How to Add a Condition to the Geom_Point Size

How to add a condition to the geom_point size?

scale_size_manual sets the sizes for a discrete variable.

geom_point(aes(size =n_in_stat>4)) + scale_size_manual(values=c(2,5))

ggplot, conditional fill geom_point

an alternative approach can be the usage of to specific shapes and assign them manually. A nice side effect is a more descriptive legend:

mydata <- tibble(x_var = 1:5, 
                 y_var = runif(5), 
                 category_a = c('yes', 'yes', 'no', 'no', 'yes'),
                 category_b = c('down', 'up', 'up', 'down', 'down'))

# choose circle and dot shapes
shps <- c(1, 16)

ggplot(mydata, aes(x = x_var, y =  y_var, color = category_a, shape= category_b)) +
    geom_point(size = 5, stroke = 2) + 
    # add manually choosen shapes and colors
    scale_shape_manual(values=shapes)

Setting absolute point size for geom_point with scale_size_area

You can play around with the range and limits arguments within scale_size to get something closer to what you're looking for:

ggplot(data.frame(area = seq(from = 0, to = 1, length.out = 17), y = 1), aes(x = area, y = y)) + 
  geom_point(aes(size = area), color = "red") +  # Area point
  geom_point() +  # Default point
  scale_size("size_area", range = c(-20, 10))

EDIT:

Since that's a little hacky and not scalable, the better way to do this is to first figure out what the default point size is:

default_size <- ggplot2:::check_subclass("point", "Geom")$default_aes$size
default_size
[1] 1.5

It should be 1.5, unless you've manually changed the defaults. Now we can rebuild the plot and figure out how the size aesthetic is currently being mapped to area:

df <- data.frame(area = seq(from = 0, to = 1, length.out = 17), y = 1)

g <- ggplot(df, aes(x = area, y = y)) + 
  geom_point(aes(size = area), color = "red") +  # Area point
  geom_point() +
  scale_size_area()

g2 <- ggplot_build(g)

g2$data[[1]] %>%
  select(x, size)

x     size
1  0.0000 0.000000
2  0.0625 1.500000
3  0.1250 2.121320
4  0.1875 2.598076
5  0.2500 3.000000
6  0.3125 3.354102
7  0.3750 3.674235
8  0.4375 3.968627
9  0.5000 4.242641
10 0.5625 4.500000
11 0.6250 4.743416
12 0.6875 4.974937
13 0.7500 5.196152
14 0.8125 5.408327
15 0.8750 5.612486
16 0.9375 5.809475
17 1.0000 6.000000

The relationship is size = 6*sqrt(x). Why 6? Because the scale_size_area has a default max_size of 6. So, to make it so the x-value of 0.5 maps to 1.5 size, we have to solve the above equation for a new max_size, and we get 1.5/sqrt(0.5).

To automate this, we can do the following:

default_size_val <- 0.5
max_size <- default_size/(sqrt(default_size_val))

ggplot(df, aes(x = area, y = y)) + 
  geom_point(aes(size = area), color = "red") +  # Area point
  geom_point() +
  scale_size_area(max_size = max_size)

Adjust point size to individual variables using geom_point in R

Decided to make my comment an answer. You need to group by variable before scaling.

library(tidyverse)
data <- tibble::tibble(
  value = c(4.07,   5.76,   2.87,4.94,  5.48,   6.75,1.53,  1.35,   1.32), 
  Variable = rep(c(rep("A",3),rep("B",3), rep("C",3))),
  Experiment = rep(c(1:3),3))

data <- data %>%group_by(Variable)%>%
  mutate(scaled_val = scale(value)) %>%

  ungroup()

data$Variable <- factor(data$Variable,levels=rev(unique(data$Variable)))

ggplot(data, aes(x = Experiment, y = Variable, label=NA)) +
  geom_point(aes(size = scaled_val, colour = value)) + 
  geom_text(hjust = 1, size = 2) +
  # scale_size(range = c(1,3)) +
  theme_bw()+
  scale_color_gradient(low = "lightblue", high = "darkblue")
#> Warning: Removed 9 rows containing missing values (geom_text).

^{Created on 2020-04-22 by the reprex package (v0.3.0)}

Fill geom_point() based on two conditions: either on column value, or if value is 0

Build a new variable after value. This new variable will take two values (0,1). Use that as an aes() for color.

Here an example:

library(ggplot2)
library(dplyr)

First create new_var according to your needs:

# new_var is 0 if wt>5, otherwise is 1
mtcars <- mtcars %>% 
  mutate(new_var = ifelse(wt>5, 0, 1))
 #mutate(new_var = ifelse(value==0, 0, 1)) # in your case do this instead

Plot using new_var as a new aesthetics:

ggplot(mtcars, aes(x=mpg, y=wt)) +
  geom_point(aes(size=wt, color = as.factor(new_var))) + # add as.factor() to color accordingly
  scale_color_manual(values=c("gray", "black")) # custom coloring the points
  #+ guides(color=FALSE) # this removes the color legend

Of course you can remove later the second legend and do other improvements.

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Another example, with a different shape:

ggplot(mtcars, aes(x=mpg, y=wt)) +
  geom_point(aes(size=wt, color = as.factor(new_var)), shape=21, fill="black") +
  scale_color_manual(values=c("red", "black")) +
  guides(color=FALSE)

if else condition in ggplot to add an extra layer

What you are seeing is a syntax error. The most robust way I can think of is:

tmp.data<-c(1,2,3) 
if(tmp.data[1]!="no value") {
   p = p + geom_point()
}
p + geom_line()

So you compose the object p in a sequence, only adding geom_point() when the if statements yields TRUE.

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