ashutoshnanda

library(shiny)

shinyServer(function(input, output) {
  
  data <- reactive({
    if(input$distribution_type == 1) {
      rnorm(n = 500, mean = input$parameter, sd = 1)
    } else {
      rpois(n = 500, lambda = input$parameter)
    }

ashutoshnanda

3 * 8 / 39
pizza <- 10
pizza
View(pizza)
pizza <- 5
pizza ^ 5
c(1, 7, 13, 10)
c(1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10)
c(1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10)
c(1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1, 7, 13, 10, 1)

ashutoshnanda

shinyServer(function(input, output) {
  output$selectvalue <- renderPrint(
    3 * as.numeric(input$myselectinput) + 5
  )
  output$slidervalue <- renderPrint(
    input$mysliderinput * as.numeric(input$myselectinput)
  )
  output$plot <- renderPlot(
    hist(rnorm(100, mean = input$mysliderinput))
  )

ashutoshnanda

install.packages("ggplot2")
library(ggplot2)
x <- rnorm(50)
x
ggplot() + geom_histogram(aes(x = x))
ggplot() + geom_histogram(aes(x = x), binwidth = 0.1)
x <- rnorm(500)
ggplot() + geom_histogram(aes(x = x), binwidth = 0.1)
length(x)
my.data <- rnorm(1000)

ashutoshnanda

ashutoshnanda

library(dplyr)
library(RSQLite)

#Set up connection to the SQLite database
connection <- dbConnect(RSQLite::SQLite(), dbname = "clinton.sqlite")

#Print all tables
print("Tables")
all_tables <-  dbListTables(connection)
print(all_tables)