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Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

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Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries 2. NumPy Arrays FREE CHAPTER 3. Statistics and Linear Algebra 4. pandas Primer 5. Retrieving, Processing, and Storing Data 6. Data Visualization 7. Signal Processing and Time Series 8. Working with Databases 9. Analyzing Textual Data and Social Media 10. Predictive Analytics and Machine Learning 11. Environments Outside the Python Ecosystem and Cloud Computing 12. Performance Tuning, Profiling, and Concurrency A. Key Concepts
B. Useful Functions C. Online Resources
Index

Reading manual pages

When we are in IPython's pylab mode ($ ipython –pylab), we can open manual pages for NumPy functions with the help command. It is not necessary to know the name of a function. We can type a few characters and then let tab completion do its work. Let's, for instance, browse the available information for the arange() function.

We can browse the available information in either of the following two ways:

  • Calling the help function: Call the help command. Type in a few characters of the function and press the Tab key.
    Reading manual pages
  • Querying with a question mark: Another option is to append a question mark to the function name. You will then, of course, need to know the function name, but you don't have to type help, for example:
    In [3]: arange?
    

    Tab completion is dependent on readline, so you need to make sure that it is installed. It can be installed with setuptools with one of the following commands:

    $ easy_install readline
    $ pip install readline
    

    The question mark gives you information from docstrings.

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