PredictCustomerSpend.ipynb

{
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  {
   "cell_type": "markdown",
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   "source": [
    "# Predicting customer spend\n",
    "\n",
    "Thomas Wood\n",
    "\n",
    "fastdatascience.com\n",
    "\n",
    "Data science consulting\n",
    "\n",
    "The dataset I used is from Kaggle, https://www.kaggle.com/c/customer-spend-model\n",
    "\n",
    "The YouTube video tutorial is at https://youtu.be/Cc8a_cMzyUk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<sqlalchemy.engine.result.ResultProxy at 0x2965a491198>"
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     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from sqlalchemy import create_engine\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "\n",
    "sqlEngine = create_engine('mysql+pymysql://thomas:@127.0.0.1', pool_recycle=3600)\n",
    "dbConnection = sqlEngine.connect()\n",
    "dbConnection.execute(\"use purchases;\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>id</th>\n",
       "      <th>orddate</th>\n",
       "      <th>ordnum</th>\n",
       "      <th>category</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-02-10</td>\n",
       "      <td>38650</td>\n",
       "      <td>35</td>\n",
       "      <td>5.010658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-02-10</td>\n",
       "      <td>38650</td>\n",
       "      <td>35</td>\n",
       "      <td>20.426102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-02-10</td>\n",
       "      <td>38650</td>\n",
       "      <td>19</td>\n",
       "      <td>20.400543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-03-15</td>\n",
       "      <td>48972</td>\n",
       "      <td>40</td>\n",
       "      <td>25.539017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-11-22</td>\n",
       "      <td>150011</td>\n",
       "      <td>40</td>\n",
       "      <td>14.316170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-11-22</td>\n",
       "      <td>150011</td>\n",
       "      <td>40</td>\n",
       "      <td>8.589699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>957</td>\n",
       "      <td>2009-10-03</td>\n",
       "      <td>286151</td>\n",
       "      <td>19</td>\n",
       "      <td>15.313187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>957</td>\n",
       "      <td>2010-04-04</td>\n",
       "      <td>376779</td>\n",
       "      <td>14</td>\n",
       "      <td>12.782295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>957</td>\n",
       "      <td>2010-04-04</td>\n",
       "      <td>376779</td>\n",
       "      <td>14</td>\n",
       "      <td>5.087353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>957</td>\n",
       "      <td>2010-04-04</td>\n",
       "      <td>376779</td>\n",
       "      <td>35</td>\n",
       "      <td>6.544533</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "    id    orddate  ordnum  category      price\n",
       "0  957 2008-02-10   38650        35   5.010658\n",
       "1  957 2008-02-10   38650        35  20.426102\n",
       "2  957 2008-02-10   38650        19  20.400543\n",
       "3  957 2008-03-15   48972        40  25.539017\n",
       "4  957 2008-11-22  150011        40  14.316170\n",
       "5  957 2008-11-22  150011        40   8.589699\n",
       "6  957 2009-10-03  286151        19  15.313187\n",
       "7  957 2010-04-04  376779        14  12.782295\n",
       "8  957 2010-04-04  376779        14   5.087353\n",
       "9  957 2010-04-04  376779        35   6.544533"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_sql_query(\"SELECT id, orddate, ordnum, category, price FROM orders LIMIT 10\", dbConnection)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "dbConnection.execute(\"\"\"CREATE OR REPLACE VIEW customerDailySpend AS SELECT id, \n",
    "       orddate, \n",
    "       Sum(price) AS dailySpend\n",
    "       FROM orders\n",
    "       GROUP BY id, orddate\n",
    "       ORDER BY id, orddate;\n",
    "\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>orddate</th>\n",
       "      <th>dailySpend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-02-10</td>\n",
       "      <td>45.837303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-03-15</td>\n",
       "      <td>25.539017</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-11-22</td>\n",
       "      <td>22.905869</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>957</td>\n",
       "      <td>2009-10-03</td>\n",
       "      <td>15.313187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>957</td>\n",
       "      <td>2010-04-04</td>\n",
       "      <td>24.414181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>957</td>\n",
       "      <td>2011-08-14</td>\n",
       "      <td>34.103157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>957</td>\n",
       "      <td>2011-09-10</td>\n",
       "      <td>35.795532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>957</td>\n",
       "      <td>2011-10-10</td>\n",
       "      <td>45.786179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>957</td>\n",
       "      <td>2012-06-19</td>\n",
       "      <td>27.900585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>957</td>\n",
       "      <td>2012-07-28</td>\n",
       "      <td>12.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>957</td>\n",
       "      <td>2013-02-20</td>\n",
       "      <td>22.749992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>957</td>\n",
       "      <td>2013-07-27</td>\n",
       "      <td>19.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>957</td>\n",
       "      <td>2014-07-19</td>\n",
       "      <td>22.799994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>957</td>\n",
       "      <td>2014-07-29</td>\n",
       "      <td>26.799990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2062</td>\n",
       "      <td>2008-10-14</td>\n",
       "      <td>62.658798</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2062</td>\n",
       "      <td>2009-12-08</td>\n",
       "      <td>86.382740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-02-22</td>\n",
       "      <td>42.258263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-03-10</td>\n",
       "      <td>19.301262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-07-12</td>\n",
       "      <td>66.621315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-10-31</td>\n",
       "      <td>46.680923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-12-29</td>\n",
       "      <td>49.365211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2062</td>\n",
       "      <td>2011-08-21</td>\n",
       "      <td>48.086983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2062</td>\n",
       "      <td>2011-12-19</td>\n",
       "      <td>65.061874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-02-20</td>\n",
       "      <td>105.800402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-05-25</td>\n",
       "      <td>85.450407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-07-21</td>\n",
       "      <td>108.300777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-10-26</td>\n",
       "      <td>68.399979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-12-16</td>\n",
       "      <td>90.799971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2062</td>\n",
       "      <td>2014-06-02</td>\n",
