Histograms and Kernel Density Estimation (KDE)

(Note: you can download the IPython Notebook here.)


A small plea for help: I used ipython nbconvert to make an html version of the notebook, stuck it on my website, and then used the pageview plugin to embed it above. Everything else I tried either broke wholesale, or broke for the images. If there's a better solution for IPython Notebooks inside WordPress posts, please let me know in the comments!)

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13 Responses to Histograms and Kernel Density Estimation (KDE)

  1. Arindam Paul says:

    Excellent !! One of the best explanations of KDE I have ever seen.
    This post has generated enough interest to read your other blogs. great job.

  2. Nils Wagner says:

    Assume that we have a spatial energy distribution given at discrete points in 3-D, i.e.

    E_i(x_i,y_i,z_i)

    where E_i denotes the energy and x_i,y_i,z_i are the corresponding coordinates.

    Is it possible to extract the local hot spots using scipy ?

    A small example is appreciated.

    Thanks in advance.

  3. domain says:

    It's really a cool and helpful piece of info. I'm happy that you simply shared this helpful information with us.
    Please stay us up to date like this. Thanks for sharing.

  4. Andreas says:

    Thanks for sharing your knowledge and interpretation of kernel density estimation with us. Very enlighting.

  5. gmas says:

    If I try to run your notebook, I get this name error:


    NameError Traceback (most recent call last)
    in ()
    ----> 1 ani = getHistBinNumAni(data)
    2 display_animation(ani, default_mode='once')

    NameError: name 'getHistBinNumAni' is not defined

    • gmas says:

      Ops.. I have just read the last part that asks to run the code before the other cells! Maybe you can add a note at the begin of the post..

  6. X says:

    Is there a way to fit data to an exponential distribution such that it maximizes the entropy H(p_i) = - sum p_i*log(p_i) where p_i is the probability of a given event?

    • mglerner says:

      I don't know, but I've been wondering about similar things for a while. If I do learn the answer, I'll update.

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  9. Koushik Khan says:

    Awesome presentation !

  10. Ben says:

    Fantastic explanation!
    Best KDE description I've found so far!
    Keep up the good work!

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