shiny

library(shiny)
library(DT) 
library(tidyverse)  
library(jsonlite)   
library(httr)       

# Define UI for application that draws a histogram
ui <- fluidPage(
    # Application title
    titlePanel("Sentiment Analysis"),
    # Sidebar with a slider input for number of bins 
    sidebarLayout(
        sidebarPanel(
            textInput("caption", label="Enter your text here.", value="", placeholder = "Phrase to get a Sentiment..."),
            verbatimTextOutput("value"),
            # Input: Select a file ----
            fileInput("file1", "upload csv file here",
                    multiple = FALSE,
                    accept = c("text/csv",
                                "text/comma-separated-values,text/plain",
                                ".csv")), 
            # Button
            downloadButton("downloadData", "Download the Predictions")
        ),
        # Show the table with the predictions
        mainPanel(
            verbatimTextOutput("Sentiment"),
            DT::dataTableOutput("mytable")
        )
    )
)

# Define server logic required to draw a histogram
server <- function(input, output) {
    reactiveDF<-reactive({
        req(input$file1)
        df <- read.csv(input$file1$datapath, sep="\t", stringsAsFactors = FALSE) 
        url="http://127.0.0.1:5000/endpoint"
        fdf<-NULL
        for (i in 1:nrow(df)) {
            body<-list(my_text=df[i,1])
            b<-POST(url, body = body, encode = "json")
            t1<-content(b, type="application/json")
            tmpdf<-data.frame(InputText=df[i,1], Sentiment=t1$output)
            fdf<-rbind(fdf, tmpdf)                   
        }
        return(fdf)   
    })
    
    output$mytable <- DT::renderDataTable({
        req(input$file1)
        return(DT::datatable(reactiveDF(),  options = list(pageLength = 100), filter = c("top")))
    })
    
    reactiveInput<-reactive({
        req(input$caption)
        url="http://127.0.0.1:5000/endpoint"
        body<-list(my_text=input$caption)
        b<-POST(url, body = body, encode = "json")
        t1<-content(b, type="application/json")
        df<-data.frame(Sentiment=t1$output)
        return(df)
    })
    output$Sentiment<-renderText({
        req(input$caption)
        reactiveInput()$Sentiment 
    })
    # Downloadable csv of selected dataset ----
    output$downloadData <- downloadHandler(
        filename = function() {
            paste("data-", Sys.Date(), ".csv", sep="")
        },
        content = function(file) {
            write.csv(reactiveDF(), file, row.names = FALSE)
        }
    )   
}

# Run the application 
shinyApp(ui = ui, server = server)

---
title: "EDA Dashboard"
output: 
flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
runtime: shiny
---

```{r setup, include=FALSE}
library(flexdashboard)
library(shiny)
library(dplyr)
library(plotly)
```


```{r data}

data <- read.csv("BankChurners.csv")

Categorical.Variables = c("Gender", "Education_Level", "Marital_Status")

Numeric.Variables = c("Customer_Age", "Total_Trans_Ct", "Credit_Limit")

```


Column {.sidebar data-width=200}
-------------------------------------------------------------------
```{r}

selectInput(inputId="categorical_variable", label = "Select Categorical Variable:", choices = Categorical.Variables, selected = Categorical.Variables[1])

selectInput(inputId="numeric_variable", label = "Select Numeric Variable:", choices = Numeric.Variables, selected = Numeric.Variables[1])

```

Column {data-width=400}
-------------------------------------------------------------------

### **Box plot** shows the relationship between categorical and numeric variables
```{r}

renderPlotly({
plot_ly(data,
            x = ~data[[input$numeric_variable]],
            color = ~data[[input$categorical_variable]],
            colors = "Paired",
            type = "box") %>%
layout(title = "",
        xaxis = list(title = "" ,
                    zeroline = FALSE))
})
```

Column {data-width=400}
-------------------------------------------------------------------

### **Bar chart** shows the distribution of categorical veriable
```{r}

renderPlotly({
data %>%
    count(var = data[[input$categorical_variable]], name = "count") %>%
    plot_ly( x = ~var, y = ~ count, type = "bar", marker = list(color = '#008ae6',
                        line = list(color = '#008ae6', width = 2)), hoverinfo = "x+y") %>%
    add_text(text = ~paste0( " (",   scales::percent(count/sum(count)),")"), 
        textposition = "bottom", 
        textfont = list(size = 12, color = "white"), 
        showlegend = FALSE) %>%
    layout(xaxis = list(title = ""), yaxis = list(title = ""))
    
})
```

### **Histogram** shows the distribution of numeric variable
```{r}

renderPlotly({
plot_ly(x = data[[input$numeric_variable]], type = "histogram",  marker = list(color = "#008ae6",
                            line = list(color = "darkgray",
                                        width = 1)))
})
```