IPython provides a rich architecture for interactive computing, and as a Python developer you can take advantage of this practical hands-on guide to make yourself an expert. Covers numerical computing, data analysis, and more.
Overview
- 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
In Detail
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 youÂ’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.
What you will learn from this book
- 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
Approach
A practical hands-on guide which focuses on interactive programming, numerical computing, and data analysis with IPython.
Who this book is written for
This book is for Python developers who use Python as a scripting language or for software development, and are interested in learning IPython for increasing their productivity during interactive sessions in the console. Knowledge of Python is required, whereas no knowledge of IPython is necessary.
