课程
理解数据可视化
基础技能水平
更新时间 2026年6月
TheoryData Visualization2小时14 视频41 道练习2,400 XP250K+成就证明
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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.
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.
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.
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.
理解数据可视化
课程完成 加入超过19百万学习者,今天就开始理解数据可视化!
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继续使用 Google显示更多选项或
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。
通过 DataCamp for Mobile 提升您的数据技能
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