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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/data-visualization-best-practices
课程评论：没有评论
课程名称：数据可视化最佳实践 课程概述：本课程将涵盖可视化的基础知识以及其在数据科学工作流程中的作用。我们将重点讨论可视化的目的背后的主要概念以及创建有效、易于沟通结果的设计原则。您还将设置Tableau环境，练习数据加载，并对标准普尔500股票行业进行单变量描述性分析。 课程大纲： 第一部分：可视化基础 描述：可视化是各个学科数据分析师的重要技能。以图形方式查看数据往往比单纯使用统计或数学更能提供深刻的直觉。在本模块中，我们将探讨可视化的基本知识，并讨论可视化如何实现更深入的数据洞察以及有效传达结果与结论。 第二部分：有效可视化的设计原则 描述：为创造有效图形，分析师必须理解并能够解释为何特定图形元素需要被包含、排除或修改。在本模块中，我们将探讨为何某些问题更适合用特定的视觉线索模式来回答，讨论在构建数据可视化时需要考虑哪些心理感知理论，同时介绍表示视觉数据的普遍框架——图形语法。 第三部分：单变量可视化方法 描述：单变量可视化方法利用图形语法来表示数据集的基本属性和结构，通过单个变量映射到视觉编码。在本模块中，我们将探讨如何查看数据、可视化什么，并讨论哪些数据映射最适合突出和提取数据中的洞察。 第四部分：标准单变量可视化 描述：为了避免每次可视化时都重头开始，分析师使用几种常见的图表类型，以消除数据解读和解释的歧义。在本模块中，我们将探讨一些标准工具和技术，旨在准备出一整套精心制作的可视化用于讲故事。在完成本模块之前，您将使用Tableau进行单变量分析，抽样数据，比较维度和度量，并练习链接可视化。
Part: 1
Title:Visualization Fundamentals
Description:Visualization is a crucial skill for data analysts across all disciplines. Viewing data graphically often provides greater intuition than by using statistics or mathematics alone. In this module, we’ll explore the fundamentals of visualization and discuss how visualizations can achieve better insight into data as well as effectively communicate results and conclusions.
Part: 2
Title:Design Principles for Effective Visualizations
Description:To create effective visuals, analysts must understand and be able to explain why specific graphical elements must be included, eliminated, or modified. In this module, we’ll investigate why certain questions are best answered by specific visual cue patterns, discuss which psychological perception theories should be considered during the construction of data visualizations, and cover the universal framework for representing visual data, the grammar of graphics.
Part: 3
Title:Univariate Visualization Methods
Description:Univariate visualization methods apply the grammar of graphics to the representation of a dataset’s fundamental properties and structures in terms of single variable mappings to visual encodings. In this module, we’ll explore specifics for how to view the data and what to visualize and discuss what mapping of data is best suited for highlighting and extracting insights from the data.
Part: 4
Title:Standard Univariate Visualizations
Description:Instead of reinventing the wheel with every visualization, analysts use several common chart types so there is no ambiguity about the decoding and interpretation of the data. In this module, we'll explore some standard tools and techniques that are used to prepare a fully crafted set of visualizations for the purpose of storytelling. Before completing this module, you will use Tableau to conduct a univariate analysis to sample data, compare dimensions vs. measures, and practice linking visualizations.
In this course, we will cover the basics of visualization and how it fits into the Data Science workflow. We will focus on the main concepts behind the purpose of visualization and the design principles for creating effective, easy-to-communicate results. You will also set up your Tableau environment, practice data loading, and perform univariate descriptive analysis of the S&P 500 stock sectors.
