Skip to content

Instantly share code, notes, and snippets.

@misho-kr
Last active October 27, 2019 09:26
Show Gist options
  • Save misho-kr/49f063e35d62ffb7b52cc9aebf84bfdd to your computer and use it in GitHub Desktop.
Save misho-kr/49f063e35d62ffb7b52cc9aebf84bfdd to your computer and use it in GitHub Desktop.
Summary of "Python Data Science Toolbox (Part 1)" course on Datacamp

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
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment