How to clean up CSV data after uploading to Shiny App - r

Question

Please help!
I'm trying to build a Shiny App with the intent to classify data loaded from a CSV file. How do I successfully create a DataFrame from a CSV file (that is uploaded) so that I can move forward and clean/analyze it.
Please see code:
library(shiny)
library(lubridate)
library(utils)
library(dplyr)
library(tidytext)
ui <- (pageWithSidebar(
headerPanel("CSV File Upload Demo"),
sidebarPanel(
#Selector for file upload
fileInput('datafile', 'Choose CSV file',
accept=c('text/csv', 'text/comma-separated-values,text/plain')),
#These column selectors are dynamically created when the file is loaded
uiOutput("fromCol"),
uiOutput("toCol"),
uiOutput("amountflag"),
#The conditional panel is triggered by the preceding checkbox
conditionalPanel(
condition="input.amountflag==true",
uiOutput("amountCol")
)
),
mainPanel(
tableOutput("filetable")
)
))
Please advise whether to use Reactive
server <- (function(input, output) {
#This function is repsonsible for loading in the selected file
filedata <- reactive({
infile <- input$datafile
if (is.null(infile)) {
# User has not uploaded a file yet
return(NULL)
}
dataframe <- reactive({
readr::read_csv(infile()$datapath)
})
# Clean data by whole-case removal of missing cells (either NAs or "nan")
# Remove the rows which have NAs
myDataClean2 = dataframe[complete.cases(dataframe),]
# In order to turn it into a tidy text dataset, we first put the data into a data frame:
text_df <- data_frame(myDataClean2$text,myDataClean2$title,myDataClean2$author,myDataClean2$id,myDataClean2$label)
names(text_df) <- c("text","title","author","id","label")
# Within the tidy text framework, we break both the text into individual tokens and transform
# it to a tidy data structure. To do this, we use tidytextâs unnest_tokens() function.
tidy_text_df <- text_df %>%
unnest_tokens(word, text)
#This previews the CSV data file
output$filetable <- renderText({
tidy_text_df()
})
})
})
# Run the application
shinyApp(ui = ui, server = server)

Answer 1

You are mixing reactive blocks. Your filedata should end with something that outputs your data, likely the output from unnest_tokens(word, text). (It should put out all data you are interested in, I think that that line does.) From there, your output$filetable needs to be outside of filedata's reactive block, on its own. And it should be using filedata(), not tidy_text_df (which isn't available outside of the first reactive block).
Try this:
server <- (function(input, output) {
#This function is repsonsible for loading in the selected file
filedata <- reactive({
infile <- input$datafile
if (is.null(infile)) {
# User has not uploaded a file yet
return(NULL)
}
dataframe <- reactive({
readr::read_csv(infile()$datapath)
})
# Clean data by whole-case removal of missing cells (either NAs or "nan")
# Remove the rows which have NAs
myDataClean2 = dataframe[complete.cases(dataframe),]
# In order to turn it into a tidy text dataset, we first put the data into a data frame:
text_df <- data_frame(myDataClean2$text,myDataClean2$title,myDataClean2$author,myDataClean2$id,myDataClean2$label)
names(text_df) <- c("text","title","author","id","label")
# Within the tidy text framework, we break both the text into individual tokens and transform
# it to a tidy data structure. To do this, we use tidytextâs unnest_tokens() function.
text_df %>%
unnest_tokens(word, text)
})
#This previews the CSV data file
output$filetable <- renderText({
filedata()
})
})