steadyfish

This method helps creating the proper R package directory structure using RStudio and then syncs it with the corresponding GitHub Project. 

Sources: 
http://www.molecularecologist.com/2013/11/using-github-with-r-and-rstudio/
https://support.rstudio.com/hc/en-us/articles/200532077-Version-Control-with-Git-and-SVN
http://r-pkgs.had.co.nz/git.html


Setup a GitHub account.
Download and install Rstudio.

steadyfish

# using dplyr finctions in non-interactive mode
# examples

library(plyr)
library(dplyr)

d1 = data_frame(x = seq(1,20),y = rep(1:10,2),z = rep(1:5,4))
head(d1)

#### single table verbs ####

steadyfish

####Download the data from Government of India open data portal#####
w_dir = getwd()
source(file=file.path(w_dir,"Code/Core.R"))
checkAndDownload(c("XML","RCurl","RJSONIO","plyr"))

### Alternative - 1: Using APIs ###
#JSON#
getJSONDoc <- function(link, res_id, api_key, offset, no_elements){
  jsonURL = paste(link,
                  "resource_id=",res_id, 

steadyfish

######## Packages ########
checkAndDownload<-function(packageNames) {
  for(packageName in packageNames) {
    if(!isInstalled(packageName)) {
      install.packages(packageName,repos="http://lib.stat.cmu.edu/R/CRAN") 
    } 
    library(packageName,character.only=TRUE,quietly=TRUE,verbose=FALSE)
  }
}