- Mastering pandas
- Table of Contents
- Mastering pandas
- Credits
- About the Author
- About the Reviewers
- www.PacktPub.com
- Preface
- 1. Introduction to pandas and Data Analysis
- 2. Installation of pandas and the Supporting Software
- 3. The pandas Data Structures
- 4. Operations in pandas, Part I – Indexing and Selecting
- 5. Operations in pandas, Part II – Grouping, Merging, and Reshaping of Data
- 6. Missing Data, Time Series, and Plotting Using Matplotlib
- 7. A Tour of Statistics – The Classical Approach
- 8. A Brief Tour of Bayesian Statistics
- Introduction to Bayesian statistics
- Mathematical framework for Bayesian statistics
- Probability distributions
- Bayesian statistics versus Frequentist statistics
- Conducting Bayesian statistical analysis
- Monte Carlo estimation of the likelihood function and PyMC
- References
- Summary
- 9. The pandas Library Architecture
- 10. R and pandas Compared
- 11. Brief Tour of Machine Learning
- Role of pandas in machine learning
- Installation of scikit-learn
- Introduction to machine learning
- Application of machine learning – Kaggle Titanic competition
- Data analysis and preprocessing using pandas
- A naïve approach to Titanic problem
- The scikit-learn ML/classifier interface
- Supervised learning algorithms
- Unsupervised learning algorithms
- Summary
- Index
Author
Femi Anthony
Reviewers
Opeyemi Akinjayeju
Louis Hénault
Carlos Marin
Commissioning Editor
Karthikey Pandey
Acquisition Editor
Kevin Colaco
Content Development Editor
Arun Nadar
Technical Editor
Mohita Vyas
Copy Editors
Tani Kothari
Jasmine Nadar
Vikrant Phadke
Project Coordinator
Neha Bhatnagar
Proofreader
Safis Editing
Indexer
Tejal Soni
Graphics
Jason Monteiro
Production Coordinator
Aparna Bhagat
Cover Work
Aparna Bhagat
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