使用串扰将多个图表与同一张表连接起来而不会相互影响

我在下面创建了 Flexdashboard，最初在其中创建了四个数据框。然后其中三个数据帧显示为图表（dcross2,store,supplier）和一个（dcross1）如表。

我想要实现的是将所有这四个对象连接在一起crosstalk封装的方式是当用户单击某个栏时，表格将做出相应的响应。不是其他图表，只有表格。我相信Abcd是实现这一点的关键，因为它在所有数据帧中都很常见，但我不知道如何将它们连接在一起。

---
title: "Operaitonal dashboard"
author: "Report"
date: 'Date: `r Sys.Date()`'
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    theme: lumen
    vertical_layout: scroll
---

```{r setup, include=FALSE}


knitr::opts_chunk$set(echo=FALSE,
                      warning= FALSE,
                      message = FALSE)
library(crosstalk)
library(shiny)
library(plotly)
library(flexdashboard)
library(ggplot2)
library(dplyr)
library(reactable)
##The four dataframes

Abcd<-c("A","A","B","B")
Prod<-c(34,56,56,89)
Div<-c("Ent","Ent","App","High")
dcross1<-data.frame(Abcd,Prod,Div)%>%
  SharedData$new() 


Counts<-c(45,67,78,56)
dcross2<-data.frame(Div,Abcd,Counts)%>%
  SharedData$new() 


Store<-c(199,199)
Abcd<-c("A","B")
Oos<-c(500,400)
store<-data.frame(Store,Abcd,Oos)%>%
  SharedData$new() 

Man<-c("Corp","Adv","Corp","Adv")
Abcd<-c("A","B","A","B")
Counts<-c(45,56,34,78)
Scounts<-c(23,45,67,67)
Per<-c(1,2,3,5)
supplier<-data.frame(Man,Abcd,Counts,Scounts,Per)%>%
  SharedData$new() 

```

# Out of stock Report {data-icon="fa-cart-arrow-down" data-orientation=rows}

## Row {data-height="200"}

### Out Of Stock: Store Overview {data-width="200"}

```{r Oos Store}
daily_store_oos_gg<-
  ggplot(store,
         aes(x=Abcd,
             y=Oos,
             fill=as.factor(Abcd)
             )) +
  geom_bar(stat="identity", position="dodge") 

# Convert to plotly object
daily_store_oos_ply <- 
  ggplotly(daily_store_oos_gg)

daily_store_oos_ply
```

### Out Of Stock: Division Overview {data-width="200"}

```{r Oos Division}
# Create ggplot object (Aggregated data)

store_division_oos_overview_gg<-
  dcross2 %>%
  ggplot(aes(x=Div,
             y=Counts ,
            fill=Abcd,
            label = Counts)) +
  geom_col(position="fill") 

# Create plotly object
store_division_oos_overview_ply<-
  ggplotly(store_division_oos_overview_gg)
store_division_oos_overview_ply
```

## Column {data-width=405}

### Supplier Overview Out of Stock
```{r supplier}
# Create ggplot object (Aggregated data)
supplier_oos_overview_gg<-
  supplier %>%
  ggplot(aes(x=Man ,
             y=Scounts
             )) +
  geom_bar(stat='identity',aes(fill = Abcd)) +
  coord_flip()

# Create plotly object
supplier_oos_overview_ply<-
  ggplotly(supplier_oos_overview_gg)

supplier_oos_overview_ply
```

### Store Overview Out of Stock
```{r out of stock reactable}
daily_item_oos_rctble<-reactable(
    dcross1
    )

daily_item_oos_rctble

```