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     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>property_id</th>\n",
       "      <th>ad_latitude</th>\n",
       "      <th>ad_longitude</th>\n",
       "      <th>create_date</th>\n",
       "      <th>check_in_date</th>\n",
       "      <th>check_out_date</th>\n",
       "      <th>country_code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1246</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012-03-07 13:26:38</td>\n",
       "      <td>2012-08-20</td>\n",
       "      <td>2012-08-25</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1246</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012-03-07 13:35:03</td>\n",
       "      <td>2012-08-27</td>\n",
       "      <td>2012-08-30</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1237</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012-03-07 13:36:33</td>\n",
       "      <td>2012-08-27</td>\n",
       "      <td>2012-08-30</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1237</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012-03-07 13:38:26</td>\n",
       "      <td>2012-03-19</td>\n",
       "      <td>2012-03-22</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1246</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2012-03-08 11:06:00</td>\n",
       "      <td>2012-08-20</td>\n",
       "      <td>2012-08-24</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   property_id  ad_latitude  ad_longitude          create_date check_in_date  \\\n",
       "0         1246          NaN           NaN  2012-03-07 13:26:38    2012-08-20   \n",
       "1         1246          NaN           NaN  2012-03-07 13:35:03    2012-08-27   \n",
       "2         1237          NaN           NaN  2012-03-07 13:36:33    2012-08-27   \n",
       "3         1237          NaN           NaN  2012-03-07 13:38:26    2012-03-19   \n",
       "4         1246          NaN           NaN  2012-03-08 11:06:00    2012-08-20   \n",
       "\n",
       "  check_out_date country_code  \n",
       "0     2012-08-25          NaN  \n",
       "1     2012-08-30          NaN  \n",
       "2     2012-08-30          NaN  \n",
       "3     2012-03-22          NaN  \n",
       "4     2012-08-24          NaN  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv('/home/valentina/Documents/Please/please3.csv', parse_dates=['check_in_date'])\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "property_id                int64\n",
       "ad_latitude              float64\n",
       "ad_longitude             float64\n",
       "create_date               object\n",
       "check_in_date     datetime64[ns]\n",
       "check_out_date            object\n",
       "country_code              object\n",
       "dtype: object"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import datetime\n",
    "\n",
    "# Convert into datetime\n",
    "\n",
    "df['check_out_date'] = pd.to_datetime(df['check_out_date'])\n",
    "df['create_date'] = pd.to_datetime(df['create_date'])\n",
    "\n",
    "# Add column with difference\n",
    "\n",
    "df['diff'] = df['check_out_date'] - df['check_in_date']\n",
    "\n",
    "# Drop bookings for more than 10 days.\n",
    "\n",
    "dfclean = df[(df['diff'].dt.days < 10)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Split dataset for each month of check_in\n",
    "\n",
    "for year in dfclean.check_in_date.apply(lambda x: x.year).unique():\n",
    "    for month in dfclean.check_in_date.apply(lambda x: x.month).unique():\n",
    "        view = dfclean[dfclean.check_in_date.apply(lambda x: x.month == month and x.year==year)]\n",
    "        if view.size:\n",
    "            view.to_csv('/home/valentina/Documents/Months/{}_{:0>2}.csv'.format(year, month))"
   ]
  }
 ],
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