Python Tutorial: Writing functions in Python

Опубликовано: 09 Ноябрь 2016
на канале: DataCamp

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Learn all about writing functions in Python: https://www.datacamp.com/courses/pyth...

Welcome to the Python Data Science Toolbox! My name is Hugo Bowne-Anderson and I'm a Data Scientist at DataCamp. These courses are for those who have taken DataCamp's introductory Python courses and are itching to develop their Python data science skills further. You are already versed in the basics of Python variables and know about ints, floats, strings and booleans, all essential building blocks for budding Pythonistas. You're also familiar with lists and dictionaries, objects which you'll invariably use to store data in your work. You have learnt about functions and packages, how to use numpy to store, access and manipulate numerical data. You know about control flow, pandas DataFrames and how to plot with matplotlib, along with having had a deep dive into hacker statistics.

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 flexible arguments. You'll gained 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. But don't take my word for it. Take the course instead! I'll see you shortly in Chapter 1 ;-)

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