# Five Fast Things You Can Do With R
  # PREPARATION ------------------------------------------------------------
  # 1. Insure this file, glass.data, glass.names, winequality-white.cvs, 
       # winequality.names and BBands.R are on the desktop
  # 2. Open firefox to http://www.r-project.org, second tab to home
  # 3. rm .RData on Desktop
  # 4. Open this file, winequality-white.cvs, glass.data and BBands.R in Text Editor
  # 5. cd Desktop
  # 6. start R (type R)

  # SUB-TOPICS --------------------------------------------------------------
  # Expain Easy / Hard / Very Powerful
  # Explain Overloading functions
  
  
=============================================================================
# WHAT IS R? ================================================================
  http://www.r-project.org/  # look at the site

# WHAT I AM GOING TO TALK ABOUT =============================================
  1. gathering and reviewing data
  2. calculating statistics
  3. visualizing data (and stats)
  4. modeling
  5. scripting, an example
=============================================================================


# GATHER DATA (and Review) =================================================
  # WINE and GLASS ---------------------------------------------------------

  # Gather Data ------------------------------------------------------------
  wine <- read.csv("winequality-white.csv", sep=";", header=TRUE)
  glass <- read.csv("glass.data", header = FALSE)

  # Review Data ------------------------------------------------------------

  # Review Data High Level -------------------------------------------------
  str(wine)   # all numbers, integers and rational numbers
  str(glass)  # all numbers, integers and rational numbers

  # Review Data Secific Ranges ---------------------------------------------
  wine[1:10, ]   # Review the first 10 observations

  glass[1:20, ]   # Review the first 20 observations
  glass[1:20, -3] # Review the first 20 observations, less 3rd column
  glass[1:20, c(-3, -5)]  # Review the first 20 observations, less 3rd and 5th  columns


# CALCULATE STATISTICS  ==================================================

  # Individual Statistics ------------------------------------------------

  mean(wine)   # individual statistic, but with Error Message!
  mean(glass)  # individual statistic, but with Error Message!

  colMeans(wine)   # individual statistic, better method
  colMeans(glass)  # individual statistic, better method

  sd(wine)     # individual statistic, but with Error Message!
  sd(glass)    # individual statistic, but with Error Message!

  sapply(wine, sd)    # individual statistic, better method
  sapply(glass, sd)   # individual statistic, better method

  max(wine)    # individual statistic for entire dataframe
  max(wine[,1])  # individual statistic for one column / varriable 
  min(glass)   # individual statistic


  # Summarized Statistics ------------------------------------------------
  summary(wine)    # statistics summarized
  summary(glass)   # statistics summarized

  # More Detailed Statistics ---------------------------------------------
  library("pastecs")  # load library

  stat.desc(wine)            # generate detailed statistics
  stat.desc(glass[, 1:5])    # easier to read


# VISUALIZE DATA =========================================================

  # Summarized Plots -----------------------------------------------------
  pairs(wine)  # SPLOM 
  pairs(glass) # SPLOM 

  pairs(wine[, 1:5])    # for better viewing SPLOM
  pairs(glass[, 1:5])   # for better viewing SPLOM

  # Individual Scatter Plots ----------------------------------------------
  plot(glass$V2, glass$V8)
  plot(wine[, c(6, 7)])

  # Histograms Plots --	----------------------------------------------------
  hist(wine$density)
  hist(glass$V2)

  # Box Plots ---------------------------------------------------------------
  boxplot(glass$V2)  # one variable
  boxplot(glass)     # all at once
  boxplot(glass[,c( -1, -6)])  # remove two columns

  # Full Demo ---------------------------------------------------------------
  demo(graphics)  # built-in graphics demo
  demo(persp)  # built-in perspective graphics demo

  library(lattice)  # load pacakge
  demo(lattice)

 
# MODELING ===================================================================
  # Simple Example-------------------------------------------------------------
  plot(wine[, c(7, 6)])  # plot one variable against another
  lmwine <- lm(wine[, c(6, 7)])  # make a linear model
  abline(lmwine, col="red")   # plot that model

  # Fuller Example-------------------------------------------------------------
  plot(wine[, c(1,6,8,9)])  # plot four variables against one another

  # Fullest Example -----------------------------------------------------------
  library(psych)  # load a package
  wineSample <- wine[c(1,6,8,9)]  # look at a sub-sample
  pairs.panels(wineSample, lm=TRUE)


# SCRIPTING =================================================================
  source("BBands.R")  # load an executable file and run it