Learning IPython for Interactive Computing and Data Visualization, Second Editio

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Learning IPython for Interactive Computing and Data Visualization, Second Edition

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关键词：Interactive computing Learning interact ipython

Learn       
Debug your code from the IPython console
Benchmark and profile your code from IPython
Perform efficient vectorized computations with NumPy
Analyze data tables with Pandas
Create visualizations with Matplotlib
Parallelize your code easily with IPython
Customize IPython and create your own magic commands
Accelerate your Python code using dynamic C compilation with Cython
About       
You already use Python as a scripting language, but did you know it is also increasingly used for scientific computing and data analysis? Interactive programming is essential in such exploratory tasks and IPython is the perfect tool for that. Once you’ve learnt it, you won’t be able to live without it.

"Learning IPython for Interactive Computing and Data Visualization" is a practical, hands-on, example-driven tutorial to considerably improve your productivity during interactive Python sessions, and shows you how to effectively use IPython for interactive computing and data analysis.

This book covers all aspects of IPython, from the highly powerful interactive Python console to the numerical and visualization features that are commonly associated with IPython.

You will learn how IPython lets you perform efficient vectorized computations, through examples covering numerical simulations with NumPy, data analysis with Pandas, and visualization with Matplotlib. You will also discover how IPython can be conveniently used to optimize your code using parallel computing and dynamic compilation in C with Cython.

"Learning IPython for Interactive Computing and Data Visualization" will allow you to optimize your productivity in interactive Python sessions.

Features       
A practical step-by-step tutorial which will help you to replace the Python console with the powerful IPython command-line interface
Use the IPython notebook to modernize the way you interact with Python
Perform highly efficient computations with NumPy and Pandas
Optimize your code using parallel computing and Cython

Table of Contents

1 Getting Started with IPython
2 Interactive Work with IPython
3 Numerical Computing with IPython
4 Interactive Plotting and Graphical Interfaces
5 High-Performance and Parallel Computing
6 Customizing IPython

Authors
Cyrille Rossant
Cyrille Rossant, PhD, is a neuroscience researcher and software engineer at University College London. He is a graduate of école Normale Supérieure, Paris, where he studied mathematics and computer science. He has also worked at Princeton University and Collège de France. While working on data science and software engineering projects, he gained experience in numerical computing, parallel computing, and high-performance data visualization.

He is the author of Learning IPython for Interactive Computing and Data Visualization, Second Edition, Packt Publishing.

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