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 online by emailing the publisher with proof of purchase at info@merclearning.com.

Features:

• 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

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 online by emailing the publisher with proof of purchase at info@merclearning.com.

Features:

• 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

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 online by emailing the publisher with proof of purchase at info@merclearning.com.

Features:

• 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