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제품번호 #:
67758848
Python Data Science Handbook: Essential Tools for Working with Data (Paperback)
제품번호 #:
67758848
KRW 93166
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Quite simply, this is the must-have reference for scientific computing in Python.
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What Stands Out
Comprehensive Guide
Offers an extensive overview of essential tools, techniques, and methodologies that empower users to work effectively with data in Python, catering to both beginners and seasoned data scientists.
Practical Examples
Includes hands-on examples and real-world applications, allowing readers to apply theoretical knowledge to practical scenarios, enhancing learning and retention of data science concepts.
Accessible Format
Presented in an easy-to-understand paperback format, making it ideal for on-the-go learning and referencing, ensuring that vital data science tools remain at readers' fingertips.
제품 세부 정보
- 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 |
| Edition | 2nd Edition |
| Publisher | O'Reilly Media |
| Original languages | English |
| Language | English |
| Is collectible | N |
| Assembled product height | 9.2 in (23.4 cm) |
| Assembled product weight | 2.15 lb (980 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.
-
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.
-
Complete Beginners
May overwhelm those with no programming background, as it assumes a basic understanding of Python and programming concepts.
-
Advanced Practitioners
Experienced data scientists may find the content too basic and lacking advanced topics or in-depth discussions.
-
Non-Technical Roles
Professionals in non-technical fields may struggle to relate the technical content to their day-to-day responsibilities.
제품 설명
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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고객 질문 및 답변
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의문:
What is included in the Python Data Science Handbook?
답변: The handbook includes essential tools like IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. -
의문:
Who is this book suitable for?
답변: It's suitable for researchers, scientists, and data enthusiasts who are already familiar with Python coding. -
의문:
How can this book help me in my data projects?
답변: It provides guidance on data manipulation, visualization, and building machine learning models effectively.
Jake Vanderplas All Books Editorial Review
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장점
- Comprehensive data science guide
- Clear and easy-to-understand examples
- Covers essential tools thoroughly
- Great for beginners and experts
- Well-organized for quick reference
단점
- Some examples may feel slightly outdated.
Product Price History
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KRW 93166
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특징 및 장점
- 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.