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Pandas for Everyone: Python Data Analysis (Addison-Wesley Data & Analytics Series)
85% of respondents would recommend this to a friend
MYR 283
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Best Python/Data Science book I've read in years...Daniel's book is a breath of fresh air. He still manages to educate without getting bogged down in the minutia or the overly verbose theory, math, etc. etc.
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What Stands Out
Product Details
| Publisher | Addison-Wesley Professional |
| Publication date | December 20, 2022 |
| Edition | 2nd |
| Language | English |
| Print length | 512 pages |
| ISBN-10 | 0137891156 |
| ISBN-13 | 978-0137891153 |
| Item Weight | 1.75 pounds (790 grams) |
| Dimensions | 7 x 1.16 x 9.12 inches (17.8 x 2.9 x 23.2 cm) |
| Part of series | Addison-Wesley Data & Analytics |
Who Should Buy?
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Beginners in Data
Ideal for novice data analysts looking to learn data handling and analysis using Python's Pandas library.
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Python Enthusiasts
Great for those familiar with Python who want to enhance their data analysis skills with practical examples.
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Data Science Students
Suitable for students studying data science, providing foundational knowledge in data manipulation and analysis techniques.
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Advanced Users
Experienced analysts may find the content too basic and lacking in advanced data manipulation techniques.
Product Description
Pandas for Everyone: Python Data Analysis (Addison-Wesley Data & Analytics Series)
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Pros
- Comprehensive coverage of Pandas
- Clear, concise explanations
- Practical examples and exercises
- User-friendly for beginners
- Updates for latest Python features
Cons
- Occasional typos in examples
Product Price History
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MYR 283
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Features & Benefits
- Manage and automate data analysis with Pandas in Python
- Practical knowledge and insight for solving real problems with Pandas
- Extended coverage of plotting and the seaborn data visualization library
- Updated Python 3.9 code and packages coverage, including statsmodels and scikit-learn libraries
- Online bonus material on geopandas, Dask, and creating interactive graphics with Altair
- Tips on performance, scalability, and the wider Python data analysis ecosystem
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