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Python data analyticswith Pandas, Nu...

Nelli, Fabio.

Python data analyticswith Pandas, NumPy, and Matplotlib /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Python data analyticsby Fabio Nelli.
Reminder of title:	with Pandas, NumPy, and Matplotlib /
Author:	Nelli, Fabio.
Published:	Berkeley, CA :Apress :2018.
Description:	xix, 569 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Python (Computer program language)
Online resource:	https://doi.org/10.1007/978-1-4842-3913-1
ISBN:	9781484239131$q(electronic bk.)

Python data analyticswith Pandas, NumPy, and Matplotlib /
Nelli, Fabio.

Python data analyticswith Pandas, NumPy, and Matplotlib /[electronic resource] :by Fabio Nelli. - 2nd ed. - Berkeley, CA :Apress :2018. - xix, 569 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9781484239131$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-3913-1doiSubjects--Topical Terms:

215247
Python (Computer program language)

LC Class. No.: QA76.73.P98 / N455 2018

Dewey Class. No.: 005.133

Python data analyticswith Pandas, NumPy, and Matplotlib /
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505 0 $a 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.
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