Book Image

Python Data Science Essentials - Second Edition

By : Luca Massaron, Alberto Boschetti
Book Image

Python Data Science Essentials - Second Edition

By: Luca Massaron, Alberto Boschetti

Overview of this book

Fully expanded and upgraded, the second edition of Python Data Science Essentials takes you through all you need to know to suceed in data science using Python. Get modern insight into the core of Python data, including the latest versions of Jupyter notebooks, NumPy, pandas and scikit-learn. Look beyond the fundamentals with beautiful data visualizations with Seaborn and ggplot, web development with Bottle, and even the new frontiers of deep learning with Theano and TensorFlow. Dive into building your essential Python 3.5 data science toolbox, using a single-source approach that will allow to to work with Python 2.7 as well. Get to grips fast with data munging and preprocessing, and all the techniques you need to load, analyse, and process your data. Finally, get a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users.
Table of Contents (13 chapters)
Python Data Science Essentials - Second Edition
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Preface

Interactive visualizations with Bokeh


The recent success of D3.js in visualization tasks in data science is due to its paradigm that leads to graphical computations happening in the browser, not on the server side. Visualizations can be delivered faster (no latency due to data going to a server and graphics getting back to the web browser) and in an interactive and personalized way.

Bokeh, from the Japanese "blurred" (a kind of photographic rendering that emphasizes the subject of the photo while blurring the background), is a Python package and part of the pydata stack that allows using web browser for presentations, mimicking the graphic style and interactivity of D3.js. It is a package that strives to make otherwise difficult representations an easy task, such as building dashboards, creating interactive plots, and representing large datasets.

We are just going to introduce it briefly, focusing on how to render matplotlib-based plots to be posted on the Web and leaving exploration of its...