{"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\nlibrary(dplyr)\nlibrary(data.table)\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\n#system(\"ls ../input\")\n\n# Any results you write to the current directory are saved as output\ntrain <- fread(\"../input/train.csv\",nrows = 1000000)\n#train <- train %>% sample_frac(0.001)\nclient <- fread(\"../input/cliente_tabla.csv\")\nproduct <- fread(\"../input/producto_tabla.csv\")\ntown <- fread(\"../input/town_state.csv\")\n\n\n"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "table(train$Semana)"
 }
],"metadata":{"kernelspec":{"display_name":"R","language":"R","name":"ir"}}, "nbformat": 4, "nbformat_minor": 0}