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Python for Data Science: A Hands-On Introduction
88% of respondents would recommend this to a friend
KZT 34754
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Python for Data Science introduces you to the Pythonic world of data analysis with a learn-by-doing approach rooted in practical examples and hands-on activities.
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What Stands Out
Информация о продукте
- Comprehensive guide to using Python for data science
- Covers essential concepts and hands-on techniques
- Provides practical examples and exercises
- Written in a clear and accessible language
- Suitable for beginners and those with prior Python knowledge
- Ideal for individuals and professionals seeking to delve into data science
| Publisher | No Starch Press |
| Publication date | August 2, 2022 |
| Language | English |
| Print length | 240 pages |
| ISBN-10 | 1718502206 |
| ISBN-13 | 978-1718502208 |
| Item Weight | 15.2 ounces (430.92 grams) |
| Dimensions | 7.05 x 0.71 x 9.25 inches (17.9 x 1.8 x 23.5 cm) |
Who Should Buy?
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Beginners in Python
Ideal for newcomers to programming who want to learn Python while focusing on data science applications.
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Data Science Enthusiasts
Perfect for individuals interested in data science who wish to gain practical experience with real-world datasets.
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Professionals Upskilling
Great for professionals looking to enhance their skill set in data analysis and Python programming for career advancement.
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Experienced Programmers
Not suitable for seasoned programmers who may find the content too basic and lacking in advanced topics.
ОПИСАНИЕ ТОВАРА
Python for Data Science: A Hands-On Introduction
Вопросы и ответы клиентов
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вопрос:
What skills will I gain from Python for Data Science A Hands-On Introduction?
отвечать: You will gain essential skills in data manipulation, analysis, and visualization using Python. This course introduces libraries such as Pandas, NumPy, and Matplotlib, allowing you to handle data effectively. It’s beneficial for aspiring data scientists and analysts and can help professionals in various fields leverage data-driven insights to make informed decisions. -
вопрос:
Is this book suitable for beginners in programming?
отвечать: Yes, this book is designed for beginners with no prior programming experience. It starts with the fundamentals of Python programming, gradually introducing data science concepts. This approach allows you to build a strong foundation, making it ideal for those starting their journey into data science. -
вопрос:
What topics are covered in this introduction to data science?
отвечать: The book covers a variety of topics, including basic Python programming, data visualization, exploratory data analysis, and statistical concepts fundamental to data science. Each chapter provides hands-on projects that reinforce these concepts, enabling you to apply your learning in real-world scenarios. -
вопрос:
How practical is the content provided in the book?
отвечать: The content is highly practical, featuring hands-on exercises that help reinforce concepts through application. Real-world datasets are utilized to demonstrate data cleaning, analysis, and visualization techniques, making it an ideal resource for anyone looking to apply data science skills immediately. -
вопрос:
Do I need specific software or tools to follow this book?
отвечать: You will need Python installed on your computer, along with libraries such as Pandas, NumPy, and Matplotlib. The book guides you on how to set up your environment step-by-step. This ensures that you can follow along with the practical exercises and projects effortlessly. -
вопрос:
Can this book help me with data science job interviews?
отвечать: Absolutely, this book covers key concepts and techniques commonly discussed in data science job interviews. By mastering the topics and hands-on projects provided, you will enhance your understanding, giving you an edge during technical interviews and assessments. -
вопрос:
What makes this book different from other data science resources?
отвечать: This book stands out due to its hands-on approach, combining theory with practical exercises. While many resources focus purely on theoretical knowledge, this book helps you apply what you learn, bridging the gap between reading and real-world application, which is essential for becoming proficient in data science. -
вопрос:
How long does it take to complete the book?
отвечать: The completion time varies per individual, but on average, readers can finish the book in several weeks if they dedicate a few hours a week. This pace allows you to absorb the material thoroughly and practice effectively, ensuring you grasp the core concepts of data science. -
вопрос:
What level of mathematical knowledge do I need?
отвечать: Basic knowledge of statistics and algebra is beneficial but not mandatory. The book introduces necessary mathematical concepts in a beginner-friendly manner. You will learn how these concepts apply within Python and data science, making it accessible for those without an extensive math background. -
вопрос:
Where can I buy Python For Data Science A Hands-On Introduction?
отвечать: You can buy 'Python For Data Science A Hands-On Introduction' from Ubuy in Kazakhstan. Ubuy offers a variety of formats, making it easy for you to choose the one that best fits your learning preferences.
Data Mining Editorial Review
Python for Data Science: A Hands-On Introduction offers a mixed experience with an emphasis on practical coding although it presents some challenges. Published by No Starch Press in August 2022, the book spans 240 pages and attempts to guide beginners through Python and data science concepts. Several reviewers highlight the lack of adequate support resources such as practice solutions on GitHub, which can impede the learning process. Additionally, the book’s structure is criticized for abruptly introducing complex coding concepts without sufficient explanation, making it potentially overwhelming for those new to programming. Despite its intention to incorporate statistical techniques, crucial topics like handling real data and common statistical methods are notably absent, leading readers to seek alternative materials for a more thorough understanding.
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Плюсы
- Well-structured for hands-on coding experience
- Publisher has a strong reputation
- Appealing print length for concise learning
- Interesting topics in data science
- Focus on practical applications is beneficial
Минусы
- Missing supplementary materials can hinder understanding
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Особенности и преимущества
- Python is an ideal choice for accessing, manipulating, and gaining insights from data of all kinds.
- Write Python code to obtain, transform, and analyze data, practicing state-of-the-art data processing techniques
- Discover Python’s rich set of built-in data structures for basic operations, as well as its robust ecosystem of open-source libraries for data science
- Load data in various formats, streamline, group, and aggregate data sets, and create charts, maps, and visualizations
- Real-world data applications including Taxi service, market basket analysis, and machine learning to predict stock prices
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