Advanced Python: Top Tools for Data Science and Engineering
2h 6mIntermediate2025-05-29
Authors
Joe Marini
Senior Developer Advocate at Google, Developer
Course details
This comprehensive course is designed to equip you with the essential skills for data processing, analysis, and application development using Python and the most popular data tools. Instructor Joe Marini shows you how to leverage powerful libraries and tools to manipulate data, interact with APIs, work with spreadsheets, and create shareable data applications. Joe gets you up and running with these popular tools, so you can decide for yourself where you want to explore further.
Learning objectives
Get an introduction to pandas, data analysis, data manipulation, Python Polars, Matplotlib, APIs, and more.
Learning objectives
Get an introduction to pandas, data analysis, data manipulation, Python Polars, Matplotlib, APIs, and more.
Skills covered
pandasData Science FoundationsData EngineeringPythonData AnalysisProgramming LanguagesData ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen SourceSoftware DevelopmentOne-Off
Concepts
0. Introduction
- 01 - The right tool for the job
- 02 - Getting set up
- 03 - Overview of the libraries
1. pandas for Data Analysis and Manipulation
- 04 - Overview of pandas
- 05 - pandas data structures
- 06 - Reading and writing data files with pandas
- 07 - pandas data operations
- 08 - Data cleaning with pandas
- 09 - Data cleaning operations
2. Polars - A Faster DataFrame
- 10 - Overview of Polars
- 11 - Comparing Polars with pandas
- 12 - Reading and writing data with Polars
- 13 - Working with Polars data
- 14 - Lazy execution with Polars
3. Faker for Generating Fake Data
- 15 - Intro to Faker
- 16 - Generating basic data
- 17 - Generating numerical data
- 18 - Generating text data
- 19 - Combining Faker with pandas
4. Visualizing Data
- 20 - Fundamentals of Matplotlib
- 21 - Creating a basic plot
- 22 - Customizing plot appearance
Conclusion
- 23 - Summary