       "      <td>89.838577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2062</td>\n",
       "      <td>2014-07-13</td>\n",
       "      <td>43.599985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>101449</th>\n",
       "      <td>16441249</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>9.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101450</th>\n",
       "      <td>16441311</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>36.698883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101451</th>\n",
       "      <td>16441753</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>25.349993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101452</th>\n",
       "      <td>16442440</td>\n",
       "      <td>2014-11-12</td>\n",
       "      <td>50.650417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101453</th>\n",
       "      <td>16442512</td>\n",
       "      <td>2014-11-12</td>\n",
       "      <td>29.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101454</th>\n",
       "      <td>16442601</td>\n",
       "      <td>2014-11-12</td>\n",
       "      <td>24.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101455</th>\n",
       "      <td>16444124</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>24.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101456</th>\n",
       "      <td>16444167</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>9.949997</td>\n",
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       "    <tr>\n",
       "      <th>101457</th>\n",
       "      <td>16444299</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>18.000000</td>\n",
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       "    <tr>\n",
       "      <th>101458</th>\n",
       "      <td>16444426</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>19.899994</td>\n",
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       "    <tr>\n",
       "      <th>101459</th>\n",
       "      <td>16444779</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>29.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101460</th>\n",
       "      <td>16444809</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>12.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101461</th>\n",
       "      <td>16444868</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>8.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101462</th>\n",
       "      <td>16445139</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>19.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101463</th>\n",
       "      <td>16446020</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>17.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101464</th>\n",
       "      <td>16447050</td>\n",
       "      <td>2014-11-16</td>\n",
       "      <td>24.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101465</th>\n",
       "      <td>16448030</td>\n",
       "      <td>2014-11-17</td>\n",
       "      <td>5.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101466</th>\n",
       "      <td>16448065</td>\n",
       "      <td>2014-11-17</td>\n",
       "      <td>49.949982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101467</th>\n",
       "      <td>16448081</td>\n",
       "      <td>2014-11-17</td>\n",
       "      <td>3.949999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101468</th>\n",
       "      <td>16448510</td>\n",
       "      <td>2014-11-17</td>\n",
       "      <td>7.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101469</th>\n",
       "      <td>16451821</td>\n",
       "      <td>2014-11-19</td>\n",
       "      <td>89.699982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101470</th>\n",
       "      <td>16451899</td>\n",
       "      <td>2014-11-19</td>\n",
       "      <td>19.799988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101471</th>\n",
       "      <td>16453115</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>19.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101472</th>\n",
       "      <td>16453182</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>29.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101473</th>\n",
       "      <td>16453395</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>24.799988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101474</th>\n",
       "      <td>16453760</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>9.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101475</th>\n",
       "      <td>16455134</td>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>162.499941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101476</th>\n",
       "      <td>16455606</td>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>29.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101477</th>\n",
       "      <td>16455720</td>\n",
       "      <td>2014-11-24</td>\n",
       "      <td>9.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101478</th>\n",
       "      <td>16456238</td>\n",
       "      <td>2014-11-24</td>\n",
       "      <td>93.439701</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>101479 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id    orddate  dailySpend\n",
       "0            957 2008-02-10   45.837303\n",
       "1            957 2008-03-15   25.539017\n",
       "2            957 2008-11-22   22.905869\n",
       "3            957 2009-10-03   15.313187\n",
       "4            957 2010-04-04   24.414181\n",
       "5            957 2011-08-14   34.103157\n",
       "6            957 2011-09-10   35.795532\n",
       "7            957 2011-10-10   45.786179\n",
       "8            957 2012-06-19   27.900585\n",
       "9            957 2012-07-28   12.949997\n",
       "10           957 2013-02-20   22.749992\n",
       "11           957 2013-07-27   19.949997\n",
       "12           957 2014-07-19   22.799994\n",
       "13           957 2014-07-29   26.799990\n",
       "14          2062 2008-10-14   62.658798\n",
       "15          2062 2009-12-08   86.382740\n",
       "16          2062 2010-02-22   42.258263\n",
       "17          2062 2010-03-10   19.301262\n",
       "18          2062 2010-07-12   66.621315\n",
       "19          2062 2010-10-31   46.680923\n",
       "20          2062 2010-12-29   49.365211\n",
       "21          2062 2011-08-21   48.086983\n",
       "22          2062 2011-12-19   65.061874\n",
       "23          2062 2013-02-20  105.800402\n",
       "24          2062 2013-05-25   85.450407\n",
       "25          2062 2013-07-21  108.300777\n",
       "26          2062 2013-10-26   68.399979\n",
       "27          2062 2013-12-16   90.799971\n",
       "28          2062 2014-06-02   89.838577\n",
       "29          2062 2014-07-13   43.599985\n",
       "...          ...        ...         ...\n",
       "101449  16441249 2014-11-11    9.949997\n",
       "101450  16441311 2014-11-11   36.698883\n",
       "101451  16441753 2014-11-11   25.349993\n",
       "101452  16442440 2014-11-12   50.650417\n",
       "101453  16442512 2014-11-12   29.949997\n",
       "101454  16442601 2014-11-12   24.899994\n",
       "101455  16444124 2014-11-15   24.949997\n",
       "101456  16444167 2014-11-15    9.949997\n",
       "101457  16444299 2014-11-15   18.000000\n",
       "101458  16444426 2014-11-15   19.899994\n",
       "101459  16444779 2014-11-15   29.899994\n",
       "101460  16444809 2014-11-15   12.899994\n",
