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Python Data Analytics: With Pandas, Numpy, And Matplotlib
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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 Scikitlearn.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 Highperformance, Easytouse Data Structures And Tools For Data Manipulationauthor 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 Ecosystemgo In Depth With Pandas For Reading, Writing, And Processing Datause Tools And Techniques For Data Visualization And Image Analysisexamine Popular Deep Learning Libraries Keras, Theano,Tensorflow, And Pytorchwho This Book Is Forexperienced Python Developers Who Need To Learn About Pythonic Tools For Data Analysis
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- Q: How many pages does this book have? A: This book contains five hundred eighty-eight pages. It offers extensive content on data analytics using Python.
- Q: What is the binding type of this book? A: The binding type is paperback. This makes it lightweight and easy to handle.
- Q: What are the dimensions of this book? A: The book measures seven point zero one inches in length, one point three four inches in width, and ten inches in height.
- Q: Is this book suitable for beginners? A: No, this book is intended for experienced Python developers. It covers advanced topics in data analysis and visualization.
- Q: What tools does this book cover for data visualization? A: The book covers tools like matplotlib for visualization and OpenCV for image analysis. These tools are essential for effective data representation.
- Q: How do I use this book for learning? A: You can use this book as a comprehensive guide. Follow the chapters and examples to learn data analysis techniques using Python.
- Q: Is this book safe for all audiences? A: Yes, this book is appropriate for anyone interested in data analytics. However, it is recommended for those with prior programming knowledge.
- Q: Can I use this book for a university course? A: Yes, this book is suitable for university courses in data science and analytics. It provides in-depth knowledge and practical examples.
- Q: How should I store this book to keep it in good condition? A: Store this book in a cool, dry place away from direct sunlight. This will help maintain the quality of the pages and cover.
- Q: What should I do if the book arrives damaged? A: If the book arrives damaged, you can return it for a replacement. Ensure to follow the return policy provided by the seller.
- Q: Does this book include examples of real-world applications? A: Yes, it includes examples of real-world applications such as sales data analysis and handwriting recognition.
- Q: What programming languages does this book focus on? A: The book focuses on Python as the primary programming language for data analysis. It teaches various libraries within the Python ecosystem.
- Q: Is there a focus on machine learning in this book? A: Yes, the book covers machine learning techniques using libraries like scikit-learn. It introduces foundational concepts in the field.
- Q: Are there exercises at the end of each chapter? A: Yes, each chapter includes exercises to reinforce learning and provide hands-on experience with the concepts discussed.
- Q: Who is the author of this book? A: The author is Fabio Nelli, known for his expertise in Python and data analytics. His experience enhances the book's credibility.