Great, thanks!
Rgds
marcus
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Are you running python 2 or python 3? If you're on python 2, what happens
if you add from __future__ import division to the top of your script?
On Tue, Aug 25, 2015 at 10:31 PM, chtan ch...@unisim.edu.sg wrote:
Hi,
the outliers in the boxplot do not seem to be drawn in the following
extreme
Your perturbed and unperturbed scenarios draw the same figure on my machine
(mpl v1.4.1).
The reason why you don't get any outliers is the following:
Boxplot uses matplotlib.cbook.boxplot_stats under the hood to compute where
everything will be drawn. If you look in there, you'll see this little
I'm on python 2.
I get the same outputs after adding from __future__ import division.
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Uh, now I understand why it's behaving this way. Tx Paul.
From the documentation, it seems natural to expect the behaviour to be
uniform throughout the meaningful range for IQR.
How may I go about searching for the responsible code on my own in
situations like this?
From the perplexing behaviour
Even though I'm familiar with the boxplot source code, I largely use
IPython for quick investigations like this.
In IPython, doing something like matplotlib.Axes.boxplot?? shows the full
source code for that functions\.
Then I saw/remembered that boxplot now just calls
Hi,
the outliers in the boxplot do not seem to be drawn in the following extreme
scenario:
Data Value: 1, Frequency: 5
Data Value: 2, Frequency: 100
Data Value: 3, Frequency: 5
Here, Q1 = Q2 = Q3, so IQR = 0.
Data values 1 and 3 are therefore outliers according to the definition in
the api
