Learning IPython for Interactive Computing and Data Visualization

More Information
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
Page Count 138
Course Length 4 hours 8 minutes
ISBN 9781782169932
Date Of Publication 24 Apr 2013

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.