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Python Data Science Toolbox (Part 1)

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

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Descrição do Curso

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.
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  1. 1

    Writing your own functions

    Grátis

    In this chapter, you'll learn how to write simple functions, as well as functions that accept multiple arguments and return multiple values. You'll also have the opportunity to apply these new skills to questions commonly encountered by data scientists.

    Reproduzir Capítulo Agora
    User-defined functions
    50 xp
    Strings in Python
    50 xp
    Recapping built-in functions
    50 xp
    Write a simple function
    100 xp
    Single-parameter functions
    100 xp
    Functions that return single values
    100 xp
    Multiple parameters and return values
    50 xp
    Functions with multiple parameters
    100 xp
    A brief introduction to tuples
    100 xp
    Functions that return multiple values
    100 xp
    Bringing it all together
    50 xp
    Bringing it all together (1)
    100 xp
    Bringing it all together (2)
    100 xp
    Congratulations!
    50 xp
  2. 2

    Default arguments, variable-length arguments and scope

    In this chapter, you'll learn to write functions with default arguments so that the user doesn't always need to specify them, and variable-length arguments so they can pass an arbitrary number of arguments on to your functions. You'll also learn about the essential concept of scope.

    Reproduzir Capítulo Agora
    Scope and user-defined functions
    50 xp
    Pop quiz on understanding scope
    50 xp
    The keyword global
    100 xp
    Python's built-in scope
    50 xp
    Nested functions
    50 xp
    Nested Functions I
    100 xp
    Nested Functions II
    100 xp
    The keyword nonlocal and nested functions
    100 xp
    Default and flexible arguments
    50 xp
    Functions with one default argument
    100 xp
    Functions with multiple default arguments
    100 xp
    Functions with variable-length arguments (*args)
    100 xp
    Functions with variable-length keyword arguments (**kwargs)
    100 xp
    Bringing it all together
    50 xp
    Bringing it all together (1)
    100 xp
    Bringing it all together (2)
    100 xp
  3. 3

    Lambda functions and error-handling

    Learn about lambda functions, which allow you to write functions quickly and on the fly. You'll also practice handling errors in your functions, which is an essential skill. Then, apply your new skills to answer data science questions.

    Reproduzir Capítulo Agora
    Lambda functions
    50 xp
    Pop quiz on lambda functions
    50 xp
    Writing a lambda function you already know
    100 xp
    Map() and lambda functions
    100 xp
    Filter() and lambda functions
    100 xp
    Reduce() and lambda functions
    100 xp
    Introduction to error handling
    50 xp
    Pop quiz about errors
    50 xp
    Error handling with try-except
    100 xp
    Error handling by raising an error
    100 xp
    Bringing it all together
    50 xp
    Bringing it all together (1)
    100 xp
    Bringing it all together (2)
    100 xp
    Bringing it all together (3)
    100 xp
    Bringing it all together: testing your error handling skills
    50 xp
    Congratulations!
    50 xp
Para Empresas

GroupTreinar 2 ou mais pessoas?

Obtenha acesso à biblioteca completa do DataCamp, com relatórios, atribuições, projetos e muito mais centralizados

Nas seguintes faixas

Certificação disponível

Cientista de dados associado em Python

Ir para a trilha

Desenvolvedor Python

Ir para a trilha

Fundamentos de Python

Ir para a trilha

Conjuntos De Dados

Tweets

Colaboradores

Collaborator's avatar
Francisco Castro

Pre Requisitos

Intermediate Python
Hugo Bowne-Anderson HeadshotHugo Bowne-Anderson

Data Scientist

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