Curso de Pandas (ETL) - Manipulando dados com Python

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Go to Course: https://www.udemy.com/course/curso-de-pandas-etl-python/

Introduction

Certainly! Here's a comprehensive review and recommendation for the Coursera course "Curso de Pandas (ETL) - Manipulando dados com Python": --- **Course Review: Curso de Pandas (ETL) - Manipulando dados com Python** If you're looking to dive into data manipulation using Python, the "Curso de Pandas (ETL) - Manipulando dados com Python" offers a thorough and practical introduction to the widely-used Pandas library. This course is designed for beginners and intermediate learners who want to develop hands-on skills in data analysis, cleaning, and transformation. **Overview & Content** This course provides a step-by-step approach to mastering data handling with Pandas. It covers essential topics such as importing data from CSV files, analyzing data structures, performing statistical analysis, and manipulating datasets through adding, updating, and deleting data. The course also explores advanced techniques like filtering data with loc and iloc, generating visualizations, and saving manipulated data in various formats. A distinctive feature of this course is its focus on practical exercises—each lesson is accompanied by exercises and solutions in video format, ensuring learners can actively apply what they've learned. It also emphasizes real-world applications by teaching how to access APIs, connect to databases, and handle data with complex commands like apply. **Teaching Methodology** Created based on the methodology of Harve School, a renowned institution in technology training, the course prioritizes clear, scripted videos that facilitate learning. This approach makes complex topics accessible and helps build confidence in handling large datasets from multiple sources. **Who Should Enroll?** - Aspiring data analysts and data scientists - Developers seeking to enhance data manipulation skills - Professionals who want to learn how to integrate data from different sources (APIs, databases) - Anyone interested in data cleaning, analysis, and visualization with Python **Pros:** - Practical, hands-on learning with exercises and solutions - Coverage of a wide range of data manipulation techniques - Focus on real-world applications, including API and database integration - Clear, structured lessons suitable for beginners and intermediate learners **Cons:** - The syllabus is not explicitly listed, so learners may need to explore the course content to understand the depth of each topic - No mention of advanced topics like machine learning or statistical modeling, which could be a future addition for advanced learners --- **Recommendation** Overall, the "Curso de Pandas (ETL) - Manipulando dados com Python" is highly recommended for anyone looking to build a solid foundation in data manipulation with Python. Its emphasis on practical exercises, real-world data handling, and comprehensive coverage make it an excellent choice for beginners and intermediate learners aiming to become proficient in data analysis and ETL processes. If you are eager to learn how to manage data from various sources, analyze it effectively, and prepare it for reporting or further analysis, this course will equip you with the necessary skills to succeed. --- **Ready to start? Don't hesitate—enroll today and take the first step toward mastering data manipulation with Pandas!**

Overview

Aprenda a manipular dados com python com essa fantástica biblioteca. Nesse curso, você irá acompanhar o passo a passo para um processo completo de análise de dados usando o Pandas.Todos os vídeos são roteirizados onde cada aula possui exercício prático e resposta, também em vídeo. As aulas são criadas com base na metodologia da escola Harve, que hoje é referência na formação de profissionais para a área de tecnologia.Nesse curso, você irá navegar pelos seguintes tópicos:Importar biblioteca e carregar arquivos csv.Analisar informações da estrutura de dados gerada.Analisar informações do conteúdo utilizando funções de estatística.Manipular adição, atualização e exclusão de dados dos conjuntos de dados.Realizar filtros com comandos fáceis através do loc e do iloc.Gerar gráficos a partir do próprio conjunto de dados.Salvar arquivos após a manipulação dos dados.Criar colunas a partir de outras colunas.Acessar apis e carregar os dados em um dataframe.Acessar banco de dados e carregar os dados em um dataframe.Tratar dados usando comandos complexos como apply.Montar strings de conexão para apis e banco de dados.Com esse curso você será capaz de carregar dados de diversas fontes diferentes, tratar e disponibilizar em vários formatos. O que está esperando? Vamos começar.

Skills

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