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library(shiny)
library(dplyr)

server <- function(input, output) {

    output$downloadData <- downloadHandler(
        
        filename = function() {
            paste('data_', Sys.Date(), '.csv', sep='')
        },

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# install.packages("shiny")
# install.packages("miniUI")
# install.packages("ggplot2")
library(shiny)
library(miniUI)
library(ggplot2)

outlier_rm <- function(data, xvar, yvar) {
    
    ui <- miniPage(

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---
title: "RMarkdown(Pandoc(LaTeX))"
author: "VP Nagraj"
date: "March 3, 2016"
output: 
    html_document:
        keep_md: yes
---

```{r, warning=FALSE, message=FALSE}

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# list manipulation workshop
# scratch script
# november 9 2016

#############################################

slamwins <- list(17,14,14,12,11)

#############################################

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# script to demonstrate outbreak animation with a subset of mers_korea_2015 data

# must install github release of threejs package

# devtools::install_github("bwlewis/rthreejs")
library(threejs)
library(outbreaks)
library(dplyr)

# use dplyr to subset results to only include hospital visit exposure

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# script to demonstrate outbreak animation with a subset of mers_korea_2015 data

# must install github release of threejs package

# devtools::install_github("bwlewis/rthreejs")
library(threejs)
library(outbreaks)
library(dplyr)

# use dplyr to subset results to only include hospital visit exposure

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library(ggplot2)
library(tidyr)

dat <- data.frame(x = rnorm(n = 1000, mean = 2.8, sd = 0.05),
                  y1 = sample(64503:73034, size = 1000, replace = TRUE),
                  y2 = sample(18738:19602, size = 1000,  replace = TRUE))

dat %>%
  ggplot() +
  geom_point(aes(x,y1)) +

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# install.packages("babynames")
library(babynames)
# install.packages("tidyverse")
library(tidyverse)
# install.packages("ggplot2")
# install.packages("dplyr")

# let's take a look at the data
babynames %>%
  View()

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---
title: "MOMA"
author: "VP Nagraj"
date: "February 29, 2016"
output: html_document
runtime: shiny
---

The Museum of Modern Art (MOMA) collection database is publicly available via Github: 

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library(microbenchmark)
library(redux)
library(svSocket)

# clear workspace
rm(list = ls())

# set up svSocket
startSocketServer()
con <- socketConnection(host = "localhost", port = 8888, blocking = FALSE)