Pythonによるあたらしいデータ分析の教科書 第3版 AI & TECHNOLOGY Tankobon Softcover – May 21, 2025
86% of respondents would recommend this to a friend
MOP 249
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A must-have for data analysis engineers to acquire basic knowledge in the shortest possible time.
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產品詳情
| Publisher | u7fd4u6cf3u793e |
| Publication date | May 21, 2025 |
| Language | Japanese |
| Print length | 344 pages |
| ISBN-10 | 4798191027 |
| ISBN-13 | 978-4798191027 |
| Item Weight | 430 g |
| Dimensions | 8.27 x 5.83 x 0.71 inches (21 x 14.8 x 1.8 cm) |
Who Should Buy?
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Students
Ideal for university students studying data analysis and seeking practical Python applications to enhance their learning.
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Aspiring Analysts
Beginners aiming to enter data analysis should find comprehensive insights and examples crucial for understanding Python usage.
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Educators
Instructors looking for a structured curriculum resource that combines theory with hands-on coding examples will benefit significantly.
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Advanced Users
Data professionals with extensive knowledge may not find advanced topics or insights they require within this textbook.
產品敘述
Pythonによるあたらしいデータ分析の教科書 第3版 AI & TECHNOLOGY Tankobon Softcover – May 21, 2025
客戶問題與解答
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題:
What is the target audience for this book?
回答: The book is aimed at those who aspire to become data analysis engineers. -
題:
What programming language does this edition focus on?
回答: This third edition focuses on Python, specifically version 3.13. -
題:
Will this book help me prepare for the Python data analysis exam?
回答: Yes, it is specified as the main teaching material for the Python data analysis exam.
寺田 学 , 辻 真吾 , 鈴木 たかのり Editorial Review
**** The third edition of "Pythonによるあたらしいデータ分析の教科書" is a comprehensive resource for anyone eager to dive into data analysis using Python. The book effectively guides readers from fundamental mathematical concepts necessary for data analysis all the way through practical applications employing popular libraries such as NumPy, pandas, Matplotlib, and scikit-learn. Reviewers appreciate its structured approach, which gradually increases in complexity, allowing readers to build understanding step-by-step. The practical focus, illustrated through numerous concise code examples, makes this textbook an excellent choice for those curious about practical data analysis as well as seasoned programmers looking to enhance their skills. Readers note that the book succinctly encapsulates the entire process of data analysis, from data collection to preprocessing, visualization, and machine learning. While the book is filled with valuable content, some users have pointed out that certain specialized terms could benefit from more comprehensive explanations. As a result, beginners might find it helpful to supplement their learning with additional resources. Despite this, the overall impression is that this text is a solid foundation for anyone serious about learning data analysis through Python, and highly recommended for both novice and experienced users alike. **
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優點
- Comprehensive coverage of data analysis using Python.
- Structured content that increases in difficulty, promoting gradual learning.
- Numerous practical examples of code, enhancing hands-on learning.
- Well-suited for a wide audience, from beginners to experienced programmers.
缺點
- Some explanations of specialized terms may be overly simplistic for beginners.
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MOP 249
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特色和優勢
- Third edition compatible with Python 3.13 and latest libraries.
- Essential for aspiring data analysis engineers.
- Covers data acquisition, processing, visualization, and machine learning.
- Explains basic Python grammar and data formats.
- Includes sample exercises for practical understanding.
- Main teaching material for the Python data analysis exam.
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