Re: [Matplotlib-users] incorrect boxplot?

[Robert K. <rob...@gm...>]

On 2009-09-14 13:49 PM, Gökhan Sever wrote:
>
>
> On Mon, Sep 14, 2009 at 12:30 PM, <jas...@cr...
> <mailto:jas...@cr...>> wrote:
>
>     I tried the following (most output text is deleted):
>
>     In [1]: ob1=[1,1,2,2,1,2,4,3,2,2,2,3,4,5,6,7,8,9,7,6,4,5,5]
>     In [2]: import matplotlib.pyplot as
>     plt
>     In [3]:
>     plt.figure()
>     In [4]:
>     plt.boxplot(ob1)
>     In [5]:
>     plt.savefig('test.png')
>     In [6]: import
>     scipy.stats
>     In [7]:
>     scipy.stats.scoreatpercentile(ob1,75)
>     Out[7]: 5.5
>
>
>     Note that the 75th percentile is 5.5.  R agrees with this calculation.
>     However, in the boxplot, the top of the box is around 6, not 5.5.  Isn't
>     the top of the box supposed to be at the 75th percentile?
>
>     Thanks,
>
>     Jason
>
>     --
>     Jason Grout
>
>
> From  matplotlib/lib/matplotlib/axes.py
>
> You can see how matplotlib calculating percentiles. And yes it doesn't
> conform with scipy's scoreatpercentile()
>
>
>              # get median and quartiles
>              q1, med, q3 = mlab.prctile(d,[25,50,75])
>
> I[36]: q1
> O[36]: 2.0
>
> I[37]: med
> O[37]: 4.0
>
> I[38]: q3
> O[38]: 6.0
>
>
> Could this be due to a rounding? I don't know, but I am curious to hear
> the explanations for this discrepancy.

prctile does not handle the case where the exact percentile lies between two 
items. scoreatpercentile does.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco