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library(igraph)
library(plotly)
library(plyr)
library(curl)


G <- read.graph("dolphins.gml", format = c("gml"))
L <- layout_nicely(G)

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#marker size
#need plyr loaded
size<-count(es$V2)
size<-rename(size,c("x"="V2"))
es<-join(es,size, by='V2', type="left")

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library(ggplot2)
library(ggthemes)
library(plyr)
library(rvest)

ice_cream <- read_html("http://future.aae.wisc.edu/data/annual_values/by_area/2252?tab=sales")
ice_table <- ice_cream %>%
  html_nodes('table') %>%
  html_table(fill=TRUE)

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stats<-data.frame(ice_table[2])
stats$Year<-as.character(stats$Year)

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ggplot(stats, aes(x=Year, y=Value)) + theme_tufte(base_size=14, ticks=F) +
  geom_bar(width=0.25, fill="gray", stat = "identity") +  theme(axis.title=element_blank()) +
  geom_hline(yintercept=seq(5, 20, 5), col="white", lwd=1) +
  annotate("text", x = 20, y = 18, adj=1,  family="serif",
           label = c("Per Capita\n U.S. Frozen Dairy\n Product Consumption\n (Annual)"))

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library(ggplot2)
library(directlabels)
#plot
ggplot(summary, aes(x=Year, y=mean, col=Region))+geom_line(alpha=.45,size=.75)+ theme_tufte( ticks=F)+
  geom_vline(xintercept=advances$Year, col="light gray",alpha=.35 ,lwd=1 )+
  theme(legend.position="none")+
  ylab("Mean Life Expectancy")+
  geom_dl(aes(label = Region), method = list(dl.combine( "last.points"), cex = 0.6))+ 
  geom_text(aes(x=1799, label="Vaccines", y=20 ), colour="gray", angle=270)+
  geom_text(aes(x=1849, label="Surgical Anesthetic", y=21), colour="gray", angle=270) +

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library(dplyr)
library(ggplot2)
library(viridis)
library(ggthemes)

#import all the files
temp <- list.files(pattern="*.csv")
alldata <- do.call(rbind, lapply(temp, function(x) read.csv(x, stringsAsFactors = FALSE)))
alldata$day <- strptime(alldata$starttime, format = "%m/%d/%Y")
alldata$day <- as.character(alldata$day)

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rides.raw<-aggregate(alldata$trip_id ,by=list(alldata$day),length)

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rides.raw$Group.1<-as.Date(rides.raw$Group.1,format='%m/%d/%Y')
rides.raw$days<-factor(weekdays(rides.raw$Group.1,T),levels = rev(c("Mon", "Tue", "Wed", "Thu","Fri", "Sat", "Sun")))
rides.raw$week<-as.numeric(format(rides.raw$Group.1,"%W"))
rides.raw$month<-as.numeric(format(rides.raw$Group.1,"%m"))
rides.raw$year<-as.numeric(format(rides.raw$Group.1,"%Y"))

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ggplot(rides.raw, aes(x = week, y = days, fill = x)) +
    scale_fill_viridis(name="Divvy Rides",option = "C", limits = c(0, max(rides.raw$x))) + 
    geom_tile(color = "white", size = 0.4)+facet_wrap("year", ncol = 1) + 
    scale_x_continuous(expand = c(0, 0), breaks = seq(1, 52, length = 12), 
    labels = c("Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"))+
    theme_tufte()