更新时间：2021-07-02 16:30:58
coverpage
Mastering Python Data Analysis
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Why subscribe?
Free access for Packt account holders
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Chapter 1. Tools of the Trade
Before you start
Using the notebook interface
Imports
An example using the Pandas library
Summary
Chapter 2. Exploring Data
The General Social Survey
Univariate data
Relationships between variables – scatterplots
Chapter 3. Learning About Models
Models and experiments
The cumulative distribution function
Working with distributions
The probability density function
Where do models come from?
Multivariate distributions
Chapter 4. Regression
Introducing linear regression
Multivariate regression
Logistic regression
Chapter 5. Clustering
Introduction to cluster finding
K-means clustering
Hierarchical clustering analysis
Chapter 6. Bayesian Methods
The Bayesian method
U.S. air travel safety record
Climate change - CO2 in the atmosphere
Chapter 7. Supervised and Unsupervised Learning
Introduction to machine learning
Scikit-learn
Linear regression
Clustering
Seeds classification
Chapter 8. Time Series Analysis
Introduction
Pandas and time series data
Indexing and slicing
Resampling smoothing and other estimates
Stationarity
Patterns and components
Time series models
Appendix A. More on Jupyter Notebook and matplotlib Styles
Jupyter Notebook
Matplotlib styles
Useful resources
