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Hands-On Data Analytics for Beginners with Google Colaboratory

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Hands-On Data Analytics for Beginners with Google Colaboratory
Hands-On Data Analytics for Beginners with Google Colaboratory
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 3 Hours | 568 MB
Genre: eLearning | Language: English

Google Colaboratory is an online platform to perform data analysis. It enables you to create interactive Jupyter notebooks that mix text with Python code to run queries and display data analysis results. Stored on Google Drive you'll be able to run notebooks and collaborate with peers through Google's cloud services.

In this course, you will learn to solve problems and obtain key results with data. You will begin by building your own Jupyter notebook before you explore and learn the basics of Google Colaboratory. Then you will explore several file formats to store data and use SQLite to query large datasets. Next, you will learn to initialize 1D and 2D data structures with the Numpy and Pandas libraries to help organize and summarize metrics such as the mean, median, and standard deviation of your data.

Moving further, you will learn to identify outliers in your data, eliminate dirty data and perform common data transformations. Finally, you will use qualitative and quantitative data types with Matplotlib to display effective charts and visuals. By the end of this course, you'll have the tools to perform data analysis to tell your own compelling stories with data.

The code bundle for this course is available at https://github.com/PacktPublishing/Hands-On-Data-Analytics-for-Beginners-with-Google-Colaboratory-Video-

Hands-On Data Analytics for Beginners with Google Colaboratory

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  1. Google Colaboratory输入分析入门实践 Google Colaboratory是一款用于数据分析的在线平台。其可以让你通过运行查询和显示数据分析结果的Python代码,创建混合了文本互动Jupyter。存储在Google Drive,你将能够通过Google云服务运行笔记和与他人协作。 在本教程中,你将学习通过数据解决问题和获取重要结果。在你了解和学习Google Colaboratory之前,你将从开发你自己的Jupyter笔记开始。然后,你将学习几种存储数据和使用SQLite查询大数据集的文件格式。接下来,你将学习通过Numpy和Pandas类库初始化1D和2D数据结构,帮助组织和总结如数据均值、中间值、标准方差的标准。 在接下来,你将学习识别数据中的异常,消除脏数据和执行常见的数据转换。最后,你将通过Matplotlib使用量化和质化数据类型,显示图表和视觉效果。学习完本教程,你将掌握执行数据分析发现数据洞察的工具。
    wilde(特殊组-翻译)3个月前 (08-05)