Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter 3rd Edition

I. THÔNG TIN SẢN PHẨM
Mã sản phẩm : STT603
Nhà xuất bản:  O'Reilly Media; 3rd edition (September 20, 2022)
Tác giả :  Wes McKinney
Ngôn Ngữ : Tiếng Anh
ISBN      : 109810403X
Số trang    : 579 pages
Hình thức : Bìa Mềm, IN ĐEN TRẮNG
Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.

II. MÔ TẢ SẢN PHẨM
1.Mô tả sản phẩm
Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.

Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.

    Use the Jupyter notebook and IPython shell for exploratory computing
    Learn basic and advanced features in NumPy
    Get started with data analysis tools in the pandas library
    Use flexible tools to load, clean, transform, merge, and reshape data
    Create informative visualizations with matplotlib
    Apply the pandas groupby facility to slice, dice, and summarize datasets
    Analyze and manipulate regular and irregular time series data
    Learn how to solve real-world data analysis problems with thorough, detailed examples
        
2. Tác giả
Wes McKinney is a Nashville-based software developer and entrepreneur. After finishing his undergraduate degree in mathematics at MIT in 2007, he went on to do quantitative finance work at AQR Capital Management in Greenwich, CT. Frustrated by cumbersome data analysis tools, he learned Python and started building what would later become the pandas project. He's now an active member of the Python data community and is an advocate for the use of Python in data analysis, finance, and statistical computing applications.