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177626428
Python for Data Analysis 3e: Data Wrangling with pandas, NumPy, and Jupyter
89% of respondents would recommend this to a friend
Item #:
177626428
MYR 547
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Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python.
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What Stands Out
Comprehensive Content
This book covers extensive data analysis techniques using popular libraries like pandas and NumPy, making it ideal for data enthusiasts looking to enhance their skills in data wrangling.
Practical Examples
Filled with real-world examples, it enables readers to grasp complex concepts and apply data analysis effectively, addressing common challenges faced by data professionals.
User-Friendly Approach
Designed for both beginners and experienced users, the integration with Jupyter enhances interactivity, ensuring readers can easily follow along and apply techniques in their projects.
Maklumat produk
- 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
| Yayıncı | O'Reilly Media |
| Yayınlanma Tarihi | 26 Ağustos 2022 |
| Baskı | 3. |
| Dil | İngilizce |
| Baskı Uzunluğu | 550 sayfa |
| ISBN-10 | 109810403X |
| ISBN-13 | 978-1098104030 |
| Boyutlar | 17.78 x 3.81 x 22.86 cm |
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Ulas Produk Ini
Kongsikan pandangan anda dengan pelanggan lain
Kebaikan
- Comprehensive data analysis guide
- Easy-to-follow examples
- Great for beginners and experts
- Covers key Python libraries
- Well-structured and organized
Keburukan
- Some topics could be more detailed.
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MYR 547
Pesan sekarang dan dapatkannya lebih kurang pada Khamis, November 12
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- 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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