gistfile1.r

install.packages('stargazer')

# states <- state.name
states <- rep(state.name,2)
# states <- rep(2,state.name)
# states1 <- rep(x=state.name,times=2)
# states2 <- rep(times=2,x=state.name)
# states1==states2
variable <- c(rep('x',50),rep('y',50))

# Two vectors (2010,2011) of length 100,
# composed of random numbers between 1 and 1000.

X2010 <- sample(1:1000,100)
X2011 <- sample(500:1000,100)

df <- data.frame(X2010,X2011,states,variable)

df1 <- df[df$variable=='x',]
df2 <- df[df$variable=='y',]

df <- rbind(df1,df2)

# Generate a vector (X2012) of length 100 with random 
# values taken from a normal distribution with mean 100,
# and a standard deviation of 10.

X2012 <- rnorm(100,mean=100,sd=10)

df <- cbind(df,X2012)

# Make df$X2012 an integer vector by rounding to whole
# numbers.

df$X2012 <- as.integer(df$X2012)

# Change df to long form like on the board. Don't forget
# to change the year values so that X2012 equals
# 2012, X2010 equals 2010 etc. Use melt and cast (dcast)
# in reshape2. Look at last week's work or google. Check
# the structure (str()) of the final data frame to make
# sure everything makes sense (year should be integer).
# Ways to change X2012 to 2012 -- substr() or gsub().

df <- melt(df,id.vars=c('states','variable'))
# names(df) <- c('states','variable','year','value')
names(df)[3] <- 'year'
df$year <- substr(df$year,2,5)
# df$year <- gsub('X','',x=df$year)
df <- dcast(df,states + year ~ variable)
df$x <- as.integer(df$x)
df$y <- as.integer(df$y)
hist(df$x)
library(ggplot2)
ggplot(data=df,aes(x=x,y=y)) + geom_point()
m <- lm(y ~ x,data=df)


summary(m)

install.packages('stargazer')
library(stargazer)

stargazer(m,type='html',out='test.html')
stargazer(m,type='text')