Python Data Analytics: With Pandas, NumPy, and Matplotlib
Autor Fabio Nellien Limba Engleză Paperback – 2 sep 2023
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
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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Specificații
ISBN-13: 9781484295311
ISBN-10: 1484295315
Pagini: 445
Ilustrații: XXI, 445 p. 696 illus., 183 illus. in color.
Dimensiuni: 178 x 254 x 29 mm
Greutate: 0.8 kg
Ediția:3rd ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
ISBN-10: 1484295315
Pagini: 445
Ilustrații: XXI, 445 p. 696 illus., 183 illus. in color.
Dimensiuni: 178 x 254 x 29 mm
Greutate: 0.8 kg
Ediția:3rd ed.
Editura: Apress
Colecția Apress
Locul publicării:Berkeley, CA, United States
Cuprins
1. An Introduction to Data Analysis .- 2. Introduction to the Python's World.- 3. The NumPy Library .- 4. The pandas Library-- An Introduction.- 5. pandas: Reading and Writing Data .- 6. pandas in Depth: Data Manipulation .- 7. Data Visualization with matplotlib .- 8. Machine Learning with scikit-learn.- 9. Deep Learning with TensorFlow.- 10. An Example - Meteorological Data.- 11. Embedding the JavaScript D3 Library in IPython Notebook.- 12. Recognizing Handwritten Digits.- 13. Textual data Analysis with NLTK.- 14. Image Analysis and Computer Vision with OpenCV.- Appendix A.- Appendix B.
Notă biografică
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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Caracteristici
Fully revised and updated with the latest tools and techniques for data analysis with Python Includes three new chapters on social media analysis, image analysis with OpenCV, and deep learning Written by IT Scientific Application Specialist, Fabio Nelli