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In a boxplot, how to show that outliers exist, but not actually plot them?

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In our datasets, we have a few absolutely huge outliers. If we plot (eg in a boxplot) and include the outliers, the axis will be so squeezed that it's useless. Log-scaling doesn't help. But we want to tell the reader that the outliers exist (and say how many, and on which side of the boxplot, positive or negative), preferably without adding text manually to the caption. Is there a good method for this? Preferably in R, Matplotlib or Seaborn.

This is different from eg Ignore outliers in ggplot2 boxplot because I don't want to ignore the outliers: I want to show that they exist, but not plot them.

Sample code:

# from https://stackoverflow.com/questions/5677885/ignore-outliers-in-ggplot2-boxplot
> library("ggplot")
> df = data.frame(y = c(-100, rnorm(100), 100))
> ggplot(df, aes(y = y)) + geom_boxplot(aes(x = factor(1)))

We see a boxplot that is useless because of the presence of outliers. If we follow the accepted answer at that link, we remove the outliers in a very nice way, but now the reader doesn't realise there were any outliers.

r matplotlib seaborn outliers

share|improve this question

edited Mar 28 at 16:59

jmmcd

asked Mar 28 at 10:47

jmmcdjmmcd

43633 silver badges1414 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Could you post some sample data and a bit of basic code to visualise the problem?
  
  – Thomas Kühn
  Mar 28 at 10:54
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Possible duplicate of Ignore outliers in ggplot2 boxplot
  
  – Wimpel
  Mar 28 at 10:54
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ThomasKühn, added code.
  
  – jmmcd
  Mar 28 at 22:12
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @Wimpel, not a duplicate as described in edit.
  
  – jmmcd
  Mar 28 at 22:12
  

  
  
  
  

add a comment
 | 

0

In our datasets, we have a few absolutely huge outliers. If we plot (eg in a boxplot) and include the outliers, the axis will be so squeezed that it's useless. Log-scaling doesn't help. But we want to tell the reader that the outliers exist (and say how many, and on which side of the boxplot, positive or negative), preferably without adding text manually to the caption. Is there a good method for this? Preferably in R, Matplotlib or Seaborn.

This is different from eg Ignore outliers in ggplot2 boxplot because I don't want to ignore the outliers: I want to show that they exist, but not plot them.

Sample code:

# from https://stackoverflow.com/questions/5677885/ignore-outliers-in-ggplot2-boxplot
> library("ggplot")
> df = data.frame(y = c(-100, rnorm(100), 100))
> ggplot(df, aes(y = y)) + geom_boxplot(aes(x = factor(1)))

We see a boxplot that is useless because of the presence of outliers. If we follow the accepted answer at that link, we remove the outliers in a very nice way, but now the reader doesn't realise there were any outliers.

r matplotlib seaborn outliers

share|improve this question

edited Mar 28 at 16:59

jmmcd

asked Mar 28 at 10:47

jmmcdjmmcd

43633 silver badges1414 bronze badges

• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Could you post some sample data and a bit of basic code to visualise the problem?
  
  – Thomas Kühn
  Mar 28 at 10:54
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  Possible duplicate of Ignore outliers in ggplot2 boxplot
  
  – Wimpel
  Mar 28 at 10:54
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @ThomasKühn, added code.
  
  – jmmcd
  Mar 28 at 22:12
  

  
  
  
  


• 
  
  
  

  
  

  
  
  
  
  
  

  
  
  @Wimpel, not a duplicate as described in edit.
  
  – jmmcd
  Mar 28 at 22:12
  

  
  
  
  

add a comment
 | 

In our datasets, we have a few absolutely huge outliers. If we plot (eg in a boxplot) and include the outliers, the axis will be so squeezed that it's useless. Log-scaling doesn't help. But we want to tell the reader that the outliers exist (and say how many, and on which side of the boxplot, positive or negative), preferably without adding text manually to the caption. Is there a good method for this? Preferably in R, Matplotlib or Seaborn.

This is different from eg Ignore outliers in ggplot2 boxplot because I don't want to ignore the outliers: I want to show that they exist, but not plot them.

Sample code:

# from https://stackoverflow.com/questions/5677885/ignore-outliers-in-ggplot2-boxplot
> library("ggplot")
> df = data.frame(y = c(-100, rnorm(100), 100))
> ggplot(df, aes(y = y)) + geom_boxplot(aes(x = factor(1)))

We see a boxplot that is useless because of the presence of outliers. If we follow the accepted answer at that link, we remove the outliers in a very nice way, but now the reader doesn't realise there were any outliers.

r matplotlib seaborn outliers

share|improve this question

edited Mar 28 at 16:59

jmmcd

asked Mar 28 at 10:47

jmmcdjmmcd

43633 silver badges1414 bronze badges

# from https://stackoverflow.com/questions/5677885/ignore-outliers-in-ggplot2-boxplot
> library("ggplot")
> df = data.frame(y = c(-100, rnorm(100), 100))
> ggplot(df, aes(y = y)) + geom_boxplot(aes(x = factor(1)))

share|improve this question

edited Mar 28 at 16:59

jmmcd

asked Mar 28 at 10:47

jmmcdjmmcd

43633 silver badges1414 bronze badges

share|improve this question

edited Mar 28 at 16:59

jmmcd

asked Mar 28 at 10:47

jmmcdjmmcd

43633 silver badges1414 bronze badges

asked Mar 28 at 10:47

jmmcdjmmcd

43633 silver badges1414 bronze badges

asked Mar 28 at 10:47

jmmcdjmmcd

43633 silver badges1414 bronze badges