| Description |
1 online resource (xii, 345 pages) : illustrations (some color) |
| Contents |
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 |
| Summary |
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) |
| Bibliography |
Includes bibliographical references |
| Notes |
Description based on online resource; title from digital title page (viewed on July 17, 2023) |
| Subject |
Python (Computer program language) -- Textbooks
|
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Big data.
|
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Data mining.
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Big data
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Data mining
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Python (Computer program language)
|
| Genre/Form |
Textbooks
|
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Textbooks.
|
| Form |
Electronic book
|
| ISBN |
9789811977022 |
|
981197702X |
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