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- Learning Data Science: Data Wrangling, Explor...
Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python
XAF 44633
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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
Bayanin samfur
- 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 1.25 x 9.25 inches (17.8 x 3.2 x 23.5 cm) |
Who Should Buy?
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Aspiring Data Scientists
Perfect for beginners looking to understand core data science principles using Python through hands-on projects and examples.
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Students and Academics
Ideal for students studying data analytics or data science who require structured learning and practical applications.
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Professionals Transitioning Careers
Beneficial for professionals seeking to shift into data-focused roles needing foundational knowledge in data manipulation and analysis.
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Complete Beginners
Not suitable for those with no prior programming experience as it assumes basic knowledge of Python.
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Advanced Data Practitioners
Less beneficial for experienced data scientists looking for in-depth techniques or niche specializations beyond foundational concepts.
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Non-technical Users
Not recommended for individuals without technical skills or interest in programming, as content is code-centric and analytical.
KWATANCEN ABUN
Tambayoyi & Amsoshi na Abokan Ciniki
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Tambaya:
Do I need prior programming experience to benefit from this book?
Amsa: A basic knowledge of Python programming is recommended but not mandatory. -
Tambaya:
What kind of tools will I learn to use in this book?
Amsa: You will learn to use industry-standard tools such as pandas for data analysis. -
Tambaya:
Is this book suitable for someone working in a non-technical role?
Amsa: Yes, it is designed for both aspiring data scientists and those in non-technical roles looking to understand data science.
Python Editorial Review
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XAF 44633
Yi Oda yanzu, a samu nan da Asabar, Agusta 01
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Fasaloli & Fa'idoji
- 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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