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Practical Data Science Cookbook - Second Edition: Data pre-processing, analysis and visualization using R and Python 2nd Revised edition
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Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data.
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What Stands Out
Product Details
| Publisher | Packt Publishing |
| Publication date | June 29, 2017 |
| Edition | 2nd Revised edition |
| Language | English |
| Print length | 434 pages |
| ISBN-10 | 1787129624 |
| ISBN-13 | 978-1787129627 |
| Item Weight | 1.64 pounds (740 grams) |
| Dimensions | 7.5 x 0.98 x 9.25 inches (19.1 x 2.5 x 23.5 cm) |
Who Should Buy?
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Beginner Data Scientists
Ideal for those new to data science looking for practical guidance on R and Python.
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Data Analysts
Useful for professionals seeking to enhance their data analysis skills with comprehensive recipes and examples.
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Academic Learners
Perfect for students and educators in data science courses needing hands-on projects and exercises.
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Advanced Users
Experienced data scientists may find the content too basic and not challenging enough for advanced techniques.
Product Description
Practical Data Science Cookbook - Second Edition: Data pre-processing, analysis and visualization using R and Python 2nd Revised edition
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Data Modeling & Design Editorial Review
The Practical Data Science Cookbook - Second Edition is a comprehensive guide for anyone looking to learn about data pre-processing, analysis, and visualization using R and Python. The book provides practical examples and step-by-step instructions to help readers gain hands-on experience. From basic concepts to advanced techniques, this cookbook covers a wide range of topics in the field of data science. Whether you are a beginner or an experienced data scientist, this book is a valuable resource to have in your collection.
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Pros
- Comprehensive guide for data pre-processing, analysis, and visualization
- Practical examples and step-by-step instructions
- Covers a wide range of topics in data science
- Suitable for beginners and experienced data scientists
Cons
- Some readers may prefer more in-depth explanations
Product Price History
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Features & Benefits
- Over 85 hands-on recipes for real-world data science projects in R and Python.
- Learn data acquisition, cleaning, analysis, and visualization techniques.
- Ideal for both aspiring data scientists and experienced professionals.
- Easy-to-follow guidance to help you implement numerical computing concepts.
- Gain a competitive advantage by mastering data science skills.
- Understand the structure of real-world data science projects.
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