aagarw30

Title: Use case - Change the side bar panel elements based on the selected tab & demo conditionalPanel() function
Description: Powered by R, Shiny, GGPLOT2 and RStudio.
License: GPL-3
Author: Abhinav Agrawal
DisplayMode: Showcase
Tags: R, R Shiny,TabsetPanel, ConditionalPanel
Type: Shiny

aagarw30

library(shiny)

ui <- fluidPage(
  
tags$div(sliderInput("slide1", "Slider1", min = 0, max=10, value=4),  style="display:inline-block"),
  tags$div(sliderInput("slide1=2", "Slider2", min = 0, max=10, value=4),  style="display:inline-block"),
  tags$div(sliderInput("slide3", "Slider3", min = 0, max=10, value=4),  style="display:inline-block")

)

aagarw30

## Load required packages

library(plotly)
library(ggplot2)
library(shiny)

## Defining a key column in mtcars which will be used for event handling in event_data()
mtcars$key <- row.names(mtcars)

aagarw30

library(shiny)

ui <- fluidPage(
  # Upload zip files
  fileInput("file", "Upload Zip file", accept = ".zip"),
  # action button to unzip the file
  actionButton("unzip", "Unzip Files"),
  
  # to display the metadata of the zipped file
  tableOutput("filedf"),

aagarw30

# Demonstration of ggcorrplot package 
# Package created by Alboukadel Kassambara
# Reference link - https://cran.r-project.org/web/packages/ggcorrplot/ggcorrplot.pdf


# Load the required libraries
# install.packages("ggcorrplot")
library(ggcorrplot)

# mtcars dataset from base R used here for demonstration

aagarw30

Title: Use case - Demo updateselectInput() and also introducing observeEvent() function
Description: Powered by R, Shiny, and RStudio.
License: GPL-3
Author: Abhinav Agrawal
DisplayMode: Showcase
Tags: R, R Shiny,updateselectInput(), observeEvent()
Type: Shiny

aagarw30

#### Brief introduction to R Plotly package ####
# The plotly package in R is an interface to open source Javascript charting library plotly.js
# Plots can be created online in the plotly web GUI or offline using the plotly package
# Interactive plots that can be easily shared online using the plotly API/account
# Plotly plots can embed into R Markdown, R Shiny
# Tool tip feature and other controls
# ggplot2 graphs can be easily converted to interactive plotly objects using ggplotly() function

# Package documentation
# https://cran.r-project.org/web/packages/plotly/plotly.pdf

aagarw30

library(shiny)

ui <- fluidPage(
  radioButtons(inputId = "plot_type" , label = "Select the plot", choices = c("scatter", "bar", "hist" )),
  plotOutput("myplot")
  
)

server <- function(input, output, session) {
  

aagarw30

# Demo example for reactiveVal with observeEvent()
# Create dependency on a button to reflect user input changes to the rendered output 
library(shiny) # for Shiny components
library(dplyr) # for piping

my = mtcars %>% 
  mutate(cyl = as.factor(cyl))

ui <- fluidPage(
  h4("Demo of using reactiveVal() along with observeEvent() in R Shiny to subset data and display on click of action Button"),

aagarw30

# Demo example for eventReactive()
# Create dependency on a button to reflect user input changes to the rendered output 
# subset data on click of button and display the resultant data

# Load the required libraries
library(shiny) # for Shiny components
library(dplyr) # for piping and data manipulation

# For demo using the mtcars dataset
# convert the cylinder variable to factor type