Ignore outliers in ggplot2 boxplot

Question

How would I ignore outliers in ggplot2 boxplot   I don t simply want them to disappear  i e  outlier size 0   but I want them to be ignored such that the y axis scales to show 1st 3rd percentile   My outliers are causing the  box  to shrink so small its practically a line   Are there some techniques to deal with this   Edit Here s an example   y   c  01   02   03   04   05   06   07   08   09   5  - 6  qplot 1  y  geom  boxplot

User · Answer

The  coef  option of the geom boxplot function allows to change the outlier cutoff in terms of interquartile ranges  This option is documented for the function stat boxplot  To deactivate outliers  in other words they are treated as regular data   one can instead of using the default value of 1 5 specify a very high cutoff value   library ggplot2    generate data with outliers  df   data frame x 1  y   c -10  rnorm 100   10      generate plot with increased cutoff for outliers  ggplot df  aes x  y     geom boxplot coef 1e30

User · Answer

One idea would be to winsorize the data in a two-pass procedure    run a first pass  learn what the bounds are  e g  cut of at given percentile  or N standard deviation above the mean  or     in a second pass  set the values beyond the given bound to the value of that bound   I should stress that this is an old-fashioned method which ought to be dominated by more modern robust techniques but you still come across it a lot

User · Answer

If you want to force the whiskers to extend to the max and min values  you can tweak the coef argument  Default value for coef is 1 5  i e  default length of the whiskers is 1 5 times the IQR      Load package and create a dummy data frame with outliers    using example from Ramnath s answer above  library ggplot2  df   data frame y   c -100  rnorm 100   100      create boxplot that includes outliers p0   ggplot df  aes y   y     geom boxplot aes x   factor 1       create boxplot where whiskers extend to max and min values p1   ggplot df  aes y   y     geom boxplot aes x   factor 1    coef   500

User · Answer

Ipaper  geom boxplot2 is just what you want     devtools  install github  kongdd Ipaper   library Ipaper  library ggplot2  p  lt - ggplot mpg  aes class  hwy   p   geom boxplot2 width   0 8  width errorbar   0 5

User · Answer

Use geom boxplot outlier shape   NA  to not display the outliers and scale y continuous limits   c lower  upper   to change the axis limits   An example   n  lt - 1e4L dfr  lt - data frame    y   exp rlnorm n      really right-skewed variable   f   gl 2  n   2     p  lt - ggplot dfr  aes f  y        geom boxplot   p     big outlier causes quartiles to look too slim  p2  lt - ggplot dfr  aes f  y        geom boxplot outlier shape   NA      scale y continuous limits   quantile dfr y  c 0 1  0 9    p2    no outliers plotted  range shifted   Actually  as Ramnath showed in his answer  and Andrie too in the comments   it makes more sense to crop the scales after you calculate the statistic  via coord cartesian   coord cartesian ylim   quantile dfr y  c 0 1  0 9       You ll probably still need to use scale y continuous to fix the axis breaks

User · Answer

Here is a solution using boxplot stats    create a dummy data frame with outliers df   data frame y   c -100  rnorm 100   100      create boxplot that includes outliers p0   ggplot df  aes y   y     geom boxplot aes x   factor 1        compute lower and upper whiskers ylim1   boxplot stats df y  stats c 1  5      scale y limits based on ylim1 p1   p0   coord cartesian ylim   ylim1 1 05

User · Answer

I had the same problem and precomputed the values for Q1  Q2  median  ymin  ymax using boxplot stats     Load package and generate data library ggplot2  data  lt - rnorm 100     Compute boxplot statistics stats  lt - boxplot stats data  stats df  lt - data frame x  label1   ymin stats 1   lower stats 2   middle stats 3                     upper stats 4   ymax stats 5      Create plot p  lt - ggplot df  aes x x  lower lower  upper upper  middle middle  ymin ymin                       ymax ymax          geom boxplot stat  identity   p   The result is a boxplot without outliers

[r] Ignore outliers in ggplot2 boxplot

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