可視化→數(shù)據(jù)處理→可視化+數(shù)據(jù)處理→建模
數(shù)據(jù)可視化的學(xué)習(xí)過程容易有成就感，而非枯燥和挫敗。良好的開端是成功的一半，堅(jiān)持下來，離會(huì)用一門新語言就不遠(yuǎn)了。
1.數(shù)據(jù)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.
2.為什么是可視化
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. 可視化夠用嗎
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.還需要什么
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.
