Chapter 1 Preliminaries
Chapter 2: Introductory Examples
Chapter 3: Ipthon: An Interactive Computing and Development Environment
Chapter 4: Numpy Basics: Arrays and Vectorized Computation
Chapter 5: Getting Started with Pandas
Chapter 6: Data Loading, Storage, and File Formats
Chapter 7: Data Wrangling: Clean, Transform, Merge, Reshape
Chapter 8: Ploting and Visualization
Chapter 9: Data Aggregation and Group Operations
Chapter 10: Time Series
Chapter 11: Financial and Economic Data Applications
Chapter 12: Anvanced NumPy
Appendix: Python Language Essentials
Chapter 1: Reading from a CSV
Chapter 2: Selecting data & finding the most common complaint type
Chapter 3: Which borough has the most noise complaints?
Chapter 4: Find out on which weekday people bike the most with groupby and aggregate
Chapter 5: Combining dataframes and scraping Canadian weather data
Chapter 6: String operations! Which month was the snowiest?
Chapter 7: Cleaning up messy data
Chapter 8: Parsing Unix timestamps
Chapter 9: Loading data from SQL databases