{
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        "# 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",
        "\n",
        "library(ggplot2) # Data visualization\n",
        "library(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",
        "\n",
        "system(\"ls ../input\")\n",
        "\n",
        "# Any results you write to the current directory are saved as output."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "e02acace-565d-5a5b-1c4e-0e29d1124615"
      },
      "outputs": [],
      "source": [
        "getwd()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "78238275-4d0e-2ec1-e8a6-88b5efc723cb"
      },
      "outputs": [],
      "source": [
        "dir()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "094576dd-7a40-79e0-e0be-032a80a60b5f"
      },
      "outputs": [],
      "source": [
        "setwd(\"../input/\")\n",
        "x <- read.csv(\"page_views_sample.csv\")[ 1:5,]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "21c94e59-61f7-97e9-d360-96ce35cc78ce"
      },
      "outputs": [],
      "source": [
        "x"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "_cell_guid": "df43a213-15b7-8d46-3bd5-8926ef2b0ce8"
      },
      "outputs": [],
      "source": ""
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