RShiny CS2 EDA.Rmd

---
title: "RShiny CS2 EDA"
author: "Max Pagan"
date: "2023-12-06"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
library(shiny)
library(ggplot2)
library(dplyr)
```

```{r shiny}
data <- read.csv("CaseStudy2-data copy 3.csv")
data <- data[, !colnames(data) %in% c("Over18")]
data <- data[, !colnames(data) %in% c("EmployeeCount")]
data <- data[, !colnames(data) %in% c("StandardHours")]
#below is code one could use to turn certain data points to factors - commented out for now

#data$JobSatisfaction <- factor(data$JobSatisfaction)
#data$Education <- factor(data$Education)
#data$EnvironmentSatisfaction <- factor(data$EnvironmentSatisfaction)
#data$JobLevel <- factor(data$JobLevel)
#data$JobInvolvement <- factor(data$JobInvolvement)
#data$PerformanceRating <- factor(data$PerformanceRating)
#data$RelationshipSatisfaction <- factor(data$RelationshipSatisfaction)
#data$StockOptionLevel <- factor(data$StockOptionLevel)
#data$WorkLifeBalance<- factor(data$WorkLifeBalance)
# Define UI
ui <- fluidPage(
  titlePanel("Scatterplot based on JobRole"),
  sidebarLayout(
    sidebarPanel(
      # Dropdown menu for X-axis variable selection
      selectInput("x_variable", "Choose X Variable", choices = colnames(data)),
      # Dropdown menu for Y-axis variable selection
      selectInput("y_variable", "Choose Y Variable", choices = colnames(data))
    ),
    mainPanel(
      # Scatterplot output with jitter
      plotOutput("scatterplot")
    )
  )
)

# Define server logic
server <- function(input, output) {
  # Create scatterplot based on user input
  output$scatterplot <- renderPlot({
    ggplot(data, aes_string(x = input$x_variable, y = input$y_variable, color = "Attrition")) +
      geom_p