作者：小橙子

来源：小橙子学数据分析

之前扬言要用R，制作一个DashBoard。结果给自己挖了个坑，看了好久的外文网站，依靠谷歌翻译和仅留的英语基础，总算完成了。

今天分享的是Rmarkdown中的flexdashboard,可以作为数据产品原型开发的样板。假如创业公司，不舍得花钱买BI工具，也可以

以Umeng的DashBoard作为参考，利用flexdashboard制作了一个类似的。

首先查看下umeng的原图：

再看下flexdashboard的效果图：

与Umeng相比，缺乏美感(渲染不行)

小橙子制作的样本，已经上传至http://rpubs.com/CHENGZI/dashboard，有兴趣的同学，可以实际点击查看下

flexdashboard知识点(太多了，写不完，推荐大家看其他人总结的)

https://bookdown.org/yihui/rmarkdown/dashboard-components.html#navigation-bar

https://zhuanlan.zhihu.com/p/41423522

https://rmarkdown.rstudio.com/flexdashboard/shiny.html#input_sidebar

小橙子的源码如下：

---
title: "APP监控DashBoard"
output:     flexdashboard::flex_dashboard:  orientation: rows   vertical_layout: scroll theme: yeti source_code: embed
--- ```{r setup, include=FALSE}
library(flexdashboard)
library(ggplot2)
library(ggthemes)
``` page 1
=====================================
## Sidebar {.sidebar}
[Page 1]    [Page 2]    ## '1-Sidebar'
### 新增用户    ```{r}  valueBox(75, icon = "fa-user-plus",color = ifelse(75 < 100, "warning", "primary"))
``` ### 活跃用户    ```{r}  valueBox('1,000', icon = "fa-user-friends",color = "info")
``` ### 近7日总活跃用户数   ```{r}  valueBox('3,000', icon = "fa-users",color = "#ffffff")
``` ### 近30日总活跃用户数  ```{r}  valueBox('10,000', icon = "fa-users")
```
##整体趋势2
### 新用户次日留存率(7日平均)  ```{r}  valueBox('75%', icon = "fa-hourglass-start")
```
### 使用时长(7日平均)  ```{r}  valueBox('00:60:20', icon = "fa-user-clock")
```
### 累计用户数   ```{r}  valueBox("23,000", icon = "fa-users")
``` ### 总崩溃率    ```{r}  valueBox('0.01%', icon = "fa-bug")
``` Row {.tabset data-width=350}
----------------------------------------------------------------------- ### Newer   ```{r}
library(ggplot2)
library(ggthemes)
mydata <- data.frame(    Date =  as.character(seq.Date(from = as.Date("2019/01/01",format = "%Y/%m/%d"), by = "day", length.out = 31)),  Newer = round(runif(31,min = 1, max = 100))
)   ggplot(data = mydata, aes(x = Date, y = Newer)) + geom_bar(stat = 'identity') + theme_economist() + theme(axis.text.x = element_text(angle = 90,size = rel(0.8)))   ``` ### Active  ```{r}
library(ggplot2)
library(ggthemes)
mydata_act <- data.frame(    Date =  as.character(seq.Date(from = as.Date("2019/01/01",format = "%Y/%m/%d"), by = "day", length.out = 31)),  Activer = round(runif(31,min = 800, max = 1200)))   ggplot(data = mydata_act, aes(x = Date, y = Activer, group = 1)) + geom_line(linetype = 3) +geom_point(size = 2,colour = "blue")+   theme_economist() + theme(axis.text.x = element_text(angle = 90,size = rel(0.8)))
``` ### Avg_Time    ```{r}
library(ggplot2)
library(ggthemes)
mydata_Use_Time <- data.frame(   Date =  as.character(seq.Date(from = as.Date("2019/01/01",format = "%Y/%m/%d"), by = "day", length.out = 31)),  Use_Time = round(runif(31,min = 50, max = 90))) ggplot(data = mydata_Use_Time, aes(x = Date, y = Use_Time, group = 1)) + geom_line(linetype = 3) +geom_point(size = 2,colour = "blue") +    theme_economist() + theme(axis.text.x = element_text(angle = 90,size = rel(0.8))) +     labs(y = "Use_Time(Minutes)")
``` page 2
=====================================
## Sidebar {.sidebar}
[Page 1]    [Page 2]    ## '1-Sidebar'
```{r}
# page2的数据，直接借用page1的了
library(ggplot2)
library(ggthemes)
mydata_Use_Time <- data.frame(   Date =  as.character(seq.Date(from = as.Date("2019/01/01",format = "%Y/%m/%d"), by = "day", length.out = 31)),  Use_Time = round(runif(31,min = 50, max = 90))) ggplot(data = mydata_Use_Time, aes(x = Date, y = Use_Time, group = 1)) + geom_line(linetype = 3) +geom_point(size = 2,colour = "blue") +    theme_economist() + theme(axis.text.x = element_text(angle = 90,size = rel(0.8))) +     labs(y = "Use_Time(Minutes)")
```

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