Learn the fundamentals of data science with Python by analyzing real datasets and solving problems using pandas
Key Features:
Book description:
The Pandas Workshop will teach you how to be more productive with data and generate real business insights to inform your decision-making. You will be guided through real-world data science problems and shown how to apply key techniques in the context of realistic examples and exercises. Engaging activities will then challenge you to apply your new skills in a way that prepares you for real data science projects.
You'll see how experienced data scientists tackle a wide range of problems using data analysis with pandas. Unlike other Python books, which focus on theory and spend too long on dry, technical explanations, this workshop is designed to quickly get you to write clean code and build your understanding through hands-on practice. As you work through this Python pandas book, you'll tackle various real-world scenarios, such as using an air quality dataset to understand the pattern of nitrogen dioxide emissions in a city, as well as analyzing transportation data to improve bus transportation services.
By the end of this data analytics book, you'll have the knowledge, skills, and confidence you need to solve your own challenging data science problems with pandas.
What You Will Learn:
Who this book is for:
This data analysis book is for anyone with prior experience working with the Python programming language who wants to learn the fundamentals of data analysis with pandas. Previous knowledge of pandas is not necessary.
"Sinopsis" puede pertenecer a otra edición de este libro.
Blaine Bateman has more than 35 years of experience working with various industries from government R&D to startups to $1B public companies. His experience focuses on analytics including machine learning and forecasting. His hands-on abilities include Python and R coding, Keras/Tensorflow, and AWS & Azure machine learning services. As a machine learning consultant, he has developed and deployed actual ML models in industry.
Saikat Basak is a data scientist and a passionate programmer. Having worked with multiple industry leaders, he has a good understanding of problem areas that can potentially be solved using data. Apart from being a data guy, he is also a science geek and loves to explore new ideas in the frontiers of science and technology.
Thomas V. Joseph is a data science practitioner, researcher, trainer, mentor, and writer with more than 19 years of experience. He has extensive experience in solving business problems using machine learning toolsets across multiple industry segments.
"Sobre este título" puede pertenecer a otra edición de este libro.
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