jtleek

## Load libraries
library(XML)
library(dplyr)
library(RCurl)

## Get the results for a specific term
scrape_term = function(search_term,npages){
  base_url = "http://scholar.google.com/scholar?"
  search_string = paste0("q=",paste0(strsplit(search_term," ")[[1]],collapse="+"))
  dat = data.frame(NA,nrow=10*npages,ncol=3)

jedifran

#get very helpful Ken French data
#for this project we will look at Industry Portfolios
#http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/48_Industry_Portfolios_daily.zip

require(latticeExtra)
require(PerformanceAnalytics)
require(quantmod)

#my.url will be the location of the zip file with the data
my.url="http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/48_Industry_Portfolios_daily.zip"

jedifran

#!/usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "Deepak.G.R."
__license__ = 'Public Domain'

"""
usage:
Go to command line and type

python ai-class.py "topic-name"

entaroadun

Movies Recommendation:

• MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
• Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
• Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
• Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html

mbostock

license: gpl-3.0

cboettig

## Credit: Taken from:  http://stackoverflow.com/questions/1358003/tricks-to-manage-the-available-memory-in-an-r-session
# improved list of objects
.ls.objects <- function (pos = 1, pattern, order.by,
                        decreasing=FALSE, head=FALSE, n=5) {
    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)