Error in active reactive context - How to fix? - r

Question

Hey I am trying to build a shiny app for the purpose of calculating per cent chance of defaulting and I thought I fixed all my issues until I hit
Error in .getReactiveEnvironment()$currentContext() :
Operation not allowed without an active reactive context. (You tried to do something that can only be done from inside a reactive expression or observer.)
but whenever I try to build something reactive I get
Error in RET#get_where(newdata = newdata, mincriterion = mincriterion) :
object 'loanfilev3' not found
I've looked over stackoverflow and tutorials and none seem to really help
Here is my UI and Server code for the first error, if someone could please highlight my issue that would be greatly appreciated.
UI:
library(shiny)
shinyUI(fluidPage(
titlePanel("Tabsets"),
# Sidebar layout with input and output definitions ----
sidebarLayout(
# Sidebar panel for inputs ----
sidebarPanel(
# Input: Select the random distribution type ----
numericInput("loan_amnt",
"Loan Amount:",
value = 5000,
min = 0,
max = NA),
numericInput("int_rate",
"Interest Rate:",
value = 10.5,
min = 0,
max = NA),
selectInput("term",
"Loan Term:",
c("36 months" = " 36 months",
"60 months" = " 60 months")),
numericInput("installment",
"Installment:",
value = 100,
min = 0,
max = NA),
textInput("grade", "Grade:", "B"),
textInput("emp_length", "Employment Length:", "5 years"),
numericInput("annual_inc",
"Annual Income:",
value = 40000,
min = 0,
max = NA),
numericInput("dti",
"Debt to Income Ratio:",
value = 5.4,
min = NA,
max = NA),
textInput("sub_grade", "SubGrade:", "B2"),
textInput("verification_status", "Verification Status:", "Verified"),
textInput("home_ownership", "Home Ownership:", "RENT"),
radioButtons("pymnt_plan", "Payment Plan:",
c("Yes" = "y",
"No" = "n"))
),
# Main panel for displaying outputs ----
mainPanel(
# Output: Tabset w/ plot, summary, and table ----
tabsetPanel(type = "tabs",
tabPanel("Decision Tree", verbatimTextOutput("ct")),
tabPanel("Generlized Linear Model", verbatimTextOutput("dl")),
tabPanel("K-Nearest Neighbour", verbatimTextOutput("kn"))
)
)
)
)
)
Server:
library(shiny)
library(pscl)
library(ROCR)
library(plyr)
library(dplyr)
library(ggplot2)
library(pROC)
library(caret)
library(e1071)
library(RMySQL)
library(reshape2)
USER <- 'inft216'
PASSWORD <- 'rosemary'
HOST <- 'bruce3.dc.bond.edu.au'
DBNAME <- 'inft216'
db <- dbConnect(MySQL(), user = USER, password = PASSWORD, host = HOST, dbname = DBNAME)
loanfile <- dbGetQuery(db, statement = "select * from lendingClub;")
dbDisconnect(db)
library(party)
colnames(loanfile) = tolower(colnames(loanfile))
bad_indicators = c("Charged Off",
"Default",
"Does not meet the credit policy. Status:Charged Off",
"Default Receiver",
"Late (16-30 days)",
"Late (31-120 days)")
loanfile$default = ifelse(loanfile$loan_status %in% bad_indicators, 1,
ifelse(loanfile$loan_status=="", NA, 0))
loanfile$loan_status = as.factor(loanfile$default)
loanfilev2 = dplyr::select(.data = loanfile,loan_status,loan_amnt,int_rate,term,installment,grade,emp_length,annual_inc,dti,sub_grade,verification_status,home_ownership,pymnt_plan)
loanfilev2$grade = as.factor(loanfilev2$grade)
loanfilev2$sub_grade <- as.factor(loanfilev2$sub_grade)
loanfilev2$term <- as.factor(loanfilev2$term)
loanfilev2$emp_length <- as.factor(loanfilev2$emp_length)
loanfilev2$verification_status <- as.factor(loanfilev2$verification_status)
loanfilev2$home_ownership <- as.factor(loanfilev2$home_ownership)
loanfilev2$pymnt_plan <- as.factor(loanfilev2$pymnt_plan)
loanfilev2$loan_status <- as.factor(loanfilev2$loan_status)
loanfilev2$grade <- as.numeric(loanfilev2$grade)
loanfilev2$sub_grade <- as.numeric(loanfilev2$sub_grade)
loanfilev2$term <- as.numeric(loanfilev2$term)
loanfilev2$emp_length <- as.numeric(loanfilev2$emp_length)
loanfilev2$verification_status <- as.numeric(loanfilev2$verification_status)
loanfilev2 <- loanfilev2[complete.cases(loanfilev2),]
set.seed(69)
train_index <- sample(seq_len(nrow(loanfilev2)), size = 5000)
TrainData<- loanfilev2[train_index, ]
ct = ctree(loan_status ~ ., data = TrainData)
dl <- glm(formula = loan_status ~ .,data = loanfilev2, family = binomial)
kn <- train(form = loan_status ~.,data = TrainData, method = 'knn')
shinyServer(function(input, output) {
loan_status <- c(0)
loan_amnt <- input$loan_amnt
int_rate <- input$int_rate
term <- input$term
installment <- input$installment
grade <- input$grade
emp_length <- input$emp_length
annual_inc <- input$annual_inc
dti <- input$dti
sub_grade <- input$sub_grade
verification_status <- input$verification_status
home_ownership <- input$home_ownership
pymnt_plan <- input$pymnt_plan
temp2 <- cbind(loan_status, loan_amnt, int_rate, term, installment, grade, emp_length, annual_inc, dti, sub_grade, verification_status, home_ownership, pymnt_plan)
loanfilev3 = dplyr::select(.data = loanfile,loan_status,loan_amnt,int_rate,term,installment,grade,emp_length,annual_inc,dti,sub_grade,verification_status,home_ownership,pymnt_plan)
loanfilev3 = rbind(loanfilev3, temp2, deparse.level = 0)
loanfilev3$grade = as.factor(loanfilev3$grade)
loanfilev3$sub_grade <- as.factor(loanfilev3$sub_grade)
loanfilev3$term <- as.factor(loanfilev3$term)
loanfilev3$emp_length <- as.factor(loanfilev3$emp_length)
loanfilev3$verification_status <- as.factor(loanfilev3$verification_status)
loanfilev3$home_ownership <- as.factor(loanfilev3$home_ownership)
loanfilev3$pymnt_plan <- as.factor(loanfilev3$pymnt_plan)
loanfilev3$loan_status <- as.factor(loanfilev3$loan_status)
loanfilev3$grade <- as.numeric(loanfilev3$grade)
loanfilev3$sub_grade <- as.numeric(loanfilev3$sub_grade)
loanfilev3$term <- as.numeric(loanfilev2$term)
loanfilev3$emp_length <- as.numeric(loanfilev3$emp_length)
loanfilev3$verification_status <- as.numeric(loanfilev3$verification_status)
loanfilev3 <- loanfilev3[complete.cases(loanfilev3),]
prediction1 = c(predict(object = ct, newdata = loanfilev3[886508], type = "prob"))
output$ct <- renderPrint({
as.data.frame(prediction1)[2,]*100
})
})

