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Python 3 Data Visualization Using Google Gemini

  • Добавил: literator
  • Дата: 21-05-2024, 18:13
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Название: Python 3 Data Visualization Using Google Gemini
Автор: O. Campesato
Издательство: Mercury Learning and Information
Год: 2024
Страниц: 201
Язык: английский
Формат: True/Retail PDF EPUB
Размер: 16.4 MB

This book offers a comprehensive guide to leveraging Python-based data visualization techniques with the innovative capabilities of Google Gemini. Tailored for individuals proficient in Python seeking to enhancetheir visualization skills, it explores essential libraries like Pandas, Matplotlib, and Seaborn, along with insights into the innovative Gemini platform. With a focus on practicality and efficiency, it delivers a rapid yet thorough exploration of data visualization methodologies, supported by Gemini-generated code samples. Companion files with source code and figures are available for downloading.

The first chapter contains a quick tour of basic Python 3, followed by a chapter that introduces you to NumPy. The third and fourth chapters introduce you to data visualization with Matplotlib and how to create graphics effects with Seaborn. The fifth chapter introduces you to Google Gemini, which also includes a discussion of GPT-4. The sixth and concluding chapter contains Gemini-generated Python code samples for performing various programming tasks.

Most of the code samples are short (usually less than one page and sometimes less than half a page), and if necessary, you can easily and quickly copy/paste the code into a new Jupyter notebook. For the Python code samples that reference a CSV file, you do not need any additional code in the corresponding Jupyter notebook to access the CSV file. Moreover, the code samples execute quickly, so you won’t need to avail yourself of the free GPU that is provided in Google Colaboratory.

If you do decide to use Google Colaboratory, you can easily copy/paste the Python code into a notebook, and also use the upload feature to upload existing Jupyter notebooks. Keep in mind the following point: if the Python code references a CSV file, make sure that you include the appropriate code snippet (details are available online) to access the CSV file in the corresponding Jupyter notebook in Google Colaboratory.

Features:

Covers Python-based data visualization libraries and techniques
Includes practical examples and Gemini-generated code samples for efficient learning
Integrates Google Gemini for advanced data visualization capabilities
Sets up a conducive development environment for a seamless coding experience
Includes companion files for downloading with source code and figures

What do I need to know for this book?
Current knowledge of Python 3.x is the most helpful skill. Knowledge of other programming languages (such as Java) can also be helpful because of the exposure to programming concepts and constructs. The less technical knowledge that you have, the more diligence will be required in order to understand the assorted topics that are covered.

As for the non-technical skills, it is important to have a strong desire to learn about data visualization, along with the motivation and discipline to read and understand code samples.

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