Practical Data Science using Python - Python Lambda Functions

The video tutorial introduces Lambda functions in Python, highlighting their characteristics as anonymous, inline functions with a single expression. It compares Lambda functions with user-defined functions, emphasizing their speed and efficiency in simple, non-repetitive tasks. The tutorial demonstrates the use of map and reduce functions with Lambda, showcasing their application in processing series of values and performing reduction operations, respectively.

What are Lambda functions and how do they differ from regular user-defined functions?

Explain the advantages of using Lambda functions in Python.

Discuss the use of anonymous Lambda functions and their benefits.

Describe the syntax of a Lambda function in Python.

Explain how the execution time of Lambda functions compares to user-defined functions.

How can Lambda functions be applied to a series of values using the map function?

Provide an example of how to create a new field in a DataFrame using a Lambda function.

What is the purpose of the reduce function in conjunction with Lambda functions?

What is the difference between the map function and the reduce function when used with Lambda functions?

What are the limitations of Lambda functions in Python?