September 2025
Intermediate to advanced
660 pages
13h 38m
Portuguese (Portugal, Brazil)
Content preview from Introdução ao Python, 3rd Edition
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Capítulo 25. Ciência de dados
Este trabalho foi traduzido com recurso a IA. Agradecemos o teu feedback e comentários: translation-feedback@oreilly.com
É um erro capital teorizar antes de ter dados.
Sherlock Holmes
O mundo é confuso, assim como os dados.1 Boa parte do seu tempo será gasta na limpeza, fusão, divisão e transferência de dados para obter o que você precisa.
O Python se tornou a linguagem de computador mais popular em parte devido à sua adoção por muitos desenvolvedores para lidar com seu nêmesis - os dados. Este capítulo aborda uma ampla gama de tópicos de dados, incluindo estes:
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Organização de dados
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Conversão de formato
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Análise e estatística
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Visualização
Primeiro, discutirei o que você obtém quando abre e sacode a caixa padrão do Python e, em seguida, mergulharei no rico conjunto de ferramentas de terceiros que as pessoas escreveram para domar os dados.
A IA terá de esperar pelo próximo capítulo, mas aposto que ela não previu isso.
Python padrão
Primeiro, vamos dar uma olhada em alguns recursos do Python que ainda não mencionei.
Mencionei sort() e sorted()no Capítulo 8, mas apliquei somente a listas. O módulo operator tem as funções úteisitemgetter()eattrgetter()que podem informar a sort() e sorted()como fazer a classificação.
A função básica itemgetter() retorna um ou mais itens de um iterável - um objeto que permite que você acesse itens com [], como uma lista ou tupla:
>>>fromoperatorimportitemgetter>>>l=['a','b','c','d','e']>>>f=itemgetter ...
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