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Item #:
90848749
Python for Data Analysis: A Complete Step By Step From Intermediate to Advanced Guide for Python Coding, NumPy, Pandas for Data Analysis. Improve
Item #:
90848749
€ 21
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Product Details
| Publisher | Independently published |
| Publication date | January 21, 2020 |
| Language | English |
| Print length | 157 pages |
| ISBN-13 | 979-8602150728 |
| Item Weight | 5.7 ounces (161.6 grams) |
| Dimensions | 5 x 0.36 x 8 inches (12.7 x 0.9 x 20.3 cm) |
Product Description
Python for Data Analysis: A Complete Step By Step From Intermediate to Advanced Guide for Python Coding, NumPy, Pandas for Data Analysis. Improve Your Skills Quickly
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Python Editorial Review
The reception of this book appears to be polarized among readers with varying levels of proficiency in Python and data analysis. Many beginners and those seeking a foundational understanding of the language have found the book beneficial, hailing its clear explanations, structured organization, and relevant examples. They appreciate it as a solid introduction, making complex subjects more approachable for novices. Readers who viewed the book solely as an introductory tool generally commend its high-level coverage of fundamental concepts, even if they also note it lacks deep technical detail. Conversely, more advanced users and those seeking practical coding examples have expressed disappointment, describing the book as inadequate for meaningful learning and application in real-life scenarios. Critics argue that it lacks sufficient coding content, providing only snippets rather than robust, instructive examples. The repetitive and simplistic writing style detracts from the overall experience for some, leading to complaints about clarity and coherence. Overall, it has been criticized for not living up to expectations for those searching for comprehensive, in-depth technical guidance. **
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Pros
- Great for beginners looking to learn Python fundamentals.
- Clear explanations of complex concepts.
- Well-structured with a good introduction and coverage of essential topics.
Cons
- Lacks practical coding examples and depth for advanced users.
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