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Data Analysis with Python

You're reading from   Data Analysis with Python A Modern Approach

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789950069
Length 490 pages
Edition 1st Edition
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Author (1):
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David Taieb David Taieb
Author Profile Icon David Taieb
David Taieb
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Table of Contents (14) Chapters Close

Preface 1. Programming and Data Science – A New Toolset FREE CHAPTER 2. Python and Jupyter Notebooks to Power your Data Analysis 3. Accelerate your Data Analysis with Python Libraries 4. Publish your Data Analysis to the Web - the PixieApp Tool 5. Python and PixieDust Best Practices and Advanced Concepts 6. Analytics Study: AI and Image Recognition with TensorFlow 7. Analytics Study: NLP and Big Data with Twitter Sentiment Analysis 8. Analytics Study: Prediction - Financial Time Series Analysis and Forecasting 9. Analytics Study: Graph Algorithms - US Domestic Flight Data Analysis 10. The Future of Data Analysis and Where to Develop your Skills A. PixieApp Quick-Reference Other Books You May Enjoy Index

Chapter 3. Accelerate your Data Analysis with Python Libraries

"Every vision is a joke until the first man accomplishes it; once realized, it becomes commonplace."

Robert H Goddard

In this chapter, we will do a technical deep dive into the PixieApp framework. You will be able to use the following information both as a Getting Started tutorial and as reference documentation for the PixieApp programming model.

We will start with a high-level description of the anatomy of a PixieApp before diving in to its foundational concepts, such as routes and requests. To help follow along, we will incrementally build a GitHub Tracking sample application that applies the capabilities and best practices as they are being introduced, starting from building the data analytics to integrating them into the PixieApp.

By the end of this chapter, you should be able to apply the lessons...

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