.Rapp.history

## #
## Module 1 Homework: an example of visualization in the #
## feedback loop#
###
# load libraries#
#
library(ggplot2)#
library(plyr)
setwd("/Users/JL/Box Sync/CUNY/CUNY_IS608")
inc <- read.csv("lecture1/data/inc5000_data.csv", header= TRUE)
head(inc)
summary(inc)
summary(inc[,c(3:6,8)])
all_inc <- inc[complete.cases(inc)==TRUE,]
all_inc
cnt <- ddply(all_inc, .(State), summarize, cnt = length(State))
cnt
p <- ggplot(cnt, aes(x=State, y=cnt)) + geom_bar(stat='identity')
p
p <- ggplot(cnt, aes(x=State, y=cnt)) + geom_bar(stat='identity')
p + coord_flip()
ny <- subset(all_inc, State == 'NY')
p <- ggplot(ny, aes(x=Industry, y=Employees)) + geom_point()
p <- ggplot(ny, aes(x=Industry, y=Employees)) + geom_point()
p + coord_flip()
winsor <- function(x, bot, top)  { return(min(top, max(x, bot))) }
ny$clip_employ <- sapply(ny$Employees, winsor, bot=0, top =2500)
p3 <- ggplot(ny, aes(x=Industry, y=clip_employ))
p3 + geom_point() + coord_flip()
p3 + geom_boxplot() + coord_flip(ylim=c(0,2500))
p3 + geom_boxplot() + coord_flip(ylim=c(0,2500)) +#
  annotate('text', label= c('outliers','3,000','10,000','32,000'),#
           x = c(18,16,5,2), y=c(2300,2400,2400,2400), size=c(4,3,3,3))
# look at ranges and averages#
ny_ave <- ddply(ny, .(Industry), summarize,#
                mean <- mean(Employees),#
                sd <- sd(Employees),#
                median <- median(clip_employ),#
                lower <- quantile(clip_employ)[2],#
                upper <- quantile(clip_employ)[4]  #
              )
names(ny_ave) <- c('Industry', 'mean', 'sd', 'median', 'lower', 'upper')#
#
head(ny_ave,2)#
#
# show point ranges#
p4 <- ggplot(ny_ave, aes(x=Industry, y=median)) + geom_point()
p4 <- p4 + geom_pointrange(ymin=ny_ave$lower, ymax=ny_ave$upper) #
p4 + ylim(c(0,750)) + coord_flip()
p5 <- ggplot(ny_ave, aes(x=Industry, y=median)) + geom_bar(stat='identity')#
p5 <- p5 + geom_errorbar(ymin=ny_ave$lower, ymax=ny_ave$upper, width=.1, color='red') #
p5 + ylim(c(0,750)) + coord_flip()
# investor info#
all_inc$rev_per_employ <- all_inc$Revenue / all_inc$Employees#
p6 <- ggplot(all_inc, aes(x=Industry, y=rev_per_employ))#
p6 + geom_boxplot() + coord_flip()