Re: [Matplotlib-users] Normalized Histograms

Hi Steven,

Try this:

import numpy as np
import numpy.random
import matplotlib as mpl
import matplotlib.pyplot as plt

x = np.random.randn(1000)
h, binedg = np.histogram(x, 10)

wid = binedg[1:] - binedg[:-1]
plt.bar(binedg[:-1], h/float(x.size), width=wid)


On Nov 30, 2011, at 10:25 AM, Steven Boada wrote:

> Hi Users,
>
> I'm looking to make a histogram that is normalized by the total number
> of items shown in the histogram. For example:
>
> Let's say that I have an array 1000 items long. If I make a  
> histogram in
> the normal way hist(x,10) then I get a histogram showing the total
> number of items in each bin. What I want to do is take that total  
> number
> in each bin and divide them by 1000 and then make the plot.
>
> So if one of my bins has 350 objects in it, then it would be  
> changed to
> 0.35.
>
> Another way to say it would be that I want the height of the histogram
> to represent the fraction of the total. I am pretty sure that this is
> different than using the "normed=True" flag, but I couldn't find  
> anyone
> talking about this when I searched.
>
> Thanks
>
> Steven
>
>
> ---------------------------------------------------------------------- 
> --------
> All the data continuously generated in your IT infrastructure
> contains a definitive record of customers, application performance,
> security threats, fraudulent activity, and more. Splunk takes this
> data and makes sense of it. IT sense. And common sense.
> http://p.sf.net/sfu/splunk-novd2d
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users