# [Numpy-discussion] NumPy Histogram for Tentative NumPy Tutorial Questions

josef.pktd@gmai... josef.pktd@gmai...
Thu Nov 26 14:23:06 CST 2009

```On Thu, Nov 26, 2009 at 2:44 PM, Wayne Watson
<sierra_mtnview@sbcglobal.net> wrote:
> I decided to try some example code from Subject.
>
> import numpy
> import pylab
> # Build a vector of 10000 normal deviates with variance 0.5^2 and mean 2
> mu, sigma = 2, 0.5
> v = numpy.random.normal(mu,sigma,10000)
> # Plot a normalized histogram with 50 bins
> pylab.hist(v, bins=50, normed=1)       # matplotlib version (plot)
> pylab.show()
> # Compute the histogram with numpy and then plot it
> (n, bins) = numpy.histogram(v, bins=50, normed=1)  # NumPy version (no plot)
> pylab.plot(.5*(bins[1:]+bins[:-1]), n)
> pylab.show()
>
> After the histogram is displayed how do I get to the plot?
> Where is histogram described in some detail? Normalized?
> The histogram x-axis goes from 0 to 4.5. How does that happen?
> Is v is two dimensional? What if it's one dimensional?

matlplotlib's histogram uses numpy histogram for the calculations,
options are pretty well explained  in the numpy docs, matplotlib has
docs and examples for the display.

If I use numpy.histogram, then, I think, I used bar plot for the
display (scipy.stats.tutorial might also have an example where I had
taken the pattern from somewhere else)

numpy also has 2d and multidimensional histogram, but I don't know if
the new 3d features of matplotlib can display them.

Josef

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