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Index
Cover
Python® for Data Science For Dummies®
Introduction
Part I: Getting Started with Python for Data Science
Chapter 1: Discovering the Match between Data Science and Python
Chapter 2: Introducing Python’s Capabilities and Wonders
Chapter 3: Setting Up Python for Data Science
Chapter 4: Reviewing Basic Python
Part II: Getting Your Hands Dirty with Data
Chapter 5: Working with Real Data
Chapter 6: Conditioning Your Data
Chapter 7: Shaping Data
Chapter 8: Putting What You Know in Action
Part III: Visualizing the Invisible
Chapter 9: Getting a Crash Course in MatPlotLib
Chapter 10: Visualizing the Data
Chapter 11: Understanding the Tools
Part IV: Wrangling Data
Chapter 12: Stretching Python’s Capabilities
Chapter 13: Exploring Data Analysis
Chapter 14: Reducing Dimensionality
Chapter 15: Clustering
Chapter 16: Detecting Outliers in Data
Part V: Learning from Data
Chapter 17: Exploring Four Simple and Effective Algorithms
Chapter 18: Performing Cross-Validation, Selection, and Optimization
Chapter 19: Increasing Complexity with Linear and Nonlinear Tricks
Chapter 20: Understanding the Power of the Many
Part VI: The Part of Tens
Chapter 21: Ten Essential Data Science Resource Collections
Chapter 22: Ten Data Challenges You Should Take
About the Authors
Cheat Sheet
Connect with Dummies
End User License Agreement
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