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how to specify colours in scatterplot quadrants?

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0

I'm looking to create a scatterplot within R that has points that are split into four quadrants and then applies a color to each quadrant based on group.

I have used the following code which works, but need to change the colours.

x_mid <- mean(c(max(iris$Petal.Length, na.rm = TRUE), 
 min(iris$Petal.Length, na.rm = TRUE)))

y_mid <- mean(c(max(iris$Petal.Width, na.rm = TRUE), 
 min(iris$Petal.Width, na.rm = TRUE)))
library(dplyr)
library(ggplot2)

iris %>% 
 mutate(quadrant = case_when(Petal.Length > x_mid & Petal.Width > y_mid ~ "Q1",
 Petal.Length <= x_mid & Petal.Width > y_mid ~ "Q2",
 Petal.Length <= x_mid & Petal.Width <= y_mid ~ "Q3",
 TRUE ~ "Q4")) %>% 
 ggplot(aes(x = Petal.Length, y = Petal.Width, color = quadrant)) +
 geom_vline(xintercept = x_mid) + # plot vertical line
 geom_hline(yintercept = y_mid) + # plot horizontal line
 geom_point()

r ggplot2 scatter-plot

share|improve this question

asked Mar 28 at 2:50

Michelle WardMichelle Ward

1155 bronze badges

add a comment | 

0

I'm looking to create a scatterplot within R that has points that are split into four quadrants and then applies a color to each quadrant based on group.

I have used the following code which works, but need to change the colours.

x_mid <- mean(c(max(iris$Petal.Length, na.rm = TRUE), 
 min(iris$Petal.Length, na.rm = TRUE)))

y_mid <- mean(c(max(iris$Petal.Width, na.rm = TRUE), 
 min(iris$Petal.Width, na.rm = TRUE)))
library(dplyr)
library(ggplot2)

iris %>% 
 mutate(quadrant = case_when(Petal.Length > x_mid & Petal.Width > y_mid ~ "Q1",
 Petal.Length <= x_mid & Petal.Width > y_mid ~ "Q2",
 Petal.Length <= x_mid & Petal.Width <= y_mid ~ "Q3",
 TRUE ~ "Q4")) %>% 
 ggplot(aes(x = Petal.Length, y = Petal.Width, color = quadrant)) +
 geom_vline(xintercept = x_mid) + # plot vertical line
 geom_hline(yintercept = y_mid) + # plot horizontal line
 geom_point()

r ggplot2 scatter-plot

share|improve this question

asked Mar 28 at 2:50

Michelle WardMichelle Ward

1155 bronze badges

add a comment | 

I'm looking to create a scatterplot within R that has points that are split into four quadrants and then applies a color to each quadrant based on group.

I have used the following code which works, but need to change the colours.

x_mid <- mean(c(max(iris$Petal.Length, na.rm = TRUE), 
 min(iris$Petal.Length, na.rm = TRUE)))

y_mid <- mean(c(max(iris$Petal.Width, na.rm = TRUE), 
 min(iris$Petal.Width, na.rm = TRUE)))
library(dplyr)
library(ggplot2)

iris %>% 
 mutate(quadrant = case_when(Petal.Length > x_mid & Petal.Width > y_mid ~ "Q1",
 Petal.Length <= x_mid & Petal.Width > y_mid ~ "Q2",
 Petal.Length <= x_mid & Petal.Width <= y_mid ~ "Q3",
 TRUE ~ "Q4")) %>% 
 ggplot(aes(x = Petal.Length, y = Petal.Width, color = quadrant)) +
 geom_vline(xintercept = x_mid) + # plot vertical line
 geom_hline(yintercept = y_mid) + # plot horizontal line
 geom_point()

r ggplot2 scatter-plot

share|improve this question

asked Mar 28 at 2:50

Michelle WardMichelle Ward

1155 bronze badges

x_mid <- mean(c(max(iris$Petal.Length, na.rm = TRUE), 
 min(iris$Petal.Length, na.rm = TRUE)))

y_mid <- mean(c(max(iris$Petal.Width, na.rm = TRUE), 
 min(iris$Petal.Width, na.rm = TRUE)))
library(dplyr)
library(ggplot2)

iris %>% 
 mutate(quadrant = case_when(Petal.Length > x_mid & Petal.Width > y_mid ~ "Q1",
 Petal.Length <= x_mid & Petal.Width > y_mid ~ "Q2",
 Petal.Length <= x_mid & Petal.Width <= y_mid ~ "Q3",
 TRUE ~ "Q4")) %>% 
 ggplot(aes(x = Petal.Length, y = Petal.Width, color = quadrant)) +
 geom_vline(xintercept = x_mid) + # plot vertical line
 geom_hline(yintercept = y_mid) + # plot horizontal line
 geom_point()

