红红火火恍恍惚惚的ggplot 高阶版
Best practice
不要搞dynamite
facet_wrap 系列:
margin = TRUE 会给你all, 看最后一个column和row
![](https://assets.matters.news/embed/d0f56a23-8a54-4761-8678-edf82ef239f3.png)
让每个小图都有自己独立的坐标轴 scales = free
![](https://assets.matters.news/embed/9bbb3513-ced3-4d48-9801-cb7082d0e20e.png)
这才是一张好图, 真是令人感动,像我这种马大哈要学习这样极致的美
![](https://assets.matters.news/embed/4a46aa67-1766-4484-8724-716146c2a241.png)
free the space
![](https://assets.matters.news/embed/db92543f-3961-4ad6-a6b6-84400302aa5c.png)
![](https://assets.matters.news/embed/35503416-8586-4865-bbfa-cc59e0704c74.png)
scales =free_x 或者 free_y 或者free 让你的plot 坐标更narrow, free the x scale
![](https://assets.matters.news/embed/bd7bbd3d-c1bd-4dc1-8ec5-8e928e5c2ae3.png)
![](https://assets.matters.news/embed/0a7d071c-bb26-43a2-8e3b-2a82516f62ff.png)
![](https://assets.matters.news/embed/d40de49a-f213-46b8-9ad4-250e8d187dec.png)
![](https://assets.matters.news/embed/005ab588-d6f2-48a5-9950-ffc730bf3804.png)
![](https://assets.matters.news/embed/0fca16c4-9aa3-4f1a-9d61-63cfd0b5d169.png)
Coordinates 层 牛逼
![](https://assets.matters.news/embed/8b962ec6-a1b0-49f8-9714-fb68785fc50c.png)
![](https://assets.matters.news/embed/75d7c864-8790-46d1-8198-2c5e19d9e5cc.png)
![](https://assets.matters.news/embed/f8580d27-b58d-4ae3-a559-5f0f54cf89f4.png)
![](https://assets.matters.news/embed/f8ea3031-c207-4e8c-8081-ff47f6e8072f.png)
![](https://assets.matters.news/embed/822edc35-ab4a-4a0a-8759-9dd9351bd9c5.png)
![](https://assets.matters.news/embed/03e8b659-94c1-453d-b85f-c7f13ee60147.png)
做review 发现自己不会的其实这么多,感觉活该自己不被hired。应该做项目,而且计时做。做得又快又对,visualization又好看实用,以这个为目标去做。毕竟我写作也不好。
不要想会不会有人要我,不要我了。先成为最好的,怎么会有人不要你呢?
这个 scale_x_continous 还有log version 都很牛逼
![](https://assets.matters.news/embed/fdabe774-04a1-4b5b-8930-d5887f73c3d8.png)
![](https://assets.matters.news/embed/6d378aa1-562f-4c26-8c81-8fc25c7227de.png)
![](https://assets.matters.news/embed/6d5ae397-0d49-49f1-8dab-5871386539cd.png)
![](https://assets.matters.news/embed/e523d2d1-3350-4fb6-84c7-83369ea7e7e7.png)
![](https://assets.matters.news/embed/3816e0ae-3df9-4355-8d8d-0a9fd14d081a.png)
qq plot https://towardsdatascience.com/q-q-plots-explained-5aa8495426c0
感觉在financial data 那边看到过qq plot ,但是我完全忘记怎么用了。。。
![](https://assets.matters.news/embed/16366308-6e65-45d8-b8f7-f69b9804a04d.png)
geom_rug. margin上会有visualization. 大概是写个频率吧。。Rd. A rug plot is a compact visualisation designed to supplement a 2d display with the two 1d marginal distributions. Rug plots display individual cases so are best used with smaller datasets.
为啥我感觉我自己从来没上过这些课?
![](https://assets.matters.news/embed/e8640eb8-d924-458f-a22f-7cefd46132b6.png)
![](https://assets.matters.news/embed/f568fa75-42d8-4c45-a67a-25ecb06a85da.png)
![](https://assets.matters.news/embed/4e0d4202-610b-4d25-bfbf-480c7bd0a1eb.png)
![](https://assets.matters.news/embed/c3eacda3-4946-4498-b7aa-55c826d8ef91.png)
![](https://assets.matters.news/embed/6ed84442-da76-46cb-8783-49b0f13c3ea9.png)
mean_sdl computes the mean plus or minus a constant times the standard deviation. In the R code below, the constant is specified using the argument mult (mult = 1).
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