IPython is the interactive computing shell for Python that will change the way you think about interactive shells. It brings to the table a host of very useful functionalities that will most likely become part of your default toolbox, including magic functions, tab completion, easy access to command-line tools, and much more. We will only scratch the surface here and strongly recommend that you keep exploring what can be done with IPython, see https://ipython.org/ for more details and options.
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Book Overview & Buying
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Table Of Contents
Practical Data Science Cookbook, Second Edition - Second Edition
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Practical Data Science Cookbook, Second Edition
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Overview of this book
As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don’t. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use.
Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python.
Table of Contents (12 chapters)
Preface
Free Chapter
Preparing Your Data Science Environment
Driving Visual Analysis with Automobile Data with R
Creating Application-Oriented Analyses Using Tax Data and Python
Modeling Stock Market Data
Visually Exploring Employment Data
Driving Visual Analyses with Automobile Data
Working with Social Graphs
Recommending Movies at Scale (Python)
Harvesting and Geolocating Twitter Data (Python)
Forecasting New Zealand Overseas Visitors
