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Python Data Analysis, Second Edition

You're reading from   Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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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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Table of Contents (16) Chapters Close

Preface 1. Getting Started with Python Libraries FREE CHAPTER 2. NumPy Arrays 3. The Pandas Primer 4. Statistics and Linear Algebra 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

Using IPython as a shell

Data analysts, data scientists, and engineers are used to experimenting. IPython was created by scientists with experimentation in mind. The interactive environment that IPython provides is comparable to an interactive computing environment provided by Matlab, Mathematica, and Maple.

The following is a list of features of the IPython shell:

  • Tab completion, which helps you find a command
  • History mechanism
  • Inline editing
  • Ability to call external Python scripts with %run
  • Access to system commands
  • Access to the Python debugger and profiler

The following list describes how to use the IPython shell:

  • Starting a session: To start a session with IPython,enter the following instruction on the command line:
    $ ipython3
    Python 3.5.2 (default, Sep 28 2016, 18:08:09) 
    Type "copyright", "credits" or "license" for more information.
            IPython 5.1.0 -- An enhanced Interactive Python.
    ?         -> Introduction and overview of IPython's features.
    %quickref -> Quick reference.
    help      -> Python's own help system.
    object?   -> Details about 'object', use 'object??' for extra 
                         details.
    In [1]: quit()
    

    Tip

    The quit() function or Ctrl + D quits the IPython shell.

  • Saving a session: We might want to be able to go back to our experiments. In IPython, it is easy to save a session for later use with the following command:
    In [1]: %logstart
    Activating auto-logging. Current session state plus future 
             input saved:
             Filename : ipython_log.py
             Mode : rotate
             Output logging : False
             Raw input log : False
             Timestamping : False
    State : active
    

    Logging can be switched off as follows:

    In [9]: %logoff
    Switching logging OFF
    
  • Executing a system shell command: Execute a system shell command in the default IPython profile by prefixing the command with the ! symbol. For instance, the following input will get the current date:
    In [1]: !date
    

    In fact, any line prefixed with ! is sent to the system shell. We can also store the command output, as shown here:

    In [2]: thedate = !date
    In [3]: thedate
    
  • Displaying history: We can show the history of our commands with the %hist command. For example:
    In [1]: a = 2 + 2
    In [2]: a
    Out[2]: 4
    In [3]: %hist
    a = 2 + 2
    a
    %hist
    

    This is a common feature in command line interface (CLI) environments. We can also search through the history with the -g switch as follows:

    In [5]: %hist -g a = 2
          1: a = 2 + 2
    

We saw a number of so-called magic functions in action. These functions start with the % character. If the magic function is used on a line by itself, the % prefix is optional.

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Python Data Analysis, Second Edition - Second Edition
Published in: Mar 2017
Publisher: Packt
ISBN-13: 9781787127487
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