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理解数据可视化

基础技能水平
更新时间 2026年6月
无需编码的数据可视化入门。
免费开始课程
TheoryData Visualization
2小时
14 视频
41 道练习
2,400 XP
250K+
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课程描述

使用图表、图形和地图来可视化数据,是传达复杂信息最有力的方式之一。在本课程中,您将学习如何为您的数据集选择最合适的可视化方式,并学习如何解读常见图形类型,如直方图、散点图、折线图和条形图。您还将了解在图表中使用颜色和形状的最佳实践,以及如何避免常见误区。通过动手练习,您将直观探索 20 多个数据集,包括全球预期寿命、洛杉矶房价、ESPN 最知名的 100 位运动员,以及历来最具影响力的嘻哈歌曲。视频包含实时字幕,您可以单击视频左下角的 "Show transcript" 进行查看。课程术语表位于右侧的资源部分。如需获得 CPE 学分,您需要完成课程,并在合格评估中取得 70% 的得分。您可以点击右侧的 CPE 学分提示进入评估。

先决条件

本课程无先修要求
1

Visualizing distributions

In this chapter you’ll learn the value of visualizations, using real-world data on British monarchs, Australian salaries, Panamanian animals, and US cigarette consumption, to graphically represent the spread of a variable using histograms and box plots.
开始章节
2

Visualizing two variables

You’ll learn how to interpret data plots and understand core data visualization concepts such as correlation, linear relationships, and log scales. Through interactive exercises, you’ll also learn how to explore the relationship between two continuous variables using scatter plots and line plots. You'll explore data on life expectancies, technology adoption, COVID-19 coronavirus cases, and Swiss juvenile offenders. Next you’ll be introduced to two other popular visualizations—bar plots and dot plots—often used to examine the relationship between categorical variables and continuous variables. Here, you'll explore famous athletes, health survey data, and the price of a Big Mac around the world.
开始章节
3

The color and the shape

It’s time to make your insights even more impactful. Discover how you can add color and shape to make your data visualizations clearer and easier to understand, especially when you find yourself working with more than two variables at the same time. You'll explore Los Angeles home prices, technology stock prices, math anxiety, the greatest hiphop songs, scotch whisky preferences, and fatty acids in olive oil.
开始章节
4

99 problems but a plot ain't one of them

In this final chapter, you’ll learn how to identify and avoid the most common plot problems. For example, how can you avoid creating misleading or hard to interpret plots, and will your audience understand what it is you’re trying to tell them? All will be revealed! You'll explore wind directions, asthma incidence, and seats in the German Federal Council.
开始章节
理解数据可视化
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继续操作即表示您接受我们的《使用条款》和《隐私政策》,并同意您的数据存储在美国。

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