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#get very helpful Ken French data
#for this project we will look at Global Factors
#http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/Global_Factors.zip

require(PerformanceAnalytics)
require(quantmod)
require(RColorBrewer)


#my.url will be the location of the zip file with the data

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library(ggplot2)
library(colorRamps)

TawiTawiPop <- c(17000, 45000, 46000, 59000, 79000, 110000, 143000, 195000, 228204,
                 250718, 322317, 450346, 366550)
YearNames <- c("1903", "1918", "1939", "1948", "1960", "1970", "1975", "1980", "1990",
               "1995", "2000", "2007", "2010")

qplot(YearNames, TawiTawiPop, 
      xlab = expression(bold("Censal Year")), 

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source('pubmed_trend.r')
sex.pub <- pubmed_trend(search.str = 'Sex+Characteristics[mh] AND Pain[mh]', year.span=1970:2011)
analgesic.pub <- pubmed_trend(search.str = 'Sex+Characteristics[mh] AND Analgesics[mh]', year.span=1970:2011)

source('plot_bar.r')
library("RColorBrewer")

pdf(file='sex_pain.pdf', height=8, width=8)
par(las=1)
colorfunction = colorRampPalette(brewer.pal(9, "Reds"))

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library(ggplot2)
library(colorRamps)

IliganCity <- c(104493, 118778, 167358, 226568, 273004, 285061, 308046, 322821)
CensalYear <- c("1970", "1975", "1980", "1990", "1995", "2000", "2007", "2010")

qplot(CensalYear, IliganCity, xlab = expression(bold("Censal Year")),
      ylab = expression(bold("Population")), geom = "bar", colour = I("red"), 
      fill = IliganCity, stat = "identity", ylim = c(0, 370000)) + theme_bw() + 
      opts(

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This post examines the features of [R Markdown](http://www.rstudio.org/docs/authoring/using_markdown) 
using [knitr](http://yihui.name/knitr/) in Rstudio 0.96.
This combination of tools provides an exciting improvement in usability for 
[reproducible analysis](http://stats.stackexchange.com/a/15006/183).
Specifically, this post 
(1) discusses getting started with R Markdown and `knitr` in  Rstudio 0.96;
(2) provides a basic example of producing console output and plots using R Markdown;
(3) highlights several code chunk options such as caching and controlling how input and output is displayed;
(4) demonstrates use of standard Markdown notation as well as the extended features of formulas and tables; and 
(5) discusses the implications of R Markdown.

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`r opts_chunk$set(cache=TRUE)`

This is a quick set of analyses of the California Test Score dataset.  The post was produced using R Markdown in RStudio 0.96.  The main purpose of this post is to provide a case study of using R Markdown to prepare a quick reproducible report.  It provides examples of using plots, output, in-line R code, and markdown. The post is designed to be read along side the R Markdown source code, which is available as a gist on github. 

<!-- more -->

### Preliminaries
* This post builds on my earlier post which provided a guide for [Getting Started with R Markdown, knitr, and RStudio 0.96](jeromyanglim.blogspot.com/2012/05/getting-started-with-r-markdown-knitr.html)
* The dataset analysed comes from the `AER` package which is an accompaniment to the book [Applied Econometrics with R](http://www.amazon.com/Applied-Econometrics-R-Use/dp/0387773169) written by [Christian Kleiber](http://wwz.unibas.ch/personen/profil/person/kleiber/) and [Achim Zeileis](http://eeecon.uibk.ac.at/~zeileis/

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\documentclass{article}
%great guides at epslatex.pdf
%check miniplot for potential use

\usepackage{graphics}
\usepackage{caption}
%\usepackage{sidecap}
%\usepackage{textpos}
\usepackage[section]{placeins}

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Interactive charts and slides with R, googleVis and knitr
========================================
```{r results='asis', echo=FALSE, message=FALSE, tidy=FALSE}
library(googleVis)
G <- gvisGeoChart(Exports, "Country", "Profit", 
                  options=list(width=250, height=120), chartid="c1")

T <- gvisBarChart(Exports[,1:2], yvar="Profit", xvar="Country",                  
                  options=list(width=250, height=260, 
                               legend='none'), chartid="c2")

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\documentclass[nohyper,justified]{tufte-handout}
%\documentclass{article}
%great guides at epslatex.pdf
%check miniplot for potential use

%\usepackage{graphics}
%\usepackage{caption}
%\usepackage{sidecap}
%\usepackage{textpos}
%\usepackage[section]{placeins}

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# Script name: instant_pkgs.R
# Purpose: Package installation and loading
# Author: Kay Cichini
# Date: 2012-06-19
# Licence: cc by-nc-sa

instant_pkgs <- function(pkgs) { 
    pkgs_miss <- pkgs[which(!pkgs %in% installed.packages()[, 1])]
    if (length(pkgs_miss) > 0) {
        install.packages(pkgs_miss)