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Hands-On Data Analysis with Pandas

You're reading from   Hands-On Data Analysis with Pandas Efficiently perform data collection, wrangling, analysis, and visualization using Python

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Product type Paperback
Published in Jul 2019
Publisher
ISBN-13 9781789615326
Length 740 pages
Edition 1st Edition
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Author (1):
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Stefanie Molin Stefanie Molin
Author Profile Icon Stefanie Molin
Stefanie Molin
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Table of Contents (21) Chapters Close

Preface 1. Section 1: Getting Started with Pandas
2. Introduction to Data Analysis FREE CHAPTER 3. Working with Pandas DataFrames 4. Section 2: Using Pandas for Data Analysis
5. Data Wrangling with Pandas 6. Aggregating Pandas DataFrames 7. Visualizing Data with Pandas and Matplotlib 8. Plotting with Seaborn and Customization Techniques 9. Section 3: Applications - Real-World Analyses Using Pandas
10. Financial Analysis - Bitcoin and the Stock Market 11. Rule-Based Anomaly Detection 12. Section 4: Introduction to Machine Learning with Scikit-Learn
13. Getting Started with Machine Learning in Python 14. Making Better Predictions - Optimizing Models 15. Machine Learning Anomaly Detection 16. Section 5: Additional Resources
17. The Road Ahead 18. Solutions
19. Other Books You May Enjoy Appendix

Data resources

As with any skill, to get better we need to practice, which, for us, means we need to find data to practice on. There is no best dataset to practice with; rather, each person should find data they are interested in exploring. While this section is by no means comprehensive, it contains resources for data from various topics in the hopes that everyone can find something they want to use.

Unsure of what kind of data to look for? What are some of the things you have wondered about, relating to a topic you find interesting? Has data been collected on this topic, and can you access it? Let your curiosity guide you!

Python packages

Both seaborn and scikit-learn provide built-in sample datasets that you can experiment...

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