如何将UI文件上的textInput值传递给全局文件中的sqldf?

时间:2016-09-20 13:33:22

标签: sqldf

  

我在UI.R上有一个textInput,我想用它作为      过滤到我在GLOBAL.R上的sqldf中的查询,但我知道如何做到这一点。      任何人都可以帮助我吗?

     

这是我的UI.R

 fluidPage(Application title   titlePanel("Robsonb - CRAI"),
         sidebarLayout(
        # Sidebar with a slider and selection inputs
        sidebarPanel(
          selectInput("selection", "Escolha uma lista:",
                      choices = books),
          actionButton("update", "Alterar"),
          hr(),

textInput(inputId="descritor",value="cárie", label = ""),

      sliderInput("freq",
                  "Minimum Frequency:",
                  min = 1,  max = 50, value = 15),
      sliderInput("max",
                  "Maximum Number of Words:",
                  min = 1,  max = 300,  value = 100)
    ),



    # Show Word Cloud
    mainPanel(
      plotOutput("plot"),
      textOutput("descritor")

    ) ) )
  

这是我的Global.R,我在那里进行SQL查询。我打算做点什么   像sqldf(“选择Assuntos,来自结果O3的sysno在哪里   [Resumo.em.português]喜欢。我正在使用闪亮的包装。

library(tm)
library(wordcloud)
library(memoise)
library(sqldf)

# The list of valid books
books <<- list("Resumo de Teses FOUSP" = "tesesFO"
               )

# Using "memoise" to automatically cache the results
getTermMatrix <- memoise(function(book) {
  # Careful not to let just any name slip in here; a
  # malicious user could manipulate this value.
  if (!(book %in% books))
    stop("Base não encontrada")


  outcome <- read.csv2("TesesFOResumo.csv", colClasses = "character")

  #input<- input$descritor


  sqldf("select Assuntos, sysno from outcome O3 where [Resumo.em.português] LIKE '%cárie%' UNION ALL 
      select Assuntos, sysno from outcome O1 where sysno in (select sysno from outcome O2 where assuntos LIKE '%cárie%')")

  text <- sqldf("select Assuntos, sysno from outcome O3 where [Resumo.em.português] LIKE '%cárie%' UNION ALL 
      select Assuntos, sysno from outcome O1 where sysno in (select sysno from outcome O2 where assuntos LIKE '%cárie%')")


  myCorpus = Corpus(VectorSource(text))
  myCorpus = tm_map(myCorpus, content_transformer(tolower))
  myCorpus = tm_map(myCorpus, removePunctuation)
  myCorpus = tm_map(myCorpus, removeNumbers)
  myCorpus = tm_map(myCorpus, removeWords,
                    c(stopwords("SMART"), "de", "da", "dos", "the", "and", "but"))

  myDTM = TermDocumentMatrix(myCorpus,
                             control = list(minWordLength = 1))

  m = as.matrix(myDTM)

  sort(rowSums(m), decreasing = TRUE)
})

0 个答案:

没有答案