Changing values in Shiny - r

Question

I am trying to implement a slider in a very simple Shiny application. The main idea is to change the values with the slider and see the visualized result in Chart 2. Below you can see my code
---
title: "Test App"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
runtime: shiny
---
```{r setup, include=FALSE}
library(flexdashboard)
library(shiny)
library(tidyverse)
# Data Set 1
df<-data.frame( cyl=c("4","6","8"),
Multiplier=c(2,4,6))
# Data Set 2
df1 <- mtcars
df1$cyl <- as.factor(df1$cyl)
```
Column {.sidebar}
-----------------------------------------------------------------------
```{r}
selectInput("clusterNum",
label = h4("Charts"),
choices = list("Chart1" = "Chart1", "Chart2" = "Chart2"),
selected = "Chart1"
)
# Sidebar to demonstrate various slider options ----
sidebarPanel(
# Input: Simple integer interval ----
sliderInput("integer", "Integer:",
min = 0, max = 8,
value = 1),)
```
Column {data-width=650}
-----------------------------------------------------------------------
### Chart
```{r}
# First chart
Chart1 <- ggplot(df1, aes(x = wt, y = mpg)) +
geom_point()
# Second chart
Chart2_df1<-df1%>%
dplyr::left_join(df,df1,by = c("cyl"="cyl"))
Chart2_df1<-Chart2_df1%>%
dplyr::mutate(mpg_new=(mpg*Multiplier))
Chart2 <- ggplot(Chart2_df1, aes(x = wt, y = mpg_new)) + geom_point()
# Visualization of the selected chart
renderPlot({
switch(input$clusterNum,
"Chart1" = Chart1,
"Chart2" = Chart2
)
})
```
With the values from the slider, I want to change the value in df for column Multiplier. These values, after changing, are part of the formula of the second chart for multiplying with the value from df1, with column mpg. After this operation, the next step is showing result on chart 2.
So can anybody help me how to implement this similar as picture below ?

Answer 1

In order for the plot to be reactive to an input, we need it to be within reactive or processing within the renderPlot (which is reactive in nature).
One way to do this is to make Chart2 a reactive plot, and then "call" it with Chart2() (the way to get at reactive data/plots):
# First chart
Chart1 <- ggplot(df1, aes(x = wt, y = mpg)) +
geom_point()
# Second chart
Chart2 <- reactive({
dplyr::left_join(df, df1, by = c("cyl" = "cyl")) %>%
dplyr::mutate(mpg_new = (mpg * Multiplier * input$integer)) %>%
ggplot(aes(x = wt, y = mpg_new)) +
geom_point()
})
# Visualization of the selected chart
renderPlot({
switch(input$clusterNum,
"Chart1" = Chart1,
"Chart2" = Chart2()
)
})
Note that Chart1 is unmodified, and since it is not a reactive component, we continue to reference it as Chart1 (no ()) just as we would any other regular R object. Since Chart2 is a shiny-reactive object, though, we need the () to get at the updated value.
If you will be doing something with this data in addition to plotting it, one might choose to make the altered data available as one reactive component and then use it in the other(s).
# Second chart data
Chart2_dat <- reactive({
dplyr::left_join(df, df1, by = c("cyl" = "cyl")) %>%
dplyr::mutate(mpg_new = (mpg * Multiplier * input$integer))
})
# Second chart
Chart2 <- reactive({
Chart2_dat() %>%
ggplot(aes(x = wt, y = mpg_new)) +
geom_point()
})
# Visualization of the selected chart
renderPlot({
switch(input$clusterNum,
"Chart1" = Chart1,
"Chart2" = Chart2()
)
})
and any other components (e.g., tables, additional plots) can also use Chart2_dat() to see the joined/updated data.