可视化→数据处理→可视化+数据处理→建模
数据可视化的学习过程容易有成就感，而非枯燥和挫败。良好的开端是成功的一半，坚持下来，离会用一门新语言就不远了。
1.数据研究
Data exploration is the art of looking at your data, rapidly generating hypotheses, quickly testing them, then repeating again and again and again. The goal of data exploration is to generate many promising leads that you can later explore in more depth.
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2.为什么是可视化
Visualisation is a great place to start with R programming, because the payoff is so clear: you get to make elegant and informative plots that help you understand data.
In data visualisation you’ll dive into visualisation, learning the basic structure of a ggplot2 plot, and powerful techniques for turning data into plots.
3. 可视化够用吗
Visualisation alone is typically not enough, so in data transformation you’ll learn the key verbs that allow you to select important variables, filter out key observations, create new variables, and compute summaries.
4.怎么做更好
Finally, in exploratory data analysis, you’ll combine visualisation and transformation with your curiosity and scepticism to ask and answer interesting questions about data.
5.还需要什么
Modelling is an important part of the exploratory process, but you don’t have the skills to effectively learn or apply it yet. We’ll come back to it in modelling, once you’re better equipped with more data wrangling and programming tools.
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