       "101461  16444868 2014-11-15    8.949997\n",
       "101462  16445139 2014-11-15   19.949997\n",
       "101463  16446020 2014-11-15   17.899994\n",
       "101464  16447050 2014-11-16   24.949997\n",
       "101465  16448030 2014-11-17    5.949997\n",
       "101466  16448065 2014-11-17   49.949982\n",
       "101467  16448081 2014-11-17    3.949999\n",
       "101468  16448510 2014-11-17    7.949997\n",
       "101469  16451821 2014-11-19   89.699982\n",
       "101470  16451899 2014-11-19   19.799988\n",
       "101471  16453115 2014-11-22   19.899994\n",
       "101472  16453182 2014-11-22   29.899994\n",
       "101473  16453395 2014-11-22   24.799988\n",
       "101474  16453760 2014-11-22    9.949997\n",
       "101475  16455134 2014-11-23  162.499941\n",
       "101476  16455606 2014-11-23   29.949997\n",
       "101477  16455720 2014-11-24    9.899994\n",
       "101478  16456238 2014-11-24   93.439701\n",
       "\n",
       "[101479 rows x 3 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_sql_query(\"\"\"SELECT * FROM customerDailySpend;\"\"\", dbConnection)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>orddate</th>\n",
       "      <th>weekday</th>\n",
       "      <th>TotalPrecedingSpend</th>\n",
       "      <th>AvgPrecedingSpend</th>\n",
       "      <th>PreviousSpend</th>\n",
       "      <th>NumPrecedingVisits</th>\n",
       "      <th>dailySpend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-02-10</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>45.837303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-03-15</td>\n",
       "      <td>7</td>\n",
       "      <td>45.837303</td>\n",
       "      <td>45.837303</td>\n",
       "      <td>45.837303</td>\n",
       "      <td>1</td>\n",
       "      <td>25.539017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>957</td>\n",
       "      <td>2008-11-22</td>\n",
       "      <td>7</td>\n",
       "      <td>71.376320</td>\n",
       "      <td>35.688160</td>\n",
       "      <td>25.539017</td>\n",
       "      <td>2</td>\n",
       "      <td>22.905869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>957</td>\n",
       "      <td>2009-10-03</td>\n",
       "      <td>7</td>\n",
       "      <td>94.282188</td>\n",
       "      <td>31.427396</td>\n",
       "      <td>22.905869</td>\n",
       "      <td>3</td>\n",
       "      <td>15.313187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>957</td>\n",
       "      <td>2010-04-04</td>\n",
       "      <td>1</td>\n",
       "      <td>109.595375</td>\n",
       "      <td>27.398844</td>\n",
       "      <td>15.313187</td>\n",
       "      <td>4</td>\n",
       "      <td>24.414181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>957</td>\n",
       "      <td>2011-08-14</td>\n",
       "      <td>1</td>\n",
       "      <td>134.009556</td>\n",
       "      <td>26.801911</td>\n",
       "      <td>24.414181</td>\n",
       "      <td>5</td>\n",
       "      <td>34.103157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>957</td>\n",
       "      <td>2011-09-10</td>\n",
       "      <td>7</td>\n",
       "      <td>168.112713</td>\n",
       "      <td>28.018785</td>\n",
       "      <td>34.103157</td>\n",
       "      <td>6</td>\n",
       "      <td>35.795532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>957</td>\n",
       "      <td>2011-10-10</td>\n",
       "      <td>2</td>\n",
       "      <td>203.908245</td>\n",
       "      <td>29.129749</td>\n",
       "      <td>35.795532</td>\n",
       "      <td>7</td>\n",
       "      <td>45.786179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>957</td>\n",
       "      <td>2012-06-19</td>\n",
       "      <td>3</td>\n",
       "      <td>249.694424</td>\n",
       "      <td>31.211803</td>\n",
       "      <td>45.786179</td>\n",
       "      <td>8</td>\n",
       "      <td>27.900585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>957</td>\n",
       "      <td>2012-07-28</td>\n",
       "      <td>7</td>\n",
       "      <td>277.595009</td>\n",
       "      <td>30.843890</td>\n",
       "      <td>27.900585</td>\n",
       "      <td>9</td>\n",
       "      <td>12.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>957</td>\n",
       "      <td>2013-02-20</td>\n",
       "      <td>4</td>\n",
       "      <td>290.545006</td>\n",
       "      <td>29.054501</td>\n",
       "      <td>12.949997</td>\n",
       "      <td>10</td>\n",
       "      <td>22.749992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>957</td>\n",
       "      <td>2013-07-27</td>\n",
       "      <td>7</td>\n",
       "      <td>313.294998</td>\n",
       "      <td>28.481363</td>\n",
       "      <td>22.749992</td>\n",
       "      <td>11</td>\n",
       "      <td>19.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>957</td>\n",
       "      <td>2014-07-19</td>\n",
       "      <td>7</td>\n",
       "      <td>333.244995</td>\n",
       "      <td>27.770416</td>\n",
       "      <td>19.949997</td>\n",
       "      <td>12</td>\n",
       "      <td>22.799994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>957</td>\n",
       "      <td>2014-07-29</td>\n",
       "      <td>3</td>\n",
       "      <td>356.044989</td>\n",
       "      <td>27.388076</td>\n",
       "      <td>22.799994</td>\n",
       "      <td>13</td>\n",
       "      <td>26.799990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2062</td>\n",
       "      <td>2008-10-14</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>62.658798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2062</td>\n",
       "      <td>2009-12-08</td>\n",
       "      <td>3</td>\n",
       "      <td>62.658798</td>\n",
       "      <td>62.658798</td>\n",
       "      <td>62.658798</td>\n",
       "      <td>1</td>\n",
       "      <td>86.382740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-02-22</td>\n",
       "      <td>2</td>\n",
       "      <td>149.041538</td>\n",
       "      <td>74.520769</td>\n",
       "      <td>86.382740</td>\n",
       "      <td>2</td>\n",
       "      <td>42.258263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-03-10</td>\n",
       "      <td>4</td>\n",
       "      <td>191.299801</td>\n",
       "      <td>63.766600</td>\n",
       "      <td>42.258263</td>\n",
       "      <td>3</td>\n",
       "      <td>19.301262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-07-12</td>\n",
       "      <td>2</td>\n",
       "      <td>210.601063</td>\n",
       "      <td>52.650266</td>\n",
       "      <td>19.301262</td>\n",
       "      <td>4</td>\n",
       "      <td>66.621315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-10-31</td>\n",
       "      <td>1</td>\n",
       "      <td>277.222378</td>\n",
       "      <td>55.444476</td>\n",
       "      <td>66.621315</td>\n",
       "      <td>5</td>\n",
       "      <td>46.680923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2062</td>\n",
       "      <td>2010-12-29</td>\n",
       "      <td>4</td>\n",
       "      <td>323.903301</td>\n",
       "      <td>53.983884</td>\n",
       "      <td>46.680923</td>\n",
       "      <td>6</td>\n",
       "      <td>49.365211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2062</td>\n",
       "      <td>2011-08-21</td>\n",
       "      <td>1</td>\n",
       "      <td>373.268513</td>\n",
       "      <td>53.324073</td>\n",
       "      <td>49.365211</td>\n",
       "      <td>7</td>\n",
