Python Data Analytics

1. Front Matter

   Pages i-xxi

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2. An Introduction to Data Analysis

   • Fabio Nelli

   Pages 1-12

3. Introduction to the Python’s World

   • Fabio Nelli

   Pages 13-34

4. The NumPy Library

   • Fabio Nelli

   Pages 35-61

5. The pandas Library—An Introduction

   • Fabio Nelli

   Pages 63-101

6. pandas: Reading and Writing Data

   • Fabio Nelli

   Pages 103-130

7. pandas in Depth: Data Manipulation

   • Fabio Nelli

   Pages 131-165

8. Data Visualization with matplotlib

   • Fabio Nelli

   Pages 167-235

9. Machine Learning with scikit-learn

   • Fabio Nelli

   Pages 237-264

10. An Example—Meteorological Data

    • Fabio Nelli

    Pages 265-288

11. Embedding the JavaScript D3 Library in IPython Notebook

    • Fabio Nelli

    Pages 289-309

12. Recognizing Handwritten Digits

    • Fabio Nelli

    Pages 311-316

13. Writing Mathematical Expressions with LaTeX

    • Fabio Nelli

    Pages 317-326

14. Open Data Sources

    • Fabio Nelli

    Pages 327-330

15. Back Matter

    Pages 331-337

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Python Data Analytics will help you tackle the world of data acquisition and analysis using the power of the Python language. At the heart of this book lies the coverage of pandas, an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.


Author Fabio Nelli expertly shows the strength of the Python programming language when applied to processing, managing and retrieving information. Inside, you will see how intuitive and flexible it is to discover and communicate meaningful patterns of data using Python scripts, reporting systems, and data export. This book examines how to go about obtaining, processing, storing, managing and analyzing data using the Python programming language.




You will use Python and other open source tools to wrangle data and tease out interesting and important trends in that data that will allowyou to predict future
patterns. Whether you are dealing with sales data, investment data (stocks, bonds, etc.), medical data, web page usage, or any other type of data set, Python can be used to interpret, analyze, and glean information from a pile of numbers and statistics. 

This book is an invaluable reference with its examples of storing and accessing data in a database; it walks you through the process of report generation; it provides three real world case studies or examples that you can take with you for your everyday analysis needs.

“The book is named ‘Python Data Analytics’ and it provides exactly what it says. It shows you how to use Python step-by-step for Data Analytics. The important libraries in Python – NumPy, Pandas, MatPlotLib are presented in literally step-by-step introduction – from their installation to about 70-80 % of their properties and functions. … if you need Python for data analysis this book is quite ok. With step by step approach, you will become fluent in what you write … .” (Vitosh Academy, vitoshacademy.com, September, 2015)

Fabio Nelli, is an IT Scientific Application Specialist at IRBM Science Park, a private research center in Pomezia, Roma (Italy). He has beena computer consultant for many years at IBM, EDS, Merck Sharp, and Dohme, along with several banks and insurance companies.He has an Organic Chemistry degree and many years of experience in Information technologies and Automation systems applied to Life Sciences (Tech Specialist at Beckman Coulter Italy and Spain).He is currently developing Java applications that interface Oracle databases with scientific instrumentations generating data and web server applications providing analysis of the results to researchers in real time.

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