Book Image

Learning IPython for Interactive Computing and Data Visualization, Second Edition

By : Cyrille Rossant
Book Image

Learning IPython for Interactive Computing and Data Visualization, Second Edition

By: Cyrille Rossant

Overview of this book

Python is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment well-adapted to data science and visualization. Together, these open source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors. This book is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and the Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in the Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this book, you will be able to perform in-depth analyses of all sorts of data.
Table of Contents (13 chapters)
Learning IPython for Interactive Computing and Data Visualization Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


In this chapter, we covered the basics of data analysis with pandas: loading a dataset, selecting rows and columns, grouping and aggregating quantities, and performing complex operations efficiently.

The next natural step is to conduct statistical analyses: hypothesis testing, modeling, predictions, and so on. Several Python libraries provide such functionality beyond pandas: SciPy, statsmodels, PyMC, and more. The IPython Cookbook contains many advanced examples of such analyses.

In the next chapter, we will introduce NumPy, the library underlying the entire SciPy ecosystem.