Python Data Science Handbook: Essential Tools for Working with Data 2nd Edition

Tình trạng: Còn hàng

Tác giả: O'Reilly Media

Loại: Data

Python Data Science Handbook is not meant to be an introduction to Python or to programming in general; I assume the reader has familiarity with the Python language, including defining functions, assigning variables, calling methods of objects, controlling the flow of a program, and other basic tasks. Instead, it is meant to help Python users learn to use Python’s data science stack—libraries such as those mentioned in the following section, and related tools—to effectively store, manipulate, and gain insight from data.

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Mô tả

I. THÔNG TIN SẢN PHẨM
Mã sản phẩm : STT690
Nhà xuất bản: O'Reilly Media; 2nd edition (January 17, 2023)
Tác giả : Jake VanderPlas
Ngôn Ngữ : Tiếng Anh
ISBN : 1098121228
Số trang : 588 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
Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the new edition of Python Data Science Handbook do you get them all—IPython, NumPy, pandas, Matplotlib, Scikit-Learn, and other related tools.

Working scientists and data crunchers familiar with reading and writing Python code will find the second edition of this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python.

With this handbook, you'll learn how:

+) IPython and Jupyter provide computational environments for scientists using Python
+) NumPy includes the ndarray for efficient storage and manipulation of dense data arrays
+) Pandas contains the DataFrame for efficient storage and manipulation of labeled/columnar data
+) Matplotlib includes capabilities for a flexible range of data visualizations
+) Scikit-learn helps you build efficient and clean Python implementations of the most important and established machine learning algorithms

2. Tác giả
Jake VanderPlas is a software engineer at Google Research, working on tools that support data-intensive research. He creates and develops Python tools for use in data-intensive science, including packages like Scikit-Learn, SciPy, AstroPy, Altair, JAX, and many others. He participates in the broader data science community, developing and presenting talks and tutorials on scientific computing topics at various conferences in the data science world.