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
| Publishers | O'Reilly Media |
| Date of publication | 26 August 2022 |
| Prints | 3. |
| Language | English |
| Print Length | 550 pages |
| ISBN-10 | 109810403X |
| ISBN-13 | 978-1098104030 |
| Dimensions | 17.78 x 3.81 x 22.86 cm |
Product Description
Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter
Product Buying Guide
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively.
Product Specifications
- Author: Wes McKinney
- Edition: 3rd
- Language: English
- Pages: Varies
- Publisher: O'Reilly Media
- Release Date: 2022
- Platform: Python
Key Features
- Comprehensive guide to data analysis in Python
- Covers the latest versions of pandas, NumPy, and Jupyter
- Includes practical case studies for hands-on learning
- Ideal for beginners and experienced Python programmers
- Available data files and related material on GitHub
Usage Scenarios
- Data manipulation, processing, cleaning, and crunching in Python
- Exploratory computing with Jupyter notebook and IPython shell
- Basic and advanced features in NumPy
- Data analysis using the pandas library
- Informative visualizations with matplotlib
- Slice, dice, and summarize datasets with pandas groupby
- Analyze and manipulate time series data
- Solve real-world data analysis problems with examples
Some User Review
- The best book for learning data analysis in Python!
- Clear and concise explanations with practical examples
- Great resource for both beginners and experienced programmers
- The updated edition covers all the latest tools and libraries
Competitors
- Moderately priced compared to similar books in the market
- Varies depending on the edition and format
Buying Considerations
- Consider your level of Python programming and data analysis experience
- Evaluate whether the specific topics covered align with your needs
- Check if the book's content remains relevant for the foreseeable future
- Review the availability of related data files and material on GitHub
Conclusion
Python for Data Analysis is the ultimate guide for anyone looking to master data manipulation, processing, and analysis in Python. With the latest updates and practical case studies, this book caters to beginners and experienced Python programmers alike. Whether you're new to Python or already familiar with the language, this book will equip you with the necessary skills to excel in data analysis. Consider your needs and level of experience before making the purchase.
View LessGet the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. Continue Reading
Customer Questions & Answers
-
Question:
Who is the author of this book?
Answer: The author of the book is Wes McKinney, the creator of the Python pandas project. -
Question:
Is this book useful for analysts and programmers new to data science?
Answer: Yes, the book is ideal for analysts new to Python and for Python programmers new to data science and scientific computing. -
Question:
Are there practical examples in the book?
Answer: Yes, the book is packed with practical case studies and real-world examples to demonstrate key concepts.
İngilizce Baskı Wes McKinney Format: Kağıt Kapak Editorial Review
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Pros
- Comprehensive data analysis guide
- Easy-to-follow examples
- Great for beginners and experts
- Covers key Python libraries
- Well-structured and organized
Cons
- Some topics could be more detailed.
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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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