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Python data science

Borjigin, Chaolemen.

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Python data science

Record Type:	Electronic resources : Monograph/item
Title/Author:	Python data science/ by Chaolemen Borjigin.
Author:	Borjigin, Chaolemen.
Published:	Singapore :Springer Nature Singapore : : 2023.,
Description:	xii, 345 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	1. Python and Data Science -- 2. Basic Python Programming for Data Science -- 3. Advanced Python Programming for Data Science -- 4. Data preprocessing and wrangling -- 5. Data analysis algorithms and models.
Contained By:	Springer Nature eBook
Subject:	Python (Computer program language) - Textbooks. -
Online resource:	https://doi.org/10.1007/978-981-19-7702-2
ISBN:	9789811977022

Python data science
Borjigin, Chaolemen.

Python data science[electronic resource] /by Chaolemen Borjigin. - Singapore :Springer Nature Singapore :2023. - xii, 345 p. :ill. (some col.), digital ;24 cm.

1. Python and Data Science -- 2. Basic Python Programming for Data Science -- 3. Advanced Python Programming for Data Science -- 4. Data preprocessing and wrangling -- 5. Data analysis algorithms and models.

Rather than presenting Python as Java or C, this book focuses on the essential Python programming skills for data scientists and advanced methods for big data analysts. Unlike conventional textbooks, it is based on Markdown and uses full-color printing and a code-centric approach to highlight the 3C principles in data science: creative design of data solutions, curiosity about the data lifecycle, and critical thinking regarding data insights. Q&A-based knowledge maps, tips and suggestions, notes, as well as warnings and cautions are employed to explain the key points, difficulties, and common mistakes in Python programming for data science. In addition, it includes suggestions for further reading. This textbook provides an open-source community via GitHub, and the course materials are licensed for free use under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

ISBN: 9789811977022

Standard No.: 10.1007/978-981-19-7702-2doiSubjects--Topical Terms:

3661585
Python (Computer program language)
--Textbooks.

LC Class. No.: QA76.73.P98 / B67 2023

Dewey Class. No.: 005.133

Python data science
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505 0 $a 1. Python and Data Science -- 2. Basic Python Programming for Data Science -- 3. Advanced Python Programming for Data Science -- 4. Data preprocessing and wrangling -- 5. Data analysis algorithms and models.
520 $a Rather than presenting Python as Java or C, this book focuses on the essential Python programming skills for data scientists and advanced methods for big data analysts. Unlike conventional textbooks, it is based on Markdown and uses full-color printing and a code-centric approach to highlight the 3C principles in data science: creative design of data solutions, curiosity about the data lifecycle, and critical thinking regarding data insights. Q&A-based knowledge maps, tips and suggestions, notes, as well as warnings and cautions are employed to explain the key points, difficulties, and common mistakes in Python programming for data science. In addition, it includes suggestions for further reading. This textbook provides an open-source community via GitHub, and the course materials are licensed for free use under the following license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
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