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Item #:
183728678
Python Data Science Handbook: Essential Tools for Working with Data
87% of respondents would recommend this to a friend
Item #:
183728678
€ 72
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Python Data Science Handbook is the must-have reference for scientific computing in Python.
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What Stands Out
Comprehensive Resource
This handbook provides an extensive overview of essential tools and techniques for data science, making it an invaluable resource for both beginners and experienced practitioners in the field.
Hands-on Examples
Includes practical examples and case studies that reinforce learning, allowing readers to apply concepts effectively and improve their data manipulation skills in real-world scenarios.
Accessible Format
Structured in an easy-to-follow format, this handbook enables quick reference and learning, catering to diverse learning styles and aiding readers in mastering data science concepts efficiently.
Product Details
- Python Data Science Handbook: Essential Tools for Working with Data 2nd Edition
- Comprehensive desk reference for scientists and data crunchers working with Python
- Covers IPython, NumPy, pandas, Matplotlib, Scikit-Learn, and other related tools
- Manipulate, transform, and clean data
- Visualize different types of data
- Build statistical or machine learning models
| Publisher | O'Reilly Media |
| Publication date | 31 Dec. 2022 |
| Edition | 2nd |
| Language | English |
| Print length | 550 pages |
| ISBN-10 | 1098121228 |
| ISBN-13 | 978-1098121228 |
| Item weight | 1.05 kg |
| Dimensions | 17.53 x 3.3 x 23.11 cm |
Who Should Buy?
-
Data Scientists
Ideal for data scientists looking to enhance their skills in Python libraries for data analysis and visualization.
-
Students
Great resource for students pursuing courses in data science or statistical analysis, providing foundational tools and concepts.
-
Analysts
Useful for data analysts needing practical insights on data manipulation, exploration, and statistical methods using Python.
-
Complete Beginners
Not suitable for individuals without any programming background, as it assumes prior knowledge of Python and data concepts.
Product Description
Python Data Science Handbook: Essential Tools for Working with Data
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AI & Machine Learning Editorial Review
Python Data Science Handbook Essential Tools For Working With Data is an essential resource for anyone venturing into the field of data science. Published by O'Reilly Media, this second edition spans 550 pages and covers vital tools for data handling, manipulation, and analysis in Python, making it an invaluable reference for both beginners and experienced practitioners. The book's comprehensive nature and clear explanations foster a deep understanding of complex topics, helping readers develop practical skills. Furthermore, users appreciate its organized structure which facilitates easy navigation between concepts. This handbook is highly recommended for its clarity and thorough approach to data science.
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Pros
- Comprehensive coverage of data science tools
- Clear explanations and structured format
- Suitable for both beginners and experienced users
- Updated with the latest techniques
- Published by a reputable publisher
Cons
- Might feel overwhelming for complete beginners
Product Price History
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Features & Benefits
- Python is a first-class tool for researchers because of its libraries for storing, manipulating, and gaining insight from data.
- The second edition of this comprehensive desk reference is ideal for manipulating, transforming, cleaning data, visualizing different types of data, and using data to build statistical or machine learning models.
- The handbook covers all essential tools for working with data, including IPython, NumPy, Pandas, Matplotlib, and Scikit-learn.
- 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, while Matplotlib includes capabilities for a flexible range of data visualizations.
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