April 2025
Intermediate to advanced
582 pages
13h 33m
Portuguese (Portugal, Brazil)
Content preview from Python para Análise de Dados, 3ª EdiçãoBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Capítulo 5. Começa a utilizar o pandas
Este trabalho foi traduzido com recurso a IA. Agradecemos o teu feedback e comentários: translation-feedback@oreilly.com
O pandas será uma ferramenta de grande interessedurante grande parte do resto do livro. Contém estruturas de dados e ferramentas de manipulação de dados concebidas para tornar a limpeza e a análise de dados rápidas e convenientes em Python. O pandas é frequentemente utilizado em conjunto com ferramentas de computação numérica como o NumPy e o SciPy, bibliotecas analíticas como o statsmodels e o scikit-learn e bibliotecas de visualização de dados como o matplotlib. O pandas adopta partes significativas do estilo idiomático do NumPy de computação baseada em matrizes, especialmente funções baseadas em matrizes e uma preferência pelo processamento de dados sem for loops.
Embora o pandas adopte muitas expressões de codificação do NumPy, a maior diferença é que o pandas foi concebido para trabalhar com dados tabulares ou heterogéneos. O NumPy, pelo contrário, é mais adequado para trabalhar com dados de matriz numérica homogeneamente tipados.
Desde que se tornou um projeto de código aberto em 2010, o pandas amadureceu e se tornou uma biblioteca bastante grande que é aplicável em um amplo conjunto de casos de uso no mundo real. A comunidade de programadores cresceu para mais de 2.500 colaboradores distintos, que têm ajudado a construir o projeto à medida que o utilizam para resolver os seus problemas diários de dados. As vibrantes comunidades ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.