Python Data Science Handbook 2nd Edition by Jake VanderPlas (Author)
- Publisher: COMPUTER SCIENCE
- Availability: In Stock
- SKU: 56529
- Number of Pages: 588
Rs.1,360.00
Rs.1,995.00
Tags: 2nd edition , advanced Python data science , applied Python machine learning , best book for Python data science , best books , Best Price , Best Selling Books , data analysis in Python , data science textbook , Essential Tools for Working with Data , Jake VanderPlas , Jupyter notebook guide , machine learning with Python , Matplotlib tutorial , NumPy guide , Online Bookshop , Pandas guide , Python algorithms for data science , Python applied data science , Python applied statistics , Python beginner data science , Python coding for data science , Python data analysis , Python data manipulation , Python data processing , Python Data Science Handbook , Python data science tools , Python data wrangling , Python for AI , Python for analytics , Python for big data , Python for business analytics , Python for data science , Python for finance data science , Python for researchers , Python for students , Python in healthcare data , Python machine learning , Python open-source data science , Python predictive analytics , Python programming for data , Python projects for data science , Python real-world examples , Python statistical modeling , Python visualization , Scikit-Learn book
📘 Title Name: Python Data Science Handbook: Essential Tools for Working with Data 2nd Edition
✍️ Author: Jake VanderPlas
📦 Quality: Black White Paper
🔹 Introduction:
This handbook is a complete guide to essential Python tools for data science, offering practical knowledge to analyze, visualize, and manage data effectively.
🔑 Key Points:
-
Covers core Python libraries including NumPy, Pandas, Matplotlib, Scikit-Learn, and Jupyter.
-
Provides hands-on examples for real-world data analysis and machine learning tasks.
-
Explains essential concepts of visualization, statistical modeling, and predictive analytics.
-
Designed for both beginners and advanced data science practitioners.
-
Serves as a practical reference for students, researchers, and professionals working with data.
🔹 Conclusion:
A must-have resource for anyone learning or working in data science, this book equips readers with the Python skills and tools needed to handle modern data challenges.