       "      <td>48.086983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2062</td>\n",
       "      <td>2011-12-19</td>\n",
       "      <td>2</td>\n",
       "      <td>421.355495</td>\n",
       "      <td>52.669437</td>\n",
       "      <td>48.086983</td>\n",
       "      <td>8</td>\n",
       "      <td>65.061874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-02-20</td>\n",
       "      <td>4</td>\n",
       "      <td>486.417370</td>\n",
       "      <td>54.046374</td>\n",
       "      <td>65.061874</td>\n",
       "      <td>9</td>\n",
       "      <td>105.800402</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-05-25</td>\n",
       "      <td>7</td>\n",
       "      <td>592.217772</td>\n",
       "      <td>59.221777</td>\n",
       "      <td>105.800402</td>\n",
       "      <td>10</td>\n",
       "      <td>85.450407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-07-21</td>\n",
       "      <td>1</td>\n",
       "      <td>677.668179</td>\n",
       "      <td>61.606198</td>\n",
       "      <td>85.450407</td>\n",
       "      <td>11</td>\n",
       "      <td>108.300777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-10-26</td>\n",
       "      <td>7</td>\n",
       "      <td>785.968956</td>\n",
       "      <td>65.497413</td>\n",
       "      <td>108.300777</td>\n",
       "      <td>12</td>\n",
       "      <td>68.399979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2062</td>\n",
       "      <td>2013-12-16</td>\n",
       "      <td>2</td>\n",
       "      <td>854.368935</td>\n",
       "      <td>65.720687</td>\n",
       "      <td>68.399979</td>\n",
       "      <td>13</td>\n",
       "      <td>90.799971</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2062</td>\n",
       "      <td>2014-06-02</td>\n",
       "      <td>2</td>\n",
       "      <td>945.168905</td>\n",
       "      <td>67.512065</td>\n",
       "      <td>90.799971</td>\n",
       "      <td>14</td>\n",
       "      <td>89.838577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2062</td>\n",
       "      <td>2014-07-13</td>\n",
       "      <td>1</td>\n",
       "      <td>1035.007483</td>\n",
       "      <td>69.000499</td>\n",
       "      <td>89.838577</td>\n",
       "      <td>15</td>\n",
       "      <td>43.599985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101449</th>\n",
       "      <td>16441249</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101450</th>\n",
       "      <td>16441311</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>36.698883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101451</th>\n",
       "      <td>16441753</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>25.349993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101452</th>\n",
       "      <td>16442440</td>\n",
       "      <td>2014-11-12</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>50.650417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101453</th>\n",
       "      <td>16442512</td>\n",
       "      <td>2014-11-12</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>29.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101454</th>\n",
       "      <td>16442601</td>\n",
       "      <td>2014-11-12</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>24.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101455</th>\n",
       "      <td>16444124</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>24.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101456</th>\n",
       "      <td>16444167</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101457</th>\n",
       "      <td>16444299</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>18.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101458</th>\n",
       "      <td>16444426</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>19.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101459</th>\n",
       "      <td>16444779</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>29.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101460</th>\n",
       "      <td>16444809</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101461</th>\n",
       "      <td>16444868</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>8.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101462</th>\n",
       "      <td>16445139</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>19.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101463</th>\n",
       "      <td>16446020</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>17.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101464</th>\n",
       "      <td>16447050</td>\n",
       "      <td>2014-11-16</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>24.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101465</th>\n",
       "      <td>16448030</td>\n",
       "      <td>2014-11-17</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101466</th>\n",
       "      <td>16448065</td>\n",
       "      <td>2014-11-17</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>49.949982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101467</th>\n",
       "      <td>16448081</td>\n",
       "      <td>2014-11-17</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>3.949999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101468</th>\n",
       "      <td>16448510</td>\n",
       "      <td>2014-11-17</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>7.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101469</th>\n",
       "      <td>16451821</td>\n",
       "      <td>2014-11-19</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>89.699982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101470</th>\n",
       "      <td>16451899</td>\n",
       "      <td>2014-11-19</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>19.799988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101471</th>\n",
       "      <td>16453115</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>19.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101472</th>\n",
       "      <td>16453182</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>29.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101473</th>\n",
       "      <td>16453395</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>24.799988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101474</th>\n",
       "      <td>16453760</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101475</th>\n",
       "      <td>16455134</td>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>162.499941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101476</th>\n",
       "      <td>16455606</td>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>29.949997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101477</th>\n",
       "      <td>16455720</td>\n",
       "      <td>2014-11-24</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101478</th>\n",
       "      <td>16456238</td>\n",
       "      <td>2014-11-24</td>\n",
       "      <td>2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>93.439701</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>101479 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id    orddate  weekday  TotalPrecedingSpend  AvgPrecedingSpend  \\\n",
       "0            957 2008-02-10        1                  NaN                NaN   \n",
       "1            957 2008-03-15        7            45.837303          45.837303   \n",
       "2            957 2008-11-22        7            71.376320          35.688160   \n",
       "3            957 2009-10-03        7            94.282188          31.427396   \n",
       "4            957 2010-04-04        1           109.595375          27.398844   \n",
       "5            957 2011-08-14        1           134.009556          26.801911   \n",
       "6            957 2011-09-10        7           168.112713          28.018785   \n",
       "7            957 2011-10-10        2           203.908245          29.129749   \n",
       "8            957 2012-06-19        3           249.694424          31.211803   \n",
       "9            957 2012-07-28        7           277.595009          30.843890   \n",
       "10           957 2013-02-20        4           290.545006          29.054501   \n",
       "11           957 2013-07-27        7           313.294998          28.481363   \n",
       "12           957 2014-07-19        7           333.244995          27.770416   \n",
       "13           957 2014-07-29        3           356.044989          27.388076   \n",
       "14          2062 2008-10-14        3                  NaN                NaN   \n",
       "15          2062 2009-12-08        3            62.658798          62.658798   \n",
       "16          2062 2010-02-22        2           149.041538          74.520769   \n",
       "17          2062 2010-03-10        4           191.299801          63.766600   \n",
       "18          2062 2010-07-12        2           210.601063          52.650266   \n",
       "19          2062 2010-10-31        1           277.222378          55.444476   \n",
       "20          2062 2010-12-29        4           323.903301          53.983884   \n",
       "21          2062 2011-08-21        1           373.268513          53.324073   \n",
       "22          2062 2011-12-19        2           421.355495          52.669437   \n",
       "23          2062 2013-02-20        4           486.417370          54.046374   \n",
       "24          2062 2013-05-25        7           592.217772          59.221777   \n",
       "25          2062 2013-07-21        1           677.668179          61.606198   \n",
       "26          2062 2013-10-26        7           785.968956          65.497413   \n",
       "27          2062 2013-12-16        2           854.368935          65.720687   \n",
       "28          2062 2014-06-02        2           945.168905          67.512065   \n",
       "29          2062 2014-07-13        1          1035.007483          69.000499   \n",
       "...          ...        ...      ...                  ...                ...   \n",
       "101449  16441249 2014-11-11        3                  NaN                NaN   \n",
       "101450  16441311 2014-11-11        3                  NaN                NaN   \n",
       "101451  16441753 2014-11-11        3                  NaN                NaN   \n",
       "101452  16442440 2014-11-12        4                  NaN                NaN   \n",
       "101453  16442512 2014-11-12        4                  NaN                NaN   \n",
       "101454  16442601 2014-11-12        4                  NaN                NaN   \n",
       "101455  16444124 2014-11-15        7                  NaN                NaN   \n",
       "101456  16444167 2014-11-15        7                  NaN                NaN   \n",
       "101457  16444299 2014-11-15        7                  NaN                NaN   \n",
       "101458  16444426 2014-11-15        7                  NaN                NaN   \n",
       "101459  16444779 2014-11-15        7                  NaN                NaN   \n",
       "101460  16444809 2014-11-15        7                  NaN                NaN   \n",
       "101461  16444868 2014-11-15        7                  NaN                NaN   \n",
       "101462  16445139 2014-11-15        7                  NaN                NaN   \n",
       "101463  16446020 2014-11-15        7                  NaN                NaN   \n",
       "101464  16447050 2014-11-16        1                  NaN                NaN   \n",
       "101465  16448030 2014-11-17        2                  NaN                NaN   \n",
       "101466  16448065 2014-11-17        2                  NaN                NaN   \n",
       "101467  16448081 2014-11-17        2                  NaN                NaN   \n",
       "101468  16448510 2014-11-17        2                  NaN                NaN   \n",
       "101469  16451821 2014-11-19        4                  NaN                NaN   \n",
       "101470  16451899 2014-11-19        4                  NaN                NaN   \n",
       "101471  16453115 2014-11-22        7                  NaN                NaN   \n",
       "101472  16453182 2014-11-22        7                  NaN                NaN   \n",
       "101473  16453395 2014-11-22        7                  NaN                NaN   \n",
       "101474  16453760 2014-11-22        7                  NaN                NaN   \n",
       "101475  16455134 2014-11-23        1                  NaN                NaN   \n",
       "101476  16455606 2014-11-23        1                  NaN                NaN   \n",
       "101477  16455720 2014-11-24        2                  NaN                NaN   \n",
       "101478  16456238 2014-11-24        2                  NaN                NaN   \n",
       "\n",
       "        PreviousSpend  NumPrecedingVisits  dailySpend  \n",
       "0                 NaN                   0   45.837303  \n",
       "1           45.837303                   1   25.539017  \n",
       "2           25.539017                   2   22.905869  \n",
       "3           22.905869                   3   15.313187  \n",
       "4           15.313187                   4   24.414181  \n",
       "5           24.414181                   5   34.103157  \n",
       "6           34.103157                   6   35.795532  \n",
       "7           35.795532                   7   45.786179  \n",
       "8           45.786179                   8   27.900585  \n",
       "9           27.900585                   9   12.949997  \n",
       "10          12.949997                  10   22.749992  \n",
       "11          22.749992                  11   19.949997  \n",
       "12          19.949997                  12   22.799994  \n",
       "13          22.799994                  13   26.799990  \n",
       "14                NaN                   0   62.658798  \n",
       "15          62.658798                   1   86.382740  \n",
       "16          86.382740                   2   42.258263  \n",
       "17          42.258263                   3   19.301262  \n",
       "18          19.301262                   4   66.621315  \n",
       "19          66.621315                   5   46.680923  \n",
       "20          46.680923                   6   49.365211  \n",
       "21          49.365211                   7   48.086983  \n",
       "22          48.086983                   8   65.061874  \n",
       "23          65.061874                   9  105.800402  \n",
       "24         105.800402                  10   85.450407  \n",
       "25          85.450407                  11  108.300777  \n",
       "26         108.300777                  12   68.399979  \n",
       "27          68.399979                  13   90.799971  \n",
       "28          90.799971                  14   89.838577  \n",
