Boxplot Data
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I have a very large set of data with many groups and subgroups. The boxplot command works well for visualization of the data. I was wondering if there was an easy way to extract the data displayed without actually doing a manual calculation of each parameter. For example, I wish boxplot provided a set of function output variables that report the values used to plot each box (mean, interquartile range, outliers, etc.)
Does anyone know of an easy way to extract this information automatically?
I know that I can manually write a script to calculate each of the values...just wondering if there is a shortcut.
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Maria Battle
2020년 12월 9일
편집: Maria Battle
2020년 12월 9일
Similar to Oleg's answer, you could use the functions iqr and mean to address your first concerns. Note: interquartile uses median, not mean. For interquartile outlier output, use the 'quartiles' method for isoutlier. To get the same results between boxplot and isoutlier, make sure the whisker value in boxplot is the same value as the threshold factor in isoutlier.
load examgrades
t = datetime('2015-12-18 12:00:00') + days(1:120)';
g = grades(:,1);
figure
boxplot(g, 'Whisker', .5);
io = isoutlier(g,'quartiles','ThresholdFactor', .5);
outg = g(io);
outt = t(io);
t = table(outt, outg);
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Maria Battle
2021년 12월 8일
In that case, you might try using Matlab's quantile function and create a condition for your threshold. I believe that's basically what isoutlier() is doing when you use the quartiles and ThresholdFactor options. I haven't tried it though.
추가 답변 (2개)
Oleg Komarov
2011년 6월 23일
It way easier to calculate the stats:
min
max
quantile(x,[.25 .5 .75])
mean
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Rania Rayyes
2020년 1월 8일
편집: Rania Rayyes
2020년 1월 8일
median and not mean, and the upper bound is not max, max is outlier here
Aymen ABID
2021년 3월 19일
편집: Aymen ABID
2021년 3월 19일
@Rania Rayyes quabtile .25 .5 .75 gives Q1,Q2 (median),Q3
median with isnan give the median
zahra zol
2017년 4월 15일
i am desperately looking for the same thing...
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Samuel Geurts
2017년 9월 14일
편집: Samuel Geurts
2017년 9월 14일
if you open de handle of the boxplot you can achieve that information, but that is not easier than calculating it.
h = boxplot(x)
handle(h)
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