anarosner

create_relational <- function( df, col, id_col="join_id", join_name="join_name" ) {
	if( !is.factor(df[,col]) )
		df[,col] <- as.factor(df[,col])
	
	df[,id_col] <- unclass( df[,col] )
	join_table <- data.frame( x=attr(unclass(df[,col]),"levels") )
	names(join_table) <- join_name
	join_table[,id_col] <- 1:length(attr(unclass(df[,col]),"levels"))
	join_table[,join_name] <- as.character( join_table[,join_name] )
	return( list(df=df, join_table=join_table) )

anarosner

read.csv.custom <- function(filename) {
      x <- read.csv( filename, stringsAsFactors=F )
      names(x) <- gsub( x=names(x), pattern="[.]", replacement="_" ) 
      return(x)
}

anarosner

list_ftp_contents <- function( url, sep="[\r\n]", fixed=FALSE ) {
  require(RCurl)
  # require(reshape2)
  
  x <- getURL( url, ftp.use.epsv = FALSE, dirlistonly = TRUE )
  y <- unlist( strsplit( x, sep, fixed=fixed ) )
  z <- y[ y!="" ]
  return(z)
}

anarosner

#get a sample data set
boo <- iris
#it's a data.frame
str(boo)

#set some attributes
attributes( boo )$source <- "r datasets package: iris"
attributes( boo )$foo <- c(1,2,3,4,5)

#see all attributes

anarosner

.Rproj.user
.Rhistory
.RData

#ignore temporary/old data
archive/stash
ignore/
temp/

#ignore markdown caches (which can be really large)

anarosner

#code snippet to import/export spatial files to/from r 

library(maptools)
library(rgdal)

# go to http://spatialreference.org/ to find proj4 string if you don't have it


#for importing/exporting esri shapefiles
r_object <- readShapePoly( fn="shapefile_name", proj4string=CRS("sdfsdlfj") )

anarosner

#purling is in the knitr package
library(knitr)


setwd("C:/ALR/Models/boo") #example using local windows directory, can easily switch

#it can be really simple
purl( "script1.Rmd", "script1.R" )
#just specify the rmd filename, then r filename, with extensions

anarosner

#list names and sizes of objects in workspace
#   by default, order by size desc
ls.objects <- function (pos = 1, pattern, alpha=F,head=FALSE, n=10) {
     napply <- function(names, fn) sapply(names, function(x)
          fn(get(x, pos = pos)))
     names <- ls(pos = pos, pattern = pattern)
     obj.class <- napply(names, function(x) as.character(class(x))[1])
     obj.mode <- napply(names, mode)
     obj.type <- ifelse(is.na(obj.class), obj.mode, obj.class)
     obj.size <- napply(names, object.size)