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nexusstc/Python Data Science Handbook (Jupyter Notebook Version)/12ac00578cc7da0fe79971b408afb21c.pdf
Python Data Science Handbook (Jupyter Notebook Version) 🔍
it-ebooks iBooker it-ebooks, it-ebooks-2017, 2017
英语 [en] · PDF · 21.9MB · 2017 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/zlib · Save
描述
For many researchers, Python is a first-class tool mainly 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 Python Data Science Handbook do you get them allIPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find 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, youll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
备用文件名
lgrsnf/Python Data Science Handbook (Jupyter Notebook Version).pdf
备用文件名
zlib/Computers/Programming/it-ebooks/Python Data Science Handbook (Jupyter Notebook Version)_11918844.pdf
备选标题
Python Data Science Handbook : Essential Tools for Working with Data
备选标题
Python для сложных задач: наука о данных и машинное обучение: 16+
备选作者
Дж. Вандер Плас; [перевела с английского И. Пальти]
备选作者
Jacob T. Vanderplas; Jake VanderPlas
备选作者
Плас, Джейк Вандер
备用出版商
O'Reilly Media, Incorporated
备用出版商
Питер
备用版本
First edition, Beijing; Boston; Farnham; Sebastopol; Tokyo, 2016
备用版本
Бестселлеры O'Reilly, Санкт-Петербург [и др.], Russia, 2020
备用版本
Бестселлеры O'Reilly, Санкт-Петербург [и др.], Russia, 2018
备用版本
United States, United States of America
备用版本
O'Reilly Media, Sebastopol, CA, 2016
备用版本
First edition, Sebastopol, CA, 2016
备用版本
1st Edition, Dec 10, 2016
备用版本
Beijing, 2017
备用版本
1, PS, 2017
元数据中的注释
lg2974328
元数据中的注释
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元数据中的注释
Фактическая дата выхода в свет - 2019
Пер.: Plas, Jake Vander Python data science handbook Beijing [etc.] : O'Reilly, cop. 2017 978-1491912058
元数据中的注释
РГБ
元数据中的注释
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Пер.: Plas, Jake Vander Python data science handbook Beijing [etc.]: O'Reilly 978-1491912058
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备用描述
For Many Researchers, Python Is A First-class Tool Mainly 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 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 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.-- Ipython: Beyond Normal Python -- Introduction To Numpy -- Data Manipulation With Pandas -- Visualization With Matplatlib -- Machine Learning. Jake Vanderplas. Includes Index.
备用描述
**Revision History**
December 2016: First Edition
2016-11-17: First Release
开源日期
2021-03-29
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