On 21-Aug-2012 17:52, Jeffrey Blackburne wrote:
>
> On Aug 21, 2012, at 10:58 AM, Virgil Stokes wrote:
>
>> In reference to my previous email.
>>
>> How can I find the outliers (samples points beyond the whiskers) in the data
>> used for the boxplot?
>>
>> Here is a code snippet that shows how it was used for the timings data (a
>> list
>> of 4 sublists (y1,y2,y3,y4), each containing 400,000 real data values),
>> ...
>> ...
>> ...
>> # Box Plots
>> plt.subplot(2,1,2)
>> timings = [y1,y2,y3,y4]
>> pos = np.array(range(len(timings)))+1
>> bp = plt.boxplot( timings, sym='k+', patch_artist=True,
>> positions=pos, notch=1, bootstrap=5000 )
>>
>> plt.xlabel('Algorithm')
>> plt.ylabel('Exection time (sec)')
>> plt.ylim(0.9*ymin,1.1*ymax)
>>
>> plt.setp(bp['whiskers'], color='k', linestyle='-' )
>> plt.setp(bp['fliers'], markersize=3.0)
>> plt.title('Box plots (%4d trials)' %(n))
>> plt.show()
>> ...
>> ...
>> ...
>>
>> Again my questions:
>> 1) How to get the value of the median?
>
> This is easily calculated from your data. Numpy will even do it for you:
> np.median(timings)
>
>> 2) How to find the outliers (outside the whiskers)?
>
> From the boxplot documentation: the whiskers extend to the most extreme data
> point within distance X of the bottom or top of the box, where X is 1.5 times
> the extent of the box. Any points more extreme than that are the outliers.
> The
> box itself of course extends from the 25th percentile to the 75th percentile
> of your data. Again, you can easily calculate these values from your data.
>
>> 3) How to find the width of the notch?
>
> Again, from the docs: with bootstrap=5000, it calculates the width of the
> notch by bootstrap resampling your data (the timings array) 5000 times and
> finding the 95% confidence interval of the median, and uses that as the notch
> width. You can redo that yourself pretty easily. Here is some bootstrap code
> for you to adapt:
> http://mail.scipy.org/pipermail/scipy-user/2009-July/021704.html
>
> I encourage you to read the documentation! This page is very useful for
> reference:
> http://matplotlib.sourceforge.net/api/pyplot_api.html
>
> -Jeff
>
Yes Jeff,
These are very useful links; however, box plots have a parameter called the
"adjacent value" (from the McGill reference),
"The plotted whisker extends to the adjacent value, which is the most extreme
data value that is not an outlier."
It seems there should be one for the lower and one for the upper whisker ---
how
can one get these two values from boxplot?
Also, is there anyway to directly get the indices of the outliers?
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