Answer 1

All input bindings (input$whatever) need to be used in reactive context for example: inside reactive() or observe or renderXXX etc. In your case you are doing stuff like loan_amnt <- input$loan_amnt outside of reactive context and that's what the error is about. See my update below. I have added your prediction model to an eventReactive that is triggered by some action button input$predict.
# add this button somewhere in your ui.R -
actionButton("predict", "Predict!")
update to server.R -
shinyServer(function(input, output) {
prediction <- eventReactive(input$predict, {
loan_status <- c(0)
loan_amnt <- input$loan_amnt
int_rate <- input$int_rate
term <- input$term
installment <- input$installment
grade <- input$grade
emp_length <- input$emp_length
annual_inc <- input$annual_inc
dti <- input$dti
sub_grade <- input$sub_grade
verification_status <- input$verification_status
home_ownership <- input$home_ownership
pymnt_plan <- input$pymnt_plan
temp2 <- cbind(loan_status, loan_amnt, int_rate, term, installment, grade, emp_length, annual_inc, dti, sub_grade, verification_status, home_ownership, pymnt_plan)
loanfilev3 = dplyr::select(.data = loanfile,loan_status,loan_amnt,int_rate,term,installment,grade,emp_length,annual_inc,dti,sub_grade,verification_status,home_ownership,pymnt_plan)
loanfilev3 = rbind(loanfilev3, temp2, deparse.level = 0)
loanfilev3$grade = as.factor(loanfilev3$grade)
loanfilev3$sub_grade <- as.factor(loanfilev3$sub_grade)
loanfilev3$term <- as.factor(loanfilev3$term)
loanfilev3$emp_length <- as.factor(loanfilev3$emp_length)
loanfilev3$verification_status <- as.factor(loanfilev3$verification_status)
loanfilev3$home_ownership <- as.factor(loanfilev3$home_ownership)
loanfilev3$pymnt_plan <- as.factor(loanfilev3$pymnt_plan)
loanfilev3$loan_status <- as.factor(loanfilev3$loan_status)
loanfilev3$grade <- as.numeric(loanfilev3$grade)
loanfilev3$sub_grade <- as.numeric(loanfilev3$sub_grade)
loanfilev3$term <- as.numeric(loanfilev2$term)
loanfilev3$emp_length <- as.numeric(loanfilev3$emp_length)
loanfilev3$verification_status <- as.numeric(loanfilev3$verification_status)
loanfilev3 <- loanfilev3[complete.cases(loanfilev3),]
predict(object = ct, newdata = loanfilev3[886508], type = "prob"))
})
output$ct <- renderPrint({
as.data.frame(prediction())[2,]*100
})
})