如何制作用户在闪亮或Flexdahsboard中选择的变量的图表？

如何解决如何制作用户在闪亮或Flexdahsboard中选择的变量的图表？

我对R来说还很陌生，我正在尝试将一个flexdashboard放在一起，它从用户输入中获取x和y变量，并返回这些值的图形。到目前为止，我已经可以在下面的代码中使用ggplotly生成所需的图形。

output$scatter <-renderPlotly({
  
  cat('input$x=',input$x,'\n')
  cat('input$y=',input$y,'\n')
  p <- ggplot(Merged_data_frame_hcat,aes_string(x=input$x,y=input$y)) +
       geom_point()+
       theme_minimal(base_size = 14) 
  g <- ggplotly(p,source = 'source') %>%
       layout(dragmode = 'lasso',margin = list(l = 100),font = list(family = 'Open Sans',size = 16))
})

但是，通过ggplotly，我意识到x轴的定义不如我使用plot_ly在仪表板外部绘制相同变量的图那样。

有没有一种方法可以在flexdashboard上使用plot_ly iside。到目前为止，我写了这篇文章，但是那没有用。顺便说一句，我在这里使用noquote，因为plot_ly不能很好地接受字符串形式的输入名称

output$scatter <-renderPlotly({
  
  cat('input$x=','\n')
  if (length(input$y) == 2){
     x1 = noquote(input$x)
     y1 =noquote(input$y[1])
     y2 = noquote(input$y[2])
  
   plot_ly(Merged_data_frame_hcat)%>%
     add_lines(x= ~x1,y =~y1,name = "Red") 
     add_lines(x= ~x1,y =~y2,name = "Green")
   }
})

在我忘记之前，这是我为简化起见而缩小的数据框示例

df <-data.frame("Timestamp.Excel_1900."=c("2019-04-01 16:52:51","2019-04-01 16:57:46","2019-04-01 17:02:51","2019-04-01 17:07:46","2019-04-01 17:12:52","2019-04-01 17:17:46"),"Temperature.C."= c(5.2995,5.3155,5.3353,5.3536,5.3770,5.4044),"pH.pH."= c(7.60,7.80,7.96,8.04,8.09,8.14))

解决方法

有几种方法可以使这项工作。不幸的是，您使用noquote的方法不起作用。

1. 最简单的方法可能是从df中提取列，并将其作为向量传递给plotly，例如x = df[[input$x]]
2. 由于plotly API与单边公式一起使用，第二种方法是将变量作为公式传递，例如x = as.formula(paste0("~",input$x))
3. 在此post之后，您还可以使用base::get，例如x = ~get(input$x)
4. 遵循此post，您还可以使用整洁的评估方式

以下示例flexdashboard中说明了所有四种方法：

---
title: "Plotly"
output: flexdashboard::flex_dashboard
runtime: shiny
---

```{r}
library(plotly)
library(rlang)
```

```{r global,include=FALSE}
# load data in 'global' chunk so it can be shared by all users of the dashboard
df <- data.frame("Timestamp.Excel_1900." = c("2019-04-01 16:52:51","2019-04-01 16:57:46","2019-04-01 17:02:51","2019-04-01 17:07:46","2019-04-01 17:12:52","2019-04-01 17:17:46"),"Temperature.C."= c(5.2995,5.3155,5.3353,5.3536,5.3770,5.4044),"pH.pH."= c(7.60,7.80,7.96,8.04,8.09,8.14))

```

Column {.sidebar}
-----------------------------------------------------------------------

```{r}
selectInput("x","x",choices = names(df),selected = "Timestamp.Excel_1900."
)
selectizeInput("y","y",selected = c("Temperature.C.","pH.pH."),multiple = TRUE,options = list(maxItems = 2)
)
```

Column
-----------------------------------------------------------------------

```{r}
# Pass the data columns as vectors
renderPlotly({
  if (length(input$y) == 2) {
    x1 <- df[[input$x]]
    y1 <- df[[input$y[1]]]
    y2 <- df[[input$y[2]]]

    plot_ly() %>%
      add_lines(x = x1,y = y1,name = "Red") %>%
      add_lines(x = x1,y = y2,name = "Green")
  }
})
```

```{r}
# One-sided formulas
renderPlotly({
  if (length(input$y) == 2) {
    x1 <- input$x
    y1 <- input$y[1]
    y2 <- input$y[2]

    plot_ly(df) %>%
      add_lines(x = as.formula(paste("~",x1)),y = as.formula(paste("~",y1)),name = "Red") %>%
      add_lines(x = as.formula(paste("~",y2)),name = "Green")
  }
})
```

Column
-----------------------------------------------------------------------

```{r}
# Using base::get
renderPlotly({
  if (length(input$y) == 2) {
    x1 <- input$x
    y1 <- input$y[1]
    y2 <- input$y[2]

    plot_ly(df) %>%
      add_lines(x = ~ get(x1),y = ~ get(y1),name = "Red") %>%
      add_lines(x = ~ get(x1),y = ~ get(y2),name = "Green")
  }
})
```

```{r}
# Using tidy evaluation
renderPlotly({
  if (length(input$y) == 2) {
    x1 <- input$x
    y1 <- input$y[1]
    y2 <- input$y[2]

    eval_tidy(
      quo_squash(
        quo({
          plot_ly(df) %>%
            add_lines(x = ~ !!sym(x1),y = ~ !!sym(y1),name = "Red") %>%
            add_lines(x = ~ !!sym(x1),y = ~ !!sym(y2),name = "Green")
        })
      )
    )
  }
})
```