       "29          89.838577                  15   43.599985  \n",
       "...               ...                 ...         ...  \n",
       "101449            NaN                   0    9.949997  \n",
       "101450            NaN                   0   36.698883  \n",
       "101451            NaN                   0   25.349993  \n",
       "101452            NaN                   0   50.650417  \n",
       "101453            NaN                   0   29.949997  \n",
       "101454            NaN                   0   24.899994  \n",
       "101455            NaN                   0   24.949997  \n",
       "101456            NaN                   0    9.949997  \n",
       "101457            NaN                   0   18.000000  \n",
       "101458            NaN                   0   19.899994  \n",
       "101459            NaN                   0   29.899994  \n",
       "101460            NaN                   0   12.899994  \n",
       "101461            NaN                   0    8.949997  \n",
       "101462            NaN                   0   19.949997  \n",
       "101463            NaN                   0   17.899994  \n",
       "101464            NaN                   0   24.949997  \n",
       "101465            NaN                   0    5.949997  \n",
       "101466            NaN                   0   49.949982  \n",
       "101467            NaN                   0    3.949999  \n",
       "101468            NaN                   0    7.949997  \n",
       "101469            NaN                   0   89.699982  \n",
       "101470            NaN                   0   19.799988  \n",
       "101471            NaN                   0   19.899994  \n",
       "101472            NaN                   0   29.899994  \n",
       "101473            NaN                   0   24.799988  \n",
       "101474            NaN                   0    9.949997  \n",
       "101475            NaN                   0  162.499941  \n",
       "101476            NaN                   0   29.949997  \n",
       "101477            NaN                   0    9.899994  \n",
       "101478            NaN                   0   93.439701  \n",
       "\n",
       "[101479 rows x 8 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_features_and_spends = pd.read_sql_query(\"\"\"SELECT id, \n",
    "       orddate, \n",
    "       DAYOFWEEK(orddate) as weekday,\n",
    "       Sum(dailySpend) \n",
    "         OVER ( \n",
    "           partition BY id \n",
    "           ORDER BY id, orddate rows BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING) as TotalPrecedingSpend,\n",
    "    Avg(dailySpend) \n",
    "         OVER ( \n",
    "           partition BY id \n",
    "           ORDER BY id, orddate rows BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING) as AvgPrecedingSpend,\n",
    "    Sum(dailySpend) \n",
    "         OVER ( \n",
    "           partition BY id \n",
    "           ORDER BY id, orddate rows BETWEEN 1 PRECEDING AND 1 PRECEDING) as PreviousSpend,\n",
    "    Count(dailySpend) \n",
    "         OVER ( \n",
    "           partition BY id \n",
    "           ORDER BY id, orddate rows BETWEEN UNBOUNDED PRECEDING AND 1 PRECEDING) as NumPrecedingVisits,\n",
    "    dailySpend\n",
    "FROM   customerDailySpend \n",
    "GROUP  BY id, orddate\n",
    "ORDER BY id, orddate \"\"\", dbConnection)\n",
    "df_features_and_spends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_features_and_spends.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\woodt.DESKTOP-QB0N6BQ\\Anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x2965c09f588>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"weekday\", y=\"dailySpend\", data=df_features_and_spends)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Start machine learning modelling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "m = RandomForestRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(df_features_and_spends.orddate);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_train = df_features_and_spends[df_features_and_spends.orddate < pd.Timestamp(2014,1,1)]\n",
    "df_test = df_features_and_spends[df_features_and_spends.orddate >= pd.Timestamp(2014,1,1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestRegressor(bootstrap=True, criterion='mse', max_depth=None,\n",
       "           max_features='auto', max_leaf_nodes=None,\n",
       "           min_impurity_decrease=0.0, min_impurity_split=None,\n",
       "           min_samples_leaf=1, min_samples_split=2,\n",
       "           min_weight_fraction_leaf=0.0, n_estimators=10, n_jobs=1,\n",
       "           oob_score=False, random_state=None, verbose=0, warm_start=False)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m.fit(df_train.drop([\"id\", \"orddate\", \"dailySpend\"], axis=1), df_train.dailySpend)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = m.predict(df_test.drop([\"id\", \"orddate\", \"dailySpend\"], axis=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([33.51338749, 17.83421974, 80.52126675, ..., 66.88864593,\n",
       "       10.9049942 , 68.45940743])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\woodt.DESKTOP-QB0N6BQ\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "df_test[\"y_pred\"] = y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>orddate</th>\n",
       "      <th>weekday</th>\n",
       "      <th>TotalPrecedingSpend</th>\n",
       "      <th>AvgPrecedingSpend</th>\n",
       "      <th>PreviousSpend</th>\n",
       "      <th>NumPrecedingVisits</th>\n",
       "      <th>dailySpend</th>\n",
       "      <th>y_pred</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>957</td>\n",
       "      <td>2014-07-19</td>\n",
       "      <td>7</td>\n",
       "      <td>333.244995</td>\n",
       "      <td>27.770416</td>\n",
       "      <td>19.949997</td>\n",
       "      <td>12</td>\n",
       "      <td>22.799994</td>\n",
       "      <td>33.513387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>957</td>\n",
       "      <td>2014-07-29</td>\n",
       "      <td>3</td>\n",
       "      <td>356.044989</td>\n",
       "      <td>27.388076</td>\n",
       "      <td>22.799994</td>\n",
       "      <td>13</td>\n",
       "      <td>26.799990</td>\n",
       "      <td>17.834220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2062</td>\n",
       "      <td>2014-06-02</td>\n",
       "      <td>2</td>\n",
       "      <td>945.168905</td>\n",
       "      <td>67.512065</td>\n",
       "      <td>90.799971</td>\n",
       "      <td>14</td>\n",
       "      <td>89.838577</td>\n",
       "      <td>80.521267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2062</td>\n",
       "      <td>2014-07-13</td>\n",
       "      <td>1</td>\n",
       "      <td>1035.007483</td>\n",
       "      <td>69.000499</td>\n",
       "      <td>89.838577</td>\n",
       "      <td>15</td>\n",
       "      <td>43.599985</td>\n",
       "      <td>57.606519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2232</td>\n",
       "      <td>2014-02-02</td>\n",
       "      <td>1</td>\n",
       "      <td>1343.310947</td>\n",
       "      <td>38.380313</td>\n",
       "      <td>59.699984</td>\n",
       "      <td>35</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>31.583850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2232</td>\n",
       "      <td>2014-03-12</td>\n",
       "      <td>4</td>\n",
       "      <td>1353.260944</td>\n",
