{"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"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# load data\ntrainData = read_csv(\"../input/train.csv\")\ntrainSubData <- trainData[sample(1:nrow(trainData), 9000000, replace=FALSE),]"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# exploration of the training dataset\n## Understanding the time\nggplot(trainSubData, aes(time)) +\n  geom_histogram(binwidth = 1, fill = \"white\", color = \"black\")"
 }
],"metadata":{"kernelspec":{"display_name":"R","language":"R","name":"ir"}}, "nbformat": 4, "nbformat_minor": 0}