Title
Python For Data Analysis: Data Wrangling With Pandas, Numpy, And Ipython
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Python For Data Analysis Is Concerned With The Nuts And Bolts Of Manipulating, Processing, Cleaning, And Crunching Data In Python. It Is Also A Practical, Modern Introduction To Scientific Computing In Python, Tailored For Dataintensive Applications. This Is A Book About The Parts Of The Python Language And Libraries Youll Need To Effectively Solve A Broad Set Of Data Analysis Problems. This Book Is Not An Exposition On Analytical Methods Using Python As The Implementation Language.Written By Wes Mckinney, The Main Author Of The Pandas Library, This Handson Book Is Packed With Practical Cases Studies. Its Ideal For Analysts New To Python And For Python Programmers New To Scientific Computing. Use The Ipython Interactive Shell As Your Primary Development Environment Learn Basic And Advanced Numpy (Numerical Python) Features Get Started With Data Analysis Tools In The Pandas Library Use Highperformance Tools To Load, Clean, Transform, Merge, And Reshape Data Create Scatter Plots And Static Or Interactive Visualizations With Matplotlib Apply The Pandas Groupby Facility To Slice, Dice, And Summarize Datasets Measure Data By Points In Time, Whether Its Specific Instances, Fixed Periods, Or Intervals Learn How To Solve Problems In Web Analytics, Social Sciences, Finance, And Economics, Through Detailed Examples
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This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the main focus of 'Python for Data Analysis'? A: 'Python for Data Analysis' primarily focuses on data manipulation, processing, cleaning, and analysis using Python, particularly through libraries like Pandas and NumPy.
- Q: Who is the author of this book? A: The book is authored by Wes McKinney, who is also the main creator of the Pandas library.
- Q: What are the key topics covered in this book? A: Key topics include data wrangling with Pandas, numerical computing with NumPy, data visualization with matplotlib, and practical applications in various fields like finance and web analytics.
- Q: Is this book suitable for beginners? A: Yes, the book is tailored for both analysts new to Python and Python programmers new to scientific computing, making it accessible for beginners.
- Q: How many pages does the book have? A: 'Python for Data Analysis' contains a total of 463 pages.
- Q: What edition of the book is available? A: This listing is for the first edition of 'Python for Data Analysis'.
- Q: When was this book published? A: The book was published on November 27, 2012.
- Q: What type of binding does the book have? A: The book is available in paperback binding.
- Q: What is the condition of the book? A: The book is listed in 'Good' condition.
- Q: Can this book help with scientific computing in Python? A: Yes, it provides a modern introduction to scientific computing in Python, focusing on practical applications for data-intensive tasks.