Python Data Analytics
eBook - ePub

Python Data Analytics

With Pandas, NumPy, and Matplotlib

  1. English
  2. ePUB (mobile friendly)
  3. Only available on web
eBook - ePub

Python Data Analytics

With Pandas, NumPy, and Matplotlib

Book details
Table of contents
Citations

About This Book

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 third edition is fully updated for the latest version of Python and its related libraries, and includes coverage of 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, Third 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

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Information

Publisher
Apress
Year
2023
ISBN
9781484295328
Edition
3
Topic
Computer Science
Subtopic
Programming in Python
Index
Computer Science

Table of contents

  1. Cover
  2. Front Matter
  3. 1. An Introduction to Data Analysis
  4. 2. Introduction to the Python World
  5. 3. The NumPy Library
  6. 4. The pandas Library—An Introduction
  7. 5. pandas: Reading and Writing Data
  8. 6. pandas in Depth: Data Manipulation
  9. 7. Data Visualization with matplotlib and Seaborn
  10. 8. Machine Learning with scikit-learn
  11. 9. Deep Learning with TensorFlow
  12. 10. An Example—Meteorological Data
  13. 11. Embedding the JavaScript D3 Library in the IPython Notebook
  14. 12. Recognizing Handwritten Digits
  15. 13. Textual Data Analysis with NLTK
  16. 14. Image Analysis and Computer Vision with OpenCV
  17. Back Matter