Practical Python: Data Wrangling and Data Quality
1. Introduction to Data Wrangling and Data Quality
2. Introduction to Python
3. Understanding Data Quality
4. Working with File-Based and Feed-Based Data in Python
5. Accessing Web-Based Data
6. Assessing Data Quality
7. Cleaning, Transforming, and Augmenting Data
8. Structuring and Refactoring Your Code
9. Introduction to Data Analysis
10. Presenting Your Data
11. Beyond Python
https://github.com/PracticalPythonDataWranglingAndQuality/data_wrangling_exercises - This repo contains draft coding exercises for the early-release version of the book Practical Python: Data Wrangling and Data Quality to be published by O'Reilly Media in 2021.
