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Python 3 and data visualization using ChatGPT / GPT-4

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Python 3 and data visualization using ChatGPT / GPT-4/ Oswald Campesato.
作者:	Campesato, Oswald.
出版者:	Boston, MA :Mercury Learning and Information, : c2024.,
面頁冊數:	1 online resource :ill., maps.
附註:	Includes index.
內容註:	Chapter 1: Introduction to Python -- Chapter 2: Introduction to NumPy -- Chapter 3: Pandas and Data Visualization -- Chapter 4: Pandas and SQL -- Chapter 5: Matplotlib and Visualization -- Chapter 6: Seaborn for Data Visualization -- Chapter 7: ChatGPT and GPT-4 -- Chapter 8: ChatGPT and Data Visualization.
標題:	Python (Computer program language) -
電子資源:	https://www.degruyterbrill.com/isbn/9781501518805
ISBN:	9781501518805

Python 3 and data visualization using ChatGPT / GPT-4
Campesato, Oswald.

Python 3 and data visualization using ChatGPT / GPT-4[electronic resource] /Oswald Campesato. - 1st ed. - Boston, MA :Mercury Learning and Information,c2024. - 1 online resource :ill., maps. - MLI generative AI series. - MLI generative AI series..

Includes index.

Chapter 1: Introduction to Python -- Chapter 2: Introduction to NumPy -- Chapter 3: Pandas and Data Visualization -- Chapter 4: Pandas and SQL -- Chapter 5: Matplotlib and Visualization -- Chapter 6: Seaborn for Data Visualization -- Chapter 7: ChatGPT and GPT-4 -- Chapter 8: ChatGPT and Data Visualization.

This book is designed to show readers the concepts of Python 3 programming and the art of data visualization. It also explores cutting-edge techniques using ChatGPT/GPT-4 in harmony with Python for generating visuals that tell more compelling data stories. Chapter 1 introduces the essentials of Python, covering a vast array of topics from basic data types, loops, and functions to more advanced constructs like dictionaries, sets, and matrices. In Chapter 2, the focus shifts to NumPy and its powerful array operations, leading into data visualization using prominent libraries such as Matplotlib. Chapter 6 includes Seaborn's rich visualization tools, offering insights into datasets like Iris and Titanic. Further, the book covers other visualization tools and techniques, including SVG graphics, D3 for dynamic visualizations, and more. Chapter 7 covers information about the main features of ChatGPT and GPT-4, as well as some of their competitors. Chapter 8 contains examples of using ChatGPT in order to perform data visualization, such as charts and graphs that are based on datasets (e.g., the Titanic dataset). Companion files with code, datasets, and figures are available for downloading. From foundational Python concepts to the intricacies of data visualization, this book is ideal for Python practitioners, data scientists, and anyone in the field of data analytics looking to enhance their storytelling with data through visuals. It's also perfect for educators seeking material for teaching advanced data visualization techniques.

Mode of access: Internet via World Wide Web.

In English.

ISBN: 9781501518805

Standard No.: 10.1515/9781501518805doiSubjects--Topical Terms:

729789
Python (Computer program language)

LC Class. No.: QA76.73.P98 / .C367 2024

Dewey Class. No.: 005.133

Python 3 and data visualization using ChatGPT / GPT-4
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500 $a Includes index.
505 0 $a Chapter 1: Introduction to Python -- Chapter 2: Introduction to NumPy -- Chapter 3: Pandas and Data Visualization -- Chapter 4: Pandas and SQL -- Chapter 5: Matplotlib and Visualization -- Chapter 6: Seaborn for Data Visualization -- Chapter 7: ChatGPT and GPT-4 -- Chapter 8: ChatGPT and Data Visualization.
520 $a This book is designed to show readers the concepts of Python 3 programming and the art of data visualization. It also explores cutting-edge techniques using ChatGPT/GPT-4 in harmony with Python for generating visuals that tell more compelling data stories. Chapter 1 introduces the essentials of Python, covering a vast array of topics from basic data types, loops, and functions to more advanced constructs like dictionaries, sets, and matrices. In Chapter 2, the focus shifts to NumPy and its powerful array operations, leading into data visualization using prominent libraries such as Matplotlib. Chapter 6 includes Seaborn's rich visualization tools, offering insights into datasets like Iris and Titanic. Further, the book covers other visualization tools and techniques, including SVG graphics, D3 for dynamic visualizations, and more. Chapter 7 covers information about the main features of ChatGPT and GPT-4, as well as some of their competitors. Chapter 8 contains examples of using ChatGPT in order to perform data visualization, such as charts and graphs that are based on datasets (e.g., the Titanic dataset). Companion files with code, datasets, and figures are available for downloading. From foundational Python concepts to the intricacies of data visualization, this book is ideal for Python practitioners, data scientists, and anyone in the field of data analytics looking to enhance their storytelling with data through visuals. It's also perfect for educators seeking material for teaching advanced data visualization techniques.
530 $a Issued also in print.
538 $a Mode of access: Internet via World Wide Web.
546 $a In English.
588 $a Description based on online resource; title from PDF title page (publisher's Web site, viewed September 18 2025)
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