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Item #:
4566825
Python Data Science Handbook: Essential Tools for Working with Data
89% of respondents would recommend this to a friend
Item #:
4566825
CAD 116
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What Stands Out
Comprehensive Guide
Covers essential data science tools like NumPy, Pandas, Matplotlib, and Scikit-Learn, providing a thorough understanding for beginners and advanced users alike.
Practical Examples
Includes real-world data analysis examples, enabling readers to apply concepts directly to solve problems and enhance their data manipulation skills efficiently.
Clear Explanations
Offers clear and concise explanations of complex topics, making them accessible for readers with varying levels of expertise, ensuring a smoother learning curve.
Product Details
- 1st Edition of the Python Data Science Handbook
- Provides essential tools for working with data in Python
- Published by O'Reilly, a renowned brand in sharing expert knowledge
- O'Reilly has over 40 years of experience in inspiring and educating companies and individuals
- Aims to provide the skills and understanding necessary for success in data science
- Supports customers in building innovations that drive the world forward
| Package Weight | 2.0 Pound |
Who Should Buy?
-
Data Science Beginners
Ideal for newcomers to data science looking for a practical guide to Python libraries and data manipulation techniques.
-
Students in Academia
Great resource for university students studying data analysis or machine learning, providing structured examples and exercises.
-
Professional Analysts
Beneficial for data analysts needing to sharpen their Python skills and improve data visualization and analysis techniques.
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Complete Programming Newbies
Not suitable for those without any programming knowledge, as the concepts may be too advanced without preliminary understanding.
Product Description
Python Data Science Handbook: Essential Tools for Working with Data
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Product Buying Guide
The Python Data Science Handbook is an essential resource for researchers and data scientists who work with Python. This comprehensive desk reference provides tools for storing, manipulating, and gaining insights from data. It covers popular libraries such as IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. Whether you need to manipulate and clean data, visualize different types of data, or build statistical and machine learning models, this handbook has got you covered.
Product Specifications
- Author: Not mentioned
- Edition: 1st
- Language: English
- Number of Pages: Not mentioned
- Publisher: O'Reilly Media
- Publication Date: Not mentioned
Key Features
- Comprehensive desk reference for Python data science
- Covers essential tools like IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn
- Ideal for manipulating, transforming, and cleaning data
- Provides insights on visualizing different types of data
- Helps build statistical and machine learning models
Usage Scenarios
- Manipulating, transforming, and cleaning data
- Visualizing different types of data
- Building statistical and machine learning models
Usage Scenarios
- Python for Data Analysis
- Data Science for Business
Some User Review
- This book is a life-saver for anyone working with data in Python. It covers all the essential tools and provides practical examples. Highly recommended!
- I found the explanations in this handbook very clear and easy to follow. It has become my go-to reference for all my data science projects.
- The examples and code snippets in this book are extremely helpful. It's a great resource for both beginners and experienced data scientists.
Competitors
- The price of the Python Data Science Handbook may vary depending on the vendor and edition. However, considering its comprehensive coverage and value as a desk reference, it offers great value for money.
- Compared to its competitors, the Python Data Science Handbook offers a wider range of tools and comprehensive coverage. Its price is justified by the depth of knowledge it provides.
Buying Considerations
- Consider your level of experience with Python and data science. This book is suitable for both beginners and experienced practitioners.
- If you already own similar books like 'Python for Data Analysis' or 'Data Science for Business', evaluate the additional value the Python Data Science Handbook brings to your collection.
- Check for any updated editions or newer releases to ensure you have the most up-to-date information and features.
Conclusion
The Python Data Science Handbook is a must-have reference for anyone working with data in Python. Its comprehensive coverage of essential tools and practical examples make it invaluable for manipulating, visualizing, and modeling data. Whether you are a beginner or an experienced data scientist, this handbook will enhance your skills and knowledge.
View LessThe Python Data Science Handbook is an essential resource for researchers and data scientists who work with Python. This comprehensive desk reference provides tools for storing, manipulating, and gaining insights from data. It covers popular libraries such as IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. Whether you need to manipulate and clean data, visualize different types of data, or build statistical and machine learning models, this handbook has got you covered. Continue Reading
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Python Editorial Review
The Python Data Science Handbook offers essential tools for working with data, but falls short in terms of clarity and organization. The lack of clear explanations and syntax explanations make it difficult for readers to follow along. The book is best suited as a reference for experienced individuals, rather than beginners. Additionally, the physical quality of the book is subpar, as it quickly falls apart and has black and white visualizations. Overall, the book has some useful content but is not recommended for those seeking a comprehensive and beginner-friendly guide to data science.
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Pros
- Contains essential tools for working with data
- Uses Jupyter for readability
- Useful for accessing and understanding basic Python functions and libraries
Cons
- Lacks clear explanations and syntax explanations
Product Price History
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CAD 116
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Features & Benefits
- Ideal for working scientists and data crunchers
- Comprehensive desk reference for day-to-day data issues
- Learn to manipulate, transform, clean and visualize data
- Must-have reference for scientific computing in Python
- Includes key data science libraries - IPython, NumPy, Pandas, Matplotlib, Scikit-Learn
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