Python dēta saiensu handobukku: Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook :
Pythonデータサイエンスハンドブック : Jupyter, NumPy, pandas, Matplotlib, scikit-learnを使ったデータ分析, 機械学習 /
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;...
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| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Electronic eBook |
| Language: | Japanese |
| Published: |
Tōkyō-to Shinjuku-ku
Orairī Japan
2024
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| Edition: | Dai 2-han. |
| Subjects: | |
| Links: | https://learning.oreilly.com/library/view/-/9784814400638/?ar |
| Summary: | 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;Python, 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. |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | 1 Online-Ressource (576 Seiten) |
| ISBN: | 9784814400638 4814400632 |
Staff View
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| spelling | Vanderplas, Jacob T. VerfasserIn aut Python data science handbook 880-01 Python dēta saiensu handobukku Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : Jake VanderPlas cho ; Kikuchi Akira yaku = Python data science handbook : essential tools for working with data : second edition / Jake VanderPlas Python data science handbook : 880-02 Dai 2-han. 880-03 Tōkyō-to Shinjuku-ku Orairī Japan 2024 1 Online-Ressource (576 Seiten) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index 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;Python, 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. In Japanese. Python (Computer program language) Handbooks, manuals, etc Data mining Handbooks, manuals, etc Statistical methods Electronic data processing Handbooks, manuals, etc Python (Langage de programmation) ; Guides, manuels, etc Kikuchi, Akira ÜbersetzerIn trl 245-01/Chin Pythonデータサイエンスハンドブック : Jupyter, NumPy, pandas, Matplotlib, scikit-learnを使ったデータ分析, 機械学習 / Jake VanderPlas著 ; 菊池彰訳 = Python data science handbook : essential tools for working with data : second edition / Jake VanderPlas. 250-02/Chin 第 2版. 264-03/Chin 東京都新宿区 オライリー・ジャパン 2024 |
| spellingShingle | Vanderplas, Jacob T. Python dēta saiensu handobukku Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : Python (Computer program language) Handbooks, manuals, etc Data mining Handbooks, manuals, etc Statistical methods Electronic data processing Handbooks, manuals, etc Python (Langage de programmation) ; Guides, manuels, etc |
| title | Python dēta saiensu handobukku Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : |
| title_alt | Python data science handbook Python data science handbook : |
| title_auth | Python dēta saiensu handobukku Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : |
| title_exact_search | Python dēta saiensu handobukku Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : |
| title_full | Python dēta saiensu handobukku Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : Jake VanderPlas cho ; Kikuchi Akira yaku = Python data science handbook : essential tools for working with data : second edition / Jake VanderPlas |
| title_fullStr | Python dēta saiensu handobukku Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : Jake VanderPlas cho ; Kikuchi Akira yaku = Python data science handbook : essential tools for working with data : second edition / Jake VanderPlas |
| title_full_unstemmed | Python dēta saiensu handobukku Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : Jake VanderPlas cho ; Kikuchi Akira yaku = Python data science handbook : essential tools for working with data : second edition / Jake VanderPlas |
| title_short | Python dēta saiensu handobukku |
| title_sort | python deta saiensu handobukku jupyter numpy pandas matplotlib scikit learn o tsukatta deta bunseki kikai gakushu python data science handbook |
| title_sub | Jupyter, NumPy, pandas, Matplotlib, scikit-learn o tsukatta dēta bunseki, kikai gakushū / = Python data science handbook : |
| topic | Python (Computer program language) Handbooks, manuals, etc Data mining Handbooks, manuals, etc Statistical methods Electronic data processing Handbooks, manuals, etc Python (Langage de programmation) ; Guides, manuels, etc |
| topic_facet | Python (Computer program language) Handbooks, manuals, etc Data mining Handbooks, manuals, etc Statistical methods Electronic data processing Handbooks, manuals, etc Python (Langage de programmation) ; Guides, manuels, etc |
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