Python Data Analytics

1. Front Matter

   Pages i-xix

   PDF

2. An Introduction to Data Analysis

   • Fabio Nelli

   Pages 1-17

3. Introduction to the Python World

   • Fabio Nelli

   Pages 19-48

4. The NumPy Library

   • Fabio Nelli

   Pages 49-85

5. The pandas Library—An Introduction

   • Fabio Nelli

   Pages 87-139

6. pandas: Reading and Writing Data

   • Fabio Nelli

   Pages 141-180

7. pandas in Depth: Data Manipulation

   • Fabio Nelli

   Pages 181-229

8. Data Visualization with matplotlib

   • Fabio Nelli

   Pages 231-312

9. Machine Learning with scikit-learn

   • Fabio Nelli

   Pages 313-347

10. Deep Learning with TensorFlow

    • Fabio Nelli

    Pages 349-407

11. An Example— Meteorological Data

    • Fabio Nelli

    Pages 409-443

12. Embedding the JavaScript D3 Library in the IPython Notebook

    • Fabio Nelli

    Pages 445-471

13. Recognizing Handwritten Digits

    • Fabio Nelli

    Pages 473-486

14. Textual Data Analysis with NLTK

    • Fabio Nelli

    Pages 487-506

15. Image Analysis and Computer Vision with OpenCV

    • Fabio Nelli

    Pages 507-535

16. Back Matter

    Pages 537-569

    PDF

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. 


This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation


Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data.

What You'll Learn

• Understand the core concepts of data analysis and the Python ecosystem
  
• Go in depth with pandas for reading, writing, and processing data
  
• Use tools and techniques for data visualization and image analysis
  
• Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch
  

Who This Book Is For



Experienced Python developers who need to learn about Pythonic tools for data analysis

• Deep Learning
• Machine Learning
• TensorFlow
• Keras
• Theano
• PyTorch
• OpenCV
• Image Analysis
• Text Mining
• Social Media Analysis
• Social Network Analysis
• Data visualization
• Data Analysis

• Rome, Italy

  Fabio Nelli

Fabio Nelli is an IT Scientific Application Specialist at IRBM Science Park, a private research center in Pomezia, Roma, Italy. He has been a 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 instrumentation generating data and web server applications providing analysis of the results to researchers in real time.

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