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Summary of "Python Data Science Toolbox (Part 1)" course on Datacamp
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Python Data Science Toolbox (Part 1).md

Python Data Science Toolbox (Part 1)

It's time to push forward and develop your Python chops even further. There are tons of fantastic functions in Python and its library ecosystem. However, as a data scientist, you'll constantly need to write your own functions to solve problems that are dictated by your data. You will learn the art of function writing in this first Python Data Science Toolbox course. You'll come out of this course being able to write your very own custom functions, complete with multiple parameters and multiple return values, along with default arguments and variable-length arguments. You'll gain insight into scoping in Python and be able to write lambda functions and handle errors in your function writing practice. And you'll wrap up each chapter by using your new skills to write functions that analyze Twitter DataFrames.

Lead by Hugo Bowne-Anderson, Data Scientist at DataCamp

Writing your own functions

  • Functions parameters and return values
  • Tuples

Default arguments, variable-length arguments and scope

  • Nested functions
  • Local, global, nonlocal and builtin scope
  • Default, variable length arguments and variablie length keyword arguments

Lambda functions and error-handling

  • Map, Filter, Reduce
  • Error handling and exceptions
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