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Python: End-to-end Data Analysis

You're reading from   Python: End-to-end Data Analysis Leverage the power of Python to clean, scrape, analyze, and visualize your data

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Product type Course
Published in May 2017
Publisher Packt
ISBN-13 9781788394697
Length 931 pages
Edition 1st Edition
Languages
Tools
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Authors (5):
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Luiz Felipe Martins Luiz Felipe Martins
Author Profile Icon Luiz Felipe Martins
Luiz Felipe Martins
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Phuong Vo.T.H Phuong Vo.T.H
Author Profile Icon Phuong Vo.T.H
Phuong Vo.T.H
Martin Czygan Martin Czygan
Author Profile Icon Martin Czygan
Martin Czygan
Magnus Vilhelm Persson Magnus Vilhelm Persson
Author Profile Icon Magnus Vilhelm Persson
Magnus Vilhelm Persson
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Toc

Appendix D. Tips and Tricks for Command-Line and Miscellaneous Tools

In this book we used various tools, such as the IPython notebook and Unix shell commands. We have a short list of tips, which is not meant to be exhaustive. For working with databases, I recommend the DbVisualiser software available at https://www.dbvis.com/ (retrieved January 2016). It supports all the major database products and operating systems. Also, I like to use text expanders in a desktop environment.

IPython notebooks

I explained a minimal workflow for notebooks. Also, I made simple IPython widgets, which were used throughout the book, so I will describe them here. To run the IPython notebook code, follow these steps:

  1. Start the IPython notebook either with your GUI or with the following command:
    $ jupyter notebook
    
  2. Run the code either cell by cell or in one run.

I made a widget that sets some of the matplotlib properties. The settings are stored in the dautil.json file in the current folder. These files should...

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