Pandas Basics (eBook)
215 Seiten
Packt Publishing (Verlag)
978-1-83664-540-5 (ISBN)
This book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher.
Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly.
By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.
Learn to master data analysis with Pandas, covering Python basics to advanced techniques, including data cleaning, preprocessing, and visualization.Key FeaturesComprehensive coverage of Python basics and PandasPractical examples and code samples for hands-on learningDetailed sections on data preprocessing, statistical concepts, and data visualizationBook DescriptionThis book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher. Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly. By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.What you will learnLearn to install and configure Python and PandasPerform data preprocessing and cleaning tasksUnderstand statistical concepts and their applicationCreate data visualizations with Matplotlib and SeabornHandle missing data and outliers effectivelyUtilize Pandas for advanced data manipulationWho this book is forThe ideal audience for this book is software developers with a solid background in programming, specifically in Python. Complete beginners might not find this book very helpful. Readers should have a basic understanding of programming concepts.]]>
| Erscheint lt. Verlag | 8.8.2024 |
|---|---|
| Sprache | englisch |
| Themenwelt | Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge |
| ISBN-10 | 1-83664-540-6 / 1836645406 |
| ISBN-13 | 978-1-83664-540-5 / 9781836645405 |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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