Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter
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Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python.
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Product Details
- Definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python
- Updated for Python 3.10 and pandas 1.4
- Packed with practical case studies for effective data analysis
- Written by Wes McKinney, creator of the Python pandas project
- Ideal for analysts new to Python and programmers new to data science
- Includes data files and related material on GitHub
| Yayu0131ncu0131 | O'Reilly Media |
| Yayu0131nlanma Tarihi | 26 Au011fustos 2022 |
| Basku0131 | 3. |
| Dil | u0130ngilizce |
| Basku0131 Uzunluu011fu | 550 sayfa |
| ISBN-10 | 109810403X |
| ISBN-13 | 978-1098104030 |
| Boyutlar | 17.78 x 3.81 x 22.86 cm |
| Country of Origin | This item will be imported from TR |
| Date First Available | October 11, 2024 |
| What is in the box | Python for Data Analysis... For more details, please check description/product details |
Who Should Buy?
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Data Analysts
Perfect for data analysts looking to enhance their data manipulation skills using pandas and NumPy efficiently.
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Students and Learners
An ideal resource for students wanting hands-on experience in data science concepts and practical applications.
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Professionals Transitioning
Great for professionals transitioning into data science who want to learn data wrangling techniques with real-world examples.
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Beginner Programmers
Not suitable for absolute beginners with no programming knowledge, as it assumes familiarity with Python concepts.
Product Description
Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter
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İngilizce Baskı Wes McKinney Format: Kağıt Kapak Editorial Review
Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter is a comprehensive guide published by O'Reilly Media on August 26, 2022. This third edition offers an in-depth exploration of data analysis using Python, with a focus on practical examples and detailed insights into libraries like pandas and NumPy. As readers engage with its 550 pages, they will find essential techniques for data wrangling and analysis, crafted to enhance their programming skills and analytical thinking. This book serves as a robust resource for both beginners and experienced programmers looking to refine their data handling techniques using Jupyter notebooks.
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Pros
- Comprehensive coverage of data analysis topics
- Practical examples enhance learning experience
- Well-structured for both beginners and experts
- Focus on popular libraries like pandas and NumPy
- Easy-to-follow formatting and explanations
Cons
- Some concepts may require prior programming knowledge.
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BTN 10408
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Features & Benefits
- Practical guide for solving data analysis problems in Python with latest versions of pandas, NumPy, and Jupyter
- Ideal for analysts new to Python and for Python programmers new to data science and scientific computing
- Includes practical case studies and real-world examples to demonstrate key concepts
- Learn how to manipulate, process, clean, and crunch datasets with flexible tools
- Create informative visualizations with matplotlib and analyze time series data
- Data files and related material available on GitHub
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