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?
2) How to find the outliers (outside the whiskers)?
3) How to find the width of the notch?
------------------------------------------------------------------------------
Live Security Virtual Conference
Exclusive live event will cover all the ways today's security and
threat landscape has changed and how IT managers can respond. Discussions
will include endpoint security, mobile security and the latest in malware
threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