share|improve this question

asked Mar 28 at 2:50

Michelle WardMichelle Ward

1155 bronze badges

share|improve this question

asked Mar 28 at 2:50

Michelle WardMichelle Ward

1155 bronze badges

asked Mar 28 at 2:50

Michelle WardMichelle Ward

1155 bronze badges

asked Mar 28 at 2:50

Michelle WardMichelle Ward

1155 bronze badges

1 Answer
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2

If I understood correctly, the only thing that is missing is the manual selection of the colors, in which case the fact that the colors come from quadrants is incidental. Otherwise, I'm afraid I'm missing something.

You can specify the color scale like any other aesthetic. In particular, scale_color_manual lets you give it a vector of strings specifying the colors to use.

So you can add at the end:

scale_color_manual(values = c('orange', 'yellow', 'black', 'grey'))

You you want to map a specific color to each possible level, you can give it a named vector:

 scale_color_manual(values = c(Q4 = 'orange', Q2 = 'yellow', Q1 = 'black', Q3 = 'grey'))

share|improve this answer

answered Mar 28 at 3:09

mgiormentimgiormenti

59722 silver badges1212 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  This is perfect! Thanks
  
  – Michelle Ward
  Mar 28 at 3:23
  

  
  
  
  

add a comment | 

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2

If I understood correctly, the only thing that is missing is the manual selection of the colors, in which case the fact that the colors come from quadrants is incidental. Otherwise, I'm afraid I'm missing something.

You can specify the color scale like any other aesthetic. In particular, scale_color_manual lets you give it a vector of strings specifying the colors to use.

So you can add at the end:

scale_color_manual(values = c('orange', 'yellow', 'black', 'grey'))

You you want to map a specific color to each possible level, you can give it a named vector:

 scale_color_manual(values = c(Q4 = 'orange', Q2 = 'yellow', Q1 = 'black', Q3 = 'grey'))

share|improve this answer

answered Mar 28 at 3:09

mgiormentimgiormenti

59722 silver badges1212 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  This is perfect! Thanks
  
  – Michelle Ward
  Mar 28 at 3:23
  

  
  
  
  

add a comment | 

2

If I understood correctly, the only thing that is missing is the manual selection of the colors, in which case the fact that the colors come from quadrants is incidental. Otherwise, I'm afraid I'm missing something.

You can specify the color scale like any other aesthetic. In particular, scale_color_manual lets you give it a vector of strings specifying the colors to use.

So you can add at the end:

scale_color_manual(values = c('orange', 'yellow', 'black', 'grey'))

You you want to map a specific color to each possible level, you can give it a named vector:

 scale_color_manual(values = c(Q4 = 'orange', Q2 = 'yellow', Q1 = 'black', Q3 = 'grey'))

share|improve this answer

answered Mar 28 at 3:09

mgiormentimgiormenti

59722 silver badges1212 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  This is perfect! Thanks
  
  – Michelle Ward
  Mar 28 at 3:23
  

  
  
  
  

add a comment | 

If I understood correctly, the only thing that is missing is the manual selection of the colors, in which case the fact that the colors come from quadrants is incidental. Otherwise, I'm afraid I'm missing something.

You can specify the color scale like any other aesthetic. In particular, scale_color_manual lets you give it a vector of strings specifying the colors to use.

So you can add at the end:

scale_color_manual(values = c('orange', 'yellow', 'black', 'grey'))

You you want to map a specific color to each possible level, you can give it a named vector:

 scale_color_manual(values = c(Q4 = 'orange', Q2 = 'yellow', Q1 = 'black', Q3 = 'grey'))

share|improve this answer

answered Mar 28 at 3:09

mgiormentimgiormenti

59722 silver badges1212 bronze badges

scale_color_manual(values = c('orange', 'yellow', 'black', 'grey'))

 scale_color_manual(values = c(Q4 = 'orange', Q2 = 'yellow', Q1 = 'black', Q3 = 'grey'))

share|improve this answer

answered Mar 28 at 3:09

mgiormentimgiormenti

59722 silver badges1212 bronze badges

answered Mar 28 at 3:09

mgiormentimgiormenti

59722 silver badges1212 bronze badges

answered Mar 28 at 3:09

mgiormentimgiormenti

59722 silver badges1212 bronze badges