       "      <td>37.590582</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>36</td>\n",
       "      <td>3.949999</td>\n",
       "      <td>27.544093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>4251</td>\n",
       "      <td>2014-10-12</td>\n",
       "      <td>1</td>\n",
       "      <td>607.213722</td>\n",
       "      <td>55.201247</td>\n",
       "      <td>17.949997</td>\n",
       "      <td>11</td>\n",
       "      <td>81.389975</td>\n",
       "      <td>47.400041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>4642</td>\n",
       "      <td>2014-01-05</td>\n",
       "      <td>1</td>\n",
       "      <td>27.799988</td>\n",
       "      <td>27.799988</td>\n",
       "      <td>27.799988</td>\n",
       "      <td>1</td>\n",
       "      <td>22.899994</td>\n",
       "      <td>25.056789</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>5002</td>\n",
       "      <td>2014-10-19</td>\n",
       "      <td>1</td>\n",
       "      <td>642.402832</td>\n",
       "      <td>33.810675</td>\n",
       "      <td>28.899994</td>\n",
       "      <td>19</td>\n",
       "      <td>33.849997</td>\n",
       "      <td>54.553231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-02-19</td>\n",
       "      <td>4</td>\n",
       "      <td>1532.841331</td>\n",
       "      <td>39.303624</td>\n",
       "      <td>89.099976</td>\n",
       "      <td>39</td>\n",
       "      <td>36.849991</td>\n",
       "      <td>47.298953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-03-08</td>\n",
       "      <td>7</td>\n",
       "      <td>1569.691322</td>\n",
       "      <td>39.242283</td>\n",
       "      <td>36.849991</td>\n",
       "      <td>40</td>\n",
       "      <td>52.539974</td>\n",
       "      <td>37.615624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-03-19</td>\n",
       "      <td>4</td>\n",
       "      <td>1622.231297</td>\n",
       "      <td>39.566617</td>\n",
       "      <td>52.539974</td>\n",
       "      <td>41</td>\n",
       "      <td>56.649979</td>\n",
       "      <td>43.988467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-04-01</td>\n",
       "      <td>3</td>\n",
       "      <td>1678.881275</td>\n",
       "      <td>39.973364</td>\n",
       "      <td>56.649979</td>\n",
       "      <td>42</td>\n",
       "      <td>56.799988</td>\n",
       "      <td>35.233944</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-04-22</td>\n",
       "      <td>3</td>\n",
       "      <td>1735.681263</td>\n",
       "      <td>40.364681</td>\n",
       "      <td>56.799988</td>\n",
       "      <td>43</td>\n",
       "      <td>48.599983</td>\n",
       "      <td>40.124376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-05-05</td>\n",
       "      <td>2</td>\n",
       "      <td>1784.281246</td>\n",
       "      <td>40.551847</td>\n",
       "      <td>48.599983</td>\n",
       "      <td>44</td>\n",
       "      <td>56.099976</td>\n",
       "      <td>35.062185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-06-02</td>\n",
       "      <td>2</td>\n",
       "      <td>1840.381222</td>\n",
       "      <td>40.897360</td>\n",
       "      <td>56.099976</td>\n",
       "      <td>45</td>\n",
       "      <td>32.829987</td>\n",
       "      <td>37.943221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-06-17</td>\n",
       "      <td>3</td>\n",
       "      <td>1873.211208</td>\n",
       "      <td>40.721983</td>\n",
       "      <td>32.829987</td>\n",
       "      <td>46</td>\n",
       "      <td>32.749987</td>\n",
       "      <td>31.655455</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-06-30</td>\n",
       "      <td>2</td>\n",
       "      <td>1905.961195</td>\n",
       "      <td>40.552366</td>\n",
       "      <td>32.749987</td>\n",
       "      <td>47</td>\n",
       "      <td>50.239985</td>\n",
       "      <td>31.027067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-07-13</td>\n",
       "      <td>1</td>\n",
       "      <td>1956.201179</td>\n",
       "      <td>40.754191</td>\n",
       "      <td>50.239985</td>\n",
       "      <td>48</td>\n",
       "      <td>42.649979</td>\n",
       "      <td>42.924256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-09-01</td>\n",
       "      <td>2</td>\n",
       "      <td>1998.851158</td>\n",
       "      <td>40.792881</td>\n",
       "      <td>42.649979</td>\n",
       "      <td>49</td>\n",
       "      <td>50.739985</td>\n",
       "      <td>41.946927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-09-07</td>\n",
       "      <td>1</td>\n",
       "      <td>2049.591143</td>\n",
       "      <td>40.991823</td>\n",
       "      <td>50.739985</td>\n",
       "      <td>50</td>\n",
       "      <td>22.799988</td>\n",
       "      <td>45.309762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-09-21</td>\n",
       "      <td>1</td>\n",
       "      <td>2072.391130</td>\n",
       "      <td>40.635120</td>\n",
       "      <td>22.799988</td>\n",
       "      <td>51</td>\n",
       "      <td>35.199984</td>\n",
       "      <td>35.332422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-10-05</td>\n",
       "      <td>1</td>\n",
       "      <td>2107.591114</td>\n",
       "      <td>40.530598</td>\n",
       "      <td>35.199984</td>\n",
       "      <td>52</td>\n",
       "      <td>47.749989</td>\n",
       "      <td>31.755457</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-10-22</td>\n",
       "      <td>4</td>\n",
       "      <td>2155.341103</td>\n",
       "      <td>40.666813</td>\n",
       "      <td>47.749989</td>\n",
       "      <td>53</td>\n",
       "      <td>42.699982</td>\n",
       "      <td>31.991172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>6084</td>\n",
       "      <td>2014-10-29</td>\n",
       "      <td>4</td>\n",
       "      <td>2198.041084</td>\n",
       "      <td>40.704465</td>\n",
       "      <td>42.699982</td>\n",
       "      <td>54</td>\n",
       "      <td>37.739986</td>\n",
       "      <td>34.144523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>6130</td>\n",
       "      <td>2014-08-09</td>\n",
       "      <td>7</td>\n",
       "      <td>227.789341</td>\n",
       "      <td>28.473668</td>\n",
       "      <td>20.849991</td>\n",
       "      <td>8</td>\n",
       "      <td>16.849991</td>\n",
       "      <td>15.248178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>7072</td>\n",
       "      <td>2014-02-05</td>\n",
       "      <td>4</td>\n",
       "      <td>158.096554</td>\n",
       "      <td>22.585222</td>\n",
       "      <td>21.351490</td>\n",
       "      <td>7</td>\n",
       "      <td>12.949997</td>\n",
       "      <td>24.073217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>7072</td>\n",
       "      <td>2014-10-13</td>\n",
       "      <td>2</td>\n",
       "      <td>171.046551</td>\n",
       "      <td>21.380819</td>\n",
       "      <td>12.949997</td>\n",
       "      <td>8</td>\n",
       "      <td>32.889992</td>\n",
       "      <td>27.347693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>8648</td>\n",
       "      <td>2014-01-07</td>\n",
       "      <td>3</td>\n",
       "      <td>114.979996</td>\n",
       "      <td>11.498000</td>\n",
       "      <td>12.799995</td>\n",
       "      <td>10</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>20.871008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>8648</td>\n",
