How do you create a grouped boxplot with categorical variables on the x-axis.

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Included is a picture of what I'm trying to do. I downloaded some new functions off of MatLab downloads but they seem to be for numerical variables on both the x and y-axis. I'm looking to group categorical variables on the x-axis of the boxplot. Is there anything I can download or any existing code that does this? Thanks in advance!

回答(2 个)

Adam Danz
Adam Danz 2020-3-6
编辑:Adam Danz 2020-3-6
If your boxplot data are matrices with the same number of columns, you can use boxplotGroup() from the file exchange to group the boxplots together with space between the groups.
For example,
data = {rand(100,2), rand(100,2)+.2, rand(100,2)-.2};
boxplotGroup(data, 'PrimaryLabels', {'a' 'b' 'c'}, ...
'SecondaryLabels',{'Group1', 'Group2'}, 'GroupLabelType', 'Vertical')
Example 2
data = {rand(100,2), rand(100,2)+.2, rand(100,2)-.2};
boxplotGroup(data, 'PrimaryLabels', {'a' 'b' 'c'}, ...
'SecondaryLabels',{'Group1', 'Group2'}, 'InterGroupSpace', 2)
Also see Kelly Kearney's boxplot2() function.
  4 个评论
Adam Danz
Adam Danz 2020-11-8
This is from the documentation (current vs.1.2.2).
boxplotGroup(x) receives a 1xm cell array where each element is a matrix with n columns and produced n groups of boxplot boxes with m boxes per group.
So for this input below, there will be 4 groups of 3 boxplots within each group because there are 3 elements of the cell array and each element has 4 columns. That's how you should think about organizing your data.
data = {rand(100,4), rand(20,4)*.8, rand(1000,4)*1.2}
data = 1x3 cell array
{100×4 double} {20×4 double} {1000×4 double}
boxplotGroup(data)
It sounds like what you want is,
g{1} = data(1:100, 1:4:end); % or 1:4:9
g{2} = data(1:100, 2:4:end); % or 2:4:10
g{3} = data(1:100, 3:4:end); % etc.....
g{4} = data(1:100, 4:4:end);
mhd z
mhd z 2020-11-10
Thank you Adam
I ran the code line by line and figured it out. I was a little comlex :)
its realy a good code. thank you

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Iddo Weiner
Iddo Weiner 2017-3-22
Take a look at this, it explains how to do precisely what you want: Link

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