Вот решение, основанное на данных вашего примера. Вы можете изменить условия фильтрации, изменив логику внутри функции filter ().
library(shiny)
library(dplyr)
library(data.table)
a = c("a1", "a2")
b = c("b1","b2","b3")
c = c("c1")
# Create dummy data
Name <- c("a1", "b1", "c1", "a1 & b1", "a1 & c1", "b1& c1", "a1 & b1 & c1")
# Random numbers
r2 <- runif(length(Name))
p.value <- runif(length(Name))
t.statistic <- runif(length(Name))
dummy.df <- cbind.data.frame(Name, r2, pvalue, t.statistic)
# Define UI
#ui <- fluidPage(
# sidebarPanel(
# selectInput("a.list", "Select As", a),
# selectInput("b.list", "Select Bs", b),
# selectInput("c.list", "Select Cs", c)
#),
#mainPanel(
# tableOutput("tab1"),
#tableOutput("tab2")
#)
# Create a new Row in the UI for selectInputs
fluidRow(
column(4, selectInput("a.list", "Select As", a)
),
column(4, selectInput("b.list", "Select Bs", b)
),
column(4, selectInput("c.list", "Select Cs", c)
)
),
# Create a new row for the table.
fluidRow(
column(8, tableOutput("tab2"))
)
)
# Define server logic
server <- function(input, output){
# Table with all the data
output$tab1 <- renderTable(dummy.df)
# Apply filter to data
foo <- reactive({
dummy.df %>%
filter(Name %like% input$a.list & Name %like% input$c.list)
})
# Table with filtered data - returns rows 5 and 7
output$tab2 <- renderTable(foo())
}
# Create shiny app
shinyApp(ui = ui, server = server)