Friday, May 3, 2013

A new RefCard from the GlowingPython!

Check out the DZone RefCard from the GlowingPython:

Discovering and Visualizing Patterns with Python!

This Refcard is a collection of code examples that introduces the reader to the principal Data Mining tasks using Python. In the RefCard you will find the following contents:
  • How to import and visualize data.
  • How to classify and cluster data.
  • How to discover relationships in the data using regression and correlation measures.
  • How to reduce the dimensionality of the data in order to compress and visualize the information it brings.
  • How to analyze structured data with networkx.
Each topic is covered with code examples based on four of the major Python libraries for data analysis and manipulation: numpy, matplotlib,sklearn and networkx. Here is a preview of the first two pages:


Click on the preview to get the RefCard!
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5 comments:

  1. AnonymousMay 5, 2013 at 3:47 PM

    This comment has been removed by a blog administrator.

    ReplyDelete
  2. Scott EdwardsJune 10, 2013 at 8:48 PM

    Just downloaded it - looks great. Thanks for writing this!

    ReplyDelete
  3. AnonymousJune 30, 2013 at 7:27 PM

    Thanks for putting this together. I just finished Coursera classes in Data Analysis (using R) and Machine Learning (using Octave) and this was a perfect way to get an overview of those topics in a language I like a LOT better. I found a few typos:
    1. Page 2, last paragraph, left side: three instances of the word "rows" instead of "columns".
    2. Page 4, third code block, right side: refers to "tt" instead of "c" in three lines of code.
    3. Page 5, first code block, right side: reads "import arrange" instead of "import arange".

    Thanks again for the very helpful guided tour thru numpy and friends.

    ReplyDelete
    Replies
    1. JustGlowingJune 30, 2013 at 8:13 PM

      Thanks for reporting the typos. I'll forward them to the editor. I'm glad this Refcard was useful.

      Delete
  4. JustGlowingJuly 10, 2013 at 7:33 AM

    Anticipation, in the new version of this refcard the first code block will be replaced by:

    from urllib2 import urlopen
    from contextlib import closing
    url = 'http://aima.cs.berkeley.edu/data/iris.csv'
    with closing(urlopen(url)) as u, open('iris.csv', 'w') as f:
    f.write(u.read())

    ReplyDelete

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