x = variable, y = value), width = 0.1, size = 3, color = "red")+
theme(legend.position = 'none') +
theme_classic() +
labs(x = '',
y = '',
title = "test")
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