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In this course, you will learn :
- Discover what it takes to write efficient Python code.
- Explore Python's Standard Library, learn about NumPy arrays, and put some of Python's built-in tools to the test.
- Learn how to collect and compare runtimes for various coding approaches.
- You'll practise profiling your code base and identifying bottlenecks with the line profiler and memory profiler packages.
- Learn how to use set theory and a few useful built-in modules for writing efficient code.
- Then you'll learn about Python looping patterns and how to make them more efficient.
- You'll discover the various options for iterating over a DataFrame.
- Learn how to apply functions to data stored in a DataFrame in an efficient manner.
Syllabus :
- Foundations for efficiencies
- Timing and profiling code
- Gaining efficiencies
- Basic pandas optimizations
