{"cells":[
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "%matplotlib inline\nimport numpy as np\nimport pandas as pd \nfrom subprocess import check_output\n#print(check_output([\"ls\", \"../input\"]).decode(\"utf8\"))\nimport datetime"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "train = pd.read_csv(\"../input/train.csv\", parse_dates=['date_time'], nrows=10000000)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "import seaborn as sns\nimport matplotlib.pyplot as plt"
 },
 {
  "cell_type": "markdown",
  "metadata": {},
  "source": "tall = train.ix[:, 'date_time']"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "mask = train.is_booking == True"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "trainm = train[mask]\n"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "#understanding the numerical content \n\nb1 = trainm[['srch_adults_cnt','srch_children_cnt','srch_rm_cnt']]"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "sns.countplot(y='srch_children_cnt', hue='srch_rm_cnt', data=trainm)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# putting the above separately\nsns.countplot(y='srch_adults_cnt', hue='srch_rm_cnt', data=trainm)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# putting the above separately\nsns.countplot(y='srch_adults_cnt', hue='srch_children_cnt', data=trainm)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "b1.to_csv('rooms_children_adults_nrows1K.csv',header=True)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# putting the above separately\nsns.countplot(y='srch_adults_cnt', data=trainm)"
 },
 {
  "cell_type": "code",
  "execution_count": null,
  "metadata": {
   "collapsed": false
  },
  "outputs": [],
  "source": "# putting the children\nsns.countplot(y='srch_children_cnt', data=trainm)"
 }
],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}}, "nbformat": 4, "nbformat_minor": 0}