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Python Data Science Handbook: Essential Tools for Working with Data, (Paperback)
MKD 3680
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Quite simply, this is the must-have reference for scientific computing in Python.
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- Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all--IPython, NumPy, pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you'll learn how: IPython and Jupyter provide computational environments for scientists using Python NumPy includes the ndarray for efficient storage and manipulation of dense data arrays Pandas contains the DataFrame for efficient storage and manipulation of labeled/columnar data Matplotlib includes capabilities for a flexible range of data visualizations Scikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms
| Book format | Paperback |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | January, 2023 |
| Pages | 588 |
| Reading level | General |
| Subgenre | Languages |
| Series title | No Series |
| Edition | 2nd Edition |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 6.90 x 1.30 x 9.10 in (17.5 x 3.3 x 23.1 cm) |
| Assembled product weight | 2.1 lb (950 grams) |
| Bisac subject heading | Computers |
Who Should Buy?
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Aspiring Data Scientists
Ideal for beginners entering data science, providing foundational knowledge and practical tools for data analysis.
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Analysts and Statisticians
Useful for professionals looking to enhance data handling skills with Python and learn advanced analytical techniques.
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Educators and Trainers
Perfect resource for teaching data science concepts, offering clear explanations and coding examples for classroom use.
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Complete Beginners
May overwhelm those with no programming background, as it assumes a basic understanding of Python and programming concepts.
Product Description
About This Item
The Python Data Science Handbook: Essential Tools for Working with Data, 2nd Edition, is a must-have resource for anyone engaged in data science and analysis. This comprehensive handbook provides a practical guide to using Python to analyze and visualize data, making it an essential tool for professionals, students, and enthusiasts alike. With the exponential growth of data in recent years, it is imperative to have the right tools and skills to make sense of this information. Python has become the go-to programming language for data science, and this handbook is your ultimate companion on this exciting journey. Whether you are a beginner or an experienced data scientist, this paperback edition offers a wealth of knowledge and practical examples to help you master Python's data science capabilities.
From manipulating and cleaning data to exploring and visualizing it, this handbook covers all essential aspects of data science. With Python Data Science Handbook, you will learn how to use Python libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn, which are widely used in the field. These libraries provide powerful tools for data manipulation, analysis, and modeling, allowing you to perform complex operations with ease. Additionally, this handbook covers key concepts in data science, including statistical analysis, machine learning, and data visualization. You will learn how to build and evaluate machine learning models, perform advanced statistical tests, and create insightful visualizations to communicate your findings effectively. Whether you are studying data science, transitioning to a career in the field, or simply looking to enhance your analytical skills, the Python Data Science Handbook provides the knowledge and techniques you need to succeed.
Explore the endless possibilities of Python for data science and unlock the full potential of your data. Get your hands on the Python Data Science Handbook: Essential Tools for Working with Data, 2nd Edition, and take your data analysis skills to new heights. Start your journey into the world of data science today.
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Jake Vanderplas All Books Editorial Review
Python Data Science Handbook: Essential Tools for Working with Data, (Paperback) is a comprehensive guide published by O'Reilly Media in January 2023. With 588 pages, this non-fiction book serves as an essential resource for anyone interested in the field of data science. It's formatted as a paperback, making it accessible and easy to read. The handbook covers vital tools necessary for effectively working with data. Readers appreciate its clarity and detailed examples, which enhance the learning experience. This 2nd edition remains relevant, ensuring readers have the most up-to-date information in a rapidly evolving field.
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Pros
- Comprehensive guide for data science tools
- Clear and detailed examples enhance learning
- Great for readers at all skill levels
- Well-structured and organized content
- Published by a reputable source
Cons
- No digital version available for e-readers
Product Price History
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MKD 3680
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Features & Benefits
- Comprehensive guide to essential Python libraries for data science.
- Ideal for scientists and data professionals familiar with Python.
- Covers tools like IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn.
- Perfect for daily tasks in data manipulation, cleaning, and visualization.
- Learn to build statistical and machine learning models effectively.
- Updated edition offers all-in-one resource for data science enthusiasts.
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