As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cleaning. The book includes numerous code samples using NumPy, Pandas, Matplotlib, Seaborn, and features an appendix on regular expressions. Companion files with source code and color figures are available for downloading with Amazon proof of purchase by writing to [email protected]
+Includes a concise introduction to Python 3
+Provides a thorough introduction to data and data cleaning
+Covers NumPy and Pandas
+Introduces statistical concepts and data visualization (Matplotlib/Seaborn)
+Features an appendix on regular expressions
+Includes companion files with source code and figures(Companion files with source code and color figures are available for downloading with Amazon proof of purchase by writing to [email protected]
1: Introduction to Python. 2: Working with Data. 3: Introduction to NumPy. 4: Introduction to Pandas. 5: Introduction to Probability and Statistics. 6: Data Visualization. Appendix. Regular Expressions. Index.
About the Author
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, and TensorFlow. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the Python Pocket Primer (Mercury Learning).