{"cells":[
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# You can write R code here and then click \"Run\" to run it on our platform\n\n#library(readr)\n\n# The competition datafiles are in the directory ../input\n# Read competition data files:\n#train <- read_csv(\"../input/train.csv\")\n#test <- read_csv(\"../input/test.csv\")\n\n# Write to the log:\n#cat(sprintf(\"Training set has %d rows and %d columns\\n\", nrow(train), ncol(train)))\n#cat(sprintf(\"Test set has %d rows and %d columns\\n\", nrow(test), ncol(test)))\n\n# Generate output files with write_csv(), plot() or ggplot()\n# Any files you write to the current directory get shown as outputs\n\n"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "import numpy as np\nimport urllib"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "dataset = np.loadtxt(\"../input/train.csv\", delimiter=\",\")"
 }
],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}}, "nbformat": 4, "nbformat_minor": 0}