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Python Data Science Toolbox (Part 1)

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  • 12 Videos
  • 46 Exercises
  • 3 hours 
  • 6,619 Participants
  • 3650 XP

Instructor(s):

Hugo Bowne-Anderson
Hugo Bowne-Anderson

Hugo hearts all things Pythonic and is charged with building out DataCamp’s Python curriculum. He can be found at hackathons, meetups & code sprints, primarily in NYC. Before joining the ranks of DataCamp, he worked in applied mathematics (biology) research at Yale University.

Collaborator(s):

Francisco Castro Francisco Castro

Course Description

It's now time to push forward and develop your Python chops even further. There are lots and lots 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. The art of function writing is what you'll learn 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 very own function writing practice. On top of this, you'll wrap up each Chapter by diving into using your acquired skills to write functions that analyze twitter DataFrames and are generalizable to broader Data Science contexts.