Python Data Analytics : With Pandas, NumPy, and Matplotlib / by Fabio Nelli

Von:

Nelli, Fabio [VerfasserIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: SpringerLink Bücher | Springer eBook CollectionVerlag: Berkeley, CA : Apress, 2018Auflage: 2nd edBeschreibung: Online-Ressource (XIX, 569 p. 648 illus, online resource)ISBN:

9781484239131

Schlagwörter:

Andere physische Formen: 9781484239124 | 9781484239148 | Erscheint auch als: Python data analytics. Druck-Ausgabe Second edition. New York : Apress, 2018. xix, 569 Seiten | Printed edition: 9781484239124 | Printed edition: 9781484239148 DDC-Klassifikation:

005.133

LOC-Klassifikation:

QA76.73.P98

DOI: DOI: 10.1007/978-1-4842-3913-1Online-Ressourcen:

Zusammenfassung: 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 dataZusammenfassung: 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 BPPN: PPN: 1031845933Package identifier: Produktsigel: ZDB-2-CWD | ZDB-2-SEB | ZDB-2-SXPC

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