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Item #:
101849341
Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python
Item #:
101849341
XAF 44629
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Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass the entire data science lifecycle.
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What Stands Out
Comprehensive Coverage
This book provides an all-in-one approach to data science, encompassing essential skills from data wrangling to modeling, making it ideal for beginners and intermediate learners seeking a thorough understanding.
Practical Python Focus
With a strong emphasis on Python, the book equips readers with practical coding examples and exercises, empowering them to apply data science concepts effectively in real-world scenarios.
Visualization Techniques
It expertly covers visualization methods, enabling readers to present data insights clearly and effectively, which is crucial for decision-making in any data-driven field.
Product Details
- As an aspiring data scientist, you appreciate why organizations rely on data for important decisions—whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the technical/nontechnical divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas. Refine a question of interest to one that can be studied with data Pursue data collection that may involve text processing, web scraping, etc. Glean valuable insights about data through data cleaning, exploration, and visualization Learn how to use modeling to describe the data Generalize findings beyond the data
| Publisher | O'Reilly Media |
| Publication date | October 24, 2023 |
| Edition | 1st |
| Language | English |
| Print length | 594 pages |
| ISBN-10 | 1098113004 |
| ISBN-13 | 978-1098113001 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7 x 1.2 x 9.19 inches (17.8 x 3 x 23.3 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Perfect for beginners looking to understand core data science principles using Python through hands-on projects and examples.
-
Students and Academics
Ideal for students studying data analytics or data science who require structured learning and practical applications.
-
Professionals Transitioning Careers
Beneficial for professionals seeking to shift into data-focused roles needing foundational knowledge in data manipulation and analysis.
-
Complete Beginners
Not suitable for those with no prior programming experience as it assumes basic knowledge of Python.
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Data Mining Editorial Review
Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python offers a comprehensive approach for those seeking to deepen their understanding of data science. This 1st edition, published by O'Reilly Media with a 594-page print length, covers essential topics from data wrangling to visualization. Readers can look forward to a structured learning path that emphasizes real-world applications. The book is written in English and features a well-organized layout, making it accessible for learners of varying expertise. Its detailed examples are particularly appreciated by readers, who find the hands-on approach greatly beneficial for practical understanding.
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Pros
- Comprehensive guide for aspiring data scientists
- Focus on practical applications enhances learning
- Well-structured content for varied expertise
- Covers essential topics in data science
- Detailed examples aid practical understanding
Cons
- It's a lengthy read, may require time to complete
Product Price History
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Features & Benefits
- Master data science skills to transform raw data into actionable insights.
- Learn programming and statistics foundational skills essential for data scientists.
- Ideal for aspiring data scientists and data analysts seeking to bridge technical gaps.
- Gain proficiency in industry-standard tools like pandas for data manipulation.
- Explore data collection techniques including text processing and web scraping.
- Visualize and model data to draw generalized conclusions and insights.
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