cdesante

   Coin <- c()
   Die <- c()

for (i in 1:1000) {
Coin[i] <- sample(c("Heads", "Tails"), 1)
Die[i] <- sample(c(1,2,3,4,5,6), 1)
  }
  
  table(Coin, Die)
  

cdesante

#Load ggplot default data: Diamonds
  library(ggplot2)
  library(gridExtra)
data(diamonds)
head(diamonds)
diamonds <-     diamonds[diamonds$color < "J",]
#http://127.0.0.1:25615/library/ggplot2/html/diamonds.html


B1 <- ggplot(data = diamonds ) + geom_point(aes( x = carat, y = price, color=color)

cdesante

#Load ggplot default data: Diamonds
  library(ggplot2)
  library(gridExtra)
data(diamonds)
head(diamonds)
diamonds <-     diamonds[diamonds$color < "J",]
#http://127.0.0.1:25615/library/ggplot2/html/diamonds.html

cdesante

#Load ggplot default data: Diamonds
library(ggplot2)
library(gridExtra)
data(diamonds)
head(diamonds)
diamonds <-     diamonds[diamonds$color < "J",]
#http://127.0.0.1:25615/library/ggplot2/html/diamonds.html

#Random Colors
my.colors <- sample(colors(), 7)

cdesante

X <- c(1)
Y <- c(1)

DF <- as.data.frame(cbind(X,Y))
c.1 <-  ggplot(data = DF) + geom_bar(aes(x = X, y = Y, fill = factor(X)))  + coord_flip()   +  theme(legend.position="none") + labs(x="", y="", title="One Colour") + scale_y_continuous(breaks=NULL, expand=c(0,0)) + scale_x_continuous(breaks=NULL, expand=c(0,0))

X <- c(1:2)
Y <- rep(1, length(X))
DF <- as.data.frame(cbind(X,Y))

cdesante

Con1 <- ggplot(data = DF) + geom_pointrange(aes(x = year, y = means, 
                     ymin = lows, ymax = highs, colour=factor(dems)) )
Con1 <- Con1 + ylim(0.5,2.5)  + labs(title="geom_pointrange")
 Con1
 Con2 <- ggplot(data = DF) + geom_errorbar(aes(x = year, y = means, 
             ymin = lows, ymax = highs, colour=factor(dems), width=.5) )
Con2 <- Con2 + ylim(0.5,2.5) + labs(title="geom_errorbar, width=.5")
  Con2
 Con3 <- ggplot(data = DF) + geom_errorbar(aes(x = year, y = means,
          ymin = lows, ymax = highs, colour=factor(dems), width=.75), lty=2 )

cdesante

#######################################################
# Example 4: Casting/Melting with custom functions    #
#######################################################

#Let's first define a function, SE, to represent the standard error of a
#variable:
library(gridExtra)
library(ggplot2)
SE <- function(X) {
(sd(X, na.rm=TRUE)/ sqrt(length(X)-1)  )

cdesante

#Day 1/10: using Reshape
#Christopher DeSante, Ph.D.
ANES <- read.csv("http://www.oberlin.edu/faculty/cdesante/assets/downloads/ANES.csv")
head(ANES)
ANES$caseid <- 1:dim(ANES)[1]
head(ANES)
dim(ANES)
#Melting...
#Essentially reshapes the data into a new DF based on
#whichever variables you specify in the id="" option;

cdesante

head(ANES)
party.gender.region <- ANES[,c(1, 4, 12, 16)]
head(party.gender.region)
       #Note the additional changes to our id=():
party.gender.region.year <- melt(party.gender.region, 
                   id=c("year", "female", "south"), na.rm=TRUE)
head(party.gender.region.year)
       #Note the additional changes to our formula (below):
party.gender.region.time  <- (cast(party.gender.region.year,
                   year+female+south~variable, mean, na.rm=T) )

cdesante

head(ANES)
party.and.region <- ANES[,c(1, 12, 16)]
head(party.and.region)
   #Note the additional changes to our id=():
party.and.region.year <- melt(party.and.region, id=c("year", "south"), na.rm=TRUE)
head(party.and.region.year)
   #Note the additional changes to our formula (below):
party.region.time  <- (cast(party.and.region.year, year+south~variable, 
                             mean, na.rm=T) )
party.region.time