Advanced Python: Working With Data
2h 5mAdvanced2024-08-15
Authors
Joe Marini
Senior Developer Advocate at Google, Developer
Course details
Data science is one of the fastest-growing areas of technology today. And whether you work with large data sets or just need to process spread sheet files, Python is a great language to use when working with data-intensive applications. In this course, Joe Marini gets you started on working with data in Python, highlighting some of the most useful built-in features of the language. Using a real data set from the United States Geological Survey that tracks earthquake information, Joe shows you how to perform data operations like sorting and filtering, determining basic information like minimum and maximum values, and reading and writing data to and from other formats like CSV and JSON. Check out this course with Joe to see how Python can help you make sense of your data.
Skills covered
Data Resource ManagementAdvancedPythonDatabase ManagementProgramming LanguagesOpen SourceSoftware Development
Concepts
0. Introduction
- 01 - Python and Data - Made for each other
- 02 - Getting Set Up
- 03 - The sample data set
- 04 - Tour of CoderPad
1. Built-In Data Functions
- 05 - Using built-in functions
- 06 - Finding min and max values
- 07 - Data utility functions
- 08 - Sorting data
- 09 - Data filtering
- 10 - Data transformation
- 11 - Solution - Build a data summary
2. Collection Classes
- 12 - Overview of collection classes
- 13 - Named tuples
- 14 - Default dictionaries
- 15 - Counters
- 16 - The deque class
- 17 - Solution - Classify event types
3. Serializing Data in Python
- 18 - Overview of serialization
- 19 - Serializing data as CSV
- 20 - Serializing data as JSON
- 21 - Deserialization of data
- 22 - Code Challenge - Create a CSV file
- 23 - Solution - Create a CSV file
4. Python Logging
- 24 - Overview of logging
- 25 - Basic logging
- 26 - Custom logging
Conclusion
- 27 - Next steps