Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter vs Data Science from Scratch: First Principles with Python
Overall winner: Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter
Key Differences
Wes McKinney's book (A) focuses on practical data manipulation with pandas, NumPy and Jupyter and has a higher average rating (4.60 from 444 reviews), making it better for hands‑on data wrangling. Joel Grus's book (B) is a more concise, first‑principles introduction to data science and is positioned in a lower price tier with more reviews (4.40 from 759 reviews), suitable for beginners seeking a general overview
Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter
A practical guide to manipulating data with Python using pandas, NumPy, and Jupyter. Clear, approachable explanations with real-world examples; customers appreciate the information quality but note mixed opinions on exercises
Pros
- clear, approachable explanations
- covers pandas and NumPy data manipulation
- real-world examples
- information quality praised by customers
Cons
- mixed feedback on learning material
- some say lack of end-of-chapter exercises
- color accuracy criticized for being black and white
Data Science from Scratch: First Principles with Python
Introductory data science book covering foundational concepts with Python. Helpful for starting your data science journey, with concise explanations. Customer note: clear content but mixed views on code examples
Pros
- clear content
- good for starting data science
- concise introduction
- value for money
Cons
- mixed feedback on code examples
- mixed readability/pacing
- lacks coverage of widely used Python libraries
Head-to-Head
| Criteria | Winner |
|---|---|
| Price | Joel Grus |
| Durability | Tie |
| Versatility | Wes McKinney |
| User Reviews | Wes McKinney |