{"cells":[
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# This R environment comes with all of CRAN preinstalled, as well as many other helpful packages\n# The environment is defined by the kaggle/rstats docker image: https://github.com/kaggle/docker-rstats\n# For example, here's several helpful packages to load in \n\nlibrary(ggplot2) # Data visualization\nlibrary(readr) # CSV file I/O, e.g. the read_csv function\n\n# Input data files are available in the \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nsystem(\"ls ../input\")\ntrain=read_csv(\"../input/ItemPairs_train.csv\")\nstr(train)\ntrain_info=read_csv(\"../input/ItemInfo_train.csv\")\nstr(training)\nlocation=read_csv(\"../input/Location.csv\")\n\nlibrary(data.table)\ntrain=data.table(train)\ntraining=data.table(training)\n\nsetkey(train,itemID_1)\nsetkey(training,itemID)\nnames(train)[1]<-\"itemID\""
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "names(train)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "merge(train,training,by=\"itemID\",all.x=TRUE)\n10*2"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "str(train)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": ""
 }
],"metadata":{"kernelspec":{"display_name":"R","language":"R","name":"ir"}}, "nbformat": 4, "nbformat_minor": 0}