amy17519

  output$plotedition <- renderPlotly({
    plot_ly(data = popular_editions, x = Popularity , y = Scarcity, mode = "markers",
            text= paste(Name, "<br>Edition: ", Edition, "<br>Country: ", Country,
                        "<br>City: ",City, "<br>Owner: ",Owner,"<br>Seeker: ",
                        Seeker,"<br>Trader: ",Trader, "<br>Difficulty: ",Difficulty),
            color = Edition, 
            colors = c('olivedrab3','navyblue','indianred2','darkgoldenrod1')) %>%
      layout(title='Collectible Editions: Scarcity vs. Popularity',
             xaxis=list(title='Popularity: Seeker/max(Seeker)'),
             yaxis=list(title='Scarcity: |Owner/max(Owner)-1|'))

amy17519

wss <- (nrow(mug[,7:9])-1)*sum(apply(mug[,7:9],2,var))
for (i in 2:10) wss[i] <- sum(kmeans(mug[,7:9], 
                                     centers=i)$withinss)
plot(1:10, wss, type="b", xlab="Number of Clusters",
     ylab="Within groups sum of squares")
#determines k=5

set.seed(123)
mugCluster <- kmeans(mug[, 7:9], 5, nstart = 100)

amy17519

library(shiny)
library(plotly)
library(dplyr)
library(countrycode)

shinyServer(function(input, output) {
  
  
  chooseMap=function(a){
    switch(a, 

amy17519

user[which(is.na(user$Country)),3]<-'Undefined Country'
user$Country<-tolower(user$Country)
user$City<-tolower(user$City)
user$Country<-recode(user$Country,
                    "c('81250 r.o.c taiwan','台灣','taiwan( r.o.c)','taichung','roc')='taiwan';
                     c('156013 russia ','russia ','россия','russian federation',
                    'russia / austria')='russia';
                    c('america','arizona','california','ap','美國','wa','washington','wisconsin',
                    'アメリカ合衆国','vereinigte staaten','usa / philippines','usa/germany','va',
                    'usa ','usa','us ','united states of america ','united states of america',

amy17519

from bs4 import BeautifulSoup as bs
import re
import requests
import pandas as pd

url_list_user, userName, userCity, userCountry, userMug,userPercent,userTrading,userLooking= ([] for i in range(8))

for i in range(1,438):
	url_list_user.append('http://fredorange.com/users/?&pg=' + str(i))

amy17519

  barInput <- reactive({
    newboroughkid<-boroughkid[,c("Borough",input$yvar)]
    newboroughkid<-newboroughkid[newboroughkid$Borough %in% input$boroughbar,]
    newboroughkid
  })
  
  output$bar <- renderGvis({
    gvisColumnChart(barInput(),options = list(title="Are There Enough Seats at Pre-Kindergartens",hAxes="[{title:'Borough',
                                             titleTextStyle: {color:'blue'}}]"
                                              , vAxes="[{title:'Number of Eligible Kids', 

amy17519

output$table <- renderDataTable(kidtable,
                                  options=list(aLengthMenu = c(15,25,50), 
                                               iDisplayLength = 15,
                                               columnDefs = list(list(width = '160px', targets = c(10,11)),
                                                                 list(width = '120px', targets = c(4,5)),
                                                                 list(width = '200px', targets = 3))))

amy17519

   mapInput <- eventReactive(input$go,{
    newkid<-kid[kid$Borough %in% input$borough & 
                kid$Type %in% input$type & 
                kid$Length %in% input$length,]
    newkid
    })
 
 output$map <- renderLeaflet({
    leaflet(kid) %>%
      addProviderTiles("CartoDB.Positron") %>%

amy17519

##################use address to get long/lat info################
kinder <- read.csv(url("https://github.com/amy17519/NYCPre-KGuide/blob/master/Universal_Pre-K__UPK__School_Locations.csv"), 
                   stringsAsFactors=FALSE)

######paste zipcodes to all addresses to increase accuracy of locating
kinder$address<- paste(kinder$address,kinder$zip)
geo<-geocode(kinder$address) #use geocode from ggmap package to get longtitude/latitude coordinates
geo<-geo[,c(2,1)]   #change col order of long and lat to match convention 

#Find abnormal locations using longitude/latitude boundaries of NYC