       "      <td>2014-06-15</td>\n",
       "      <td>1</td>\n",
       "      <td>127.879990</td>\n",
       "      <td>11.625454</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>11</td>\n",
       "      <td>37.699982</td>\n",
       "      <td>17.093708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101225</th>\n",
       "      <td>16332377</td>\n",
       "      <td>2014-09-22</td>\n",
       "      <td>2</td>\n",
       "      <td>24.839989</td>\n",
       "      <td>24.839989</td>\n",
       "      <td>24.839989</td>\n",
       "      <td>1</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>32.839901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101231</th>\n",
       "      <td>16333241</td>\n",
       "      <td>2014-11-18</td>\n",
       "      <td>3</td>\n",
       "      <td>33.389992</td>\n",
       "      <td>33.389992</td>\n",
       "      <td>33.389992</td>\n",
       "      <td>1</td>\n",
       "      <td>52.699982</td>\n",
       "      <td>26.362364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101236</th>\n",
       "      <td>16336330</td>\n",
       "      <td>2014-10-04</td>\n",
       "      <td>7</td>\n",
       "      <td>49.889984</td>\n",
       "      <td>49.889984</td>\n",
       "      <td>49.889984</td>\n",
       "      <td>1</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>62.731695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101237</th>\n",
       "      <td>16336330</td>\n",
       "      <td>2014-11-16</td>\n",
       "      <td>1</td>\n",
       "      <td>59.839981</td>\n",
       "      <td>29.919991</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>2</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>42.123049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101243</th>\n",
       "      <td>16339150</td>\n",
       "      <td>2014-11-23</td>\n",
       "      <td>1</td>\n",
       "      <td>17.889992</td>\n",
       "      <td>17.889992</td>\n",
       "      <td>17.889992</td>\n",
       "      <td>1</td>\n",
       "      <td>40.679987</td>\n",
       "      <td>25.862160</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101247</th>\n",
       "      <td>16342585</td>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>3</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>33.749987</td>\n",
       "      <td>27.637490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101248</th>\n",
       "      <td>16342585</td>\n",
       "      <td>2014-10-19</td>\n",
       "      <td>1</td>\n",
       "      <td>53.649981</td>\n",
       "      <td>26.824990</td>\n",
       "      <td>33.749987</td>\n",
       "      <td>2</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>26.723388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101253</th>\n",
       "      <td>16344090</td>\n",
       "      <td>2014-10-19</td>\n",
       "      <td>1</td>\n",
       "      <td>26.799992</td>\n",
       "      <td>26.799992</td>\n",
       "      <td>26.799992</td>\n",
       "      <td>1</td>\n",
       "      <td>60.699986</td>\n",
       "      <td>24.189993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101255</th>\n",
       "      <td>16344855</td>\n",
       "      <td>2014-09-29</td>\n",
       "      <td>2</td>\n",
       "      <td>213.929960</td>\n",
       "      <td>213.929960</td>\n",
       "      <td>213.929960</td>\n",
       "      <td>1</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>26.946820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101256</th>\n",
       "      <td>16344855</td>\n",
       "      <td>2014-10-27</td>\n",
       "      <td>2</td>\n",
       "      <td>221.429960</td>\n",
       "      <td>110.714980</td>\n",
       "      <td>7.500000</td>\n",
       "      <td>2</td>\n",
       "      <td>38.899996</td>\n",
       "      <td>50.653695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101285</th>\n",
       "      <td>16360249</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>3</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>15.343608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101289</th>\n",
       "      <td>16360974</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>3</td>\n",
       "      <td>98.249966</td>\n",
       "      <td>98.249966</td>\n",
       "      <td>98.249966</td>\n",
       "      <td>1</td>\n",
       "      <td>21.849991</td>\n",
       "      <td>64.831007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101291</th>\n",
       "      <td>16362497</td>\n",
       "      <td>2014-09-23</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>26.658382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101292</th>\n",
       "      <td>16362497</td>\n",
       "      <td>2014-09-27</td>\n",
       "      <td>7</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.682647</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101293</th>\n",
       "      <td>16362497</td>\n",
       "      <td>2014-09-30</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>16.330613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101294</th>\n",
       "      <td>16362497</td>\n",
       "      <td>2014-10-05</td>\n",
       "      <td>1</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.352122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101296</th>\n",
       "      <td>16362551</td>\n",
       "      <td>2014-11-16</td>\n",
       "      <td>1</td>\n",
       "      <td>9.989998</td>\n",
       "      <td>9.989998</td>\n",
       "      <td>9.989998</td>\n",
       "      <td>1</td>\n",
       "      <td>59.729980</td>\n",
       "      <td>22.403268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101302</th>\n",
       "      <td>16363302</td>\n",
       "      <td>2014-11-02</td>\n",
       "      <td>1</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>53.689983</td>\n",
       "      <td>14.847086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101303</th>\n",
       "      <td>16363302</td>\n",
       "      <td>2014-11-10</td>\n",
       "      <td>2</td>\n",
       "      <td>61.639980</td>\n",
       "      <td>30.819990</td>\n",
       "      <td>53.689983</td>\n",
       "      <td>2</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>21.295353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101310</th>\n",
       "      <td>16369106</td>\n",
       "      <td>2014-10-18</td>\n",
       "      <td>7</td>\n",
       "      <td>42.748880</td>\n",
       "      <td>42.748880</td>\n",
       "      <td>42.748880</td>\n",
       "      <td>1</td>\n",
       "      <td>23.349994</td>\n",
       "      <td>76.540371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101322</th>\n",
       "      <td>16374851</td>\n",
       "      <td>2014-11-11</td>\n",
       "      <td>3</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>35.789988</td>\n",
       "      <td>9.011663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101323</th>\n",
       "      <td>16374851</td>\n",
       "      <td>2014-11-15</td>\n",
       "      <td>7</td>\n",
       "      <td>44.739985</td>\n",
       "      <td>22.369992</td>\n",
       "      <td>35.789988</td>\n",
       "      <td>2</td>\n",
       "      <td>29.699989</td>\n",
       "      <td>35.500155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101324</th>\n",
       "      <td>16374851</td>\n",
       "      <td>2014-11-24</td>\n",
       "      <td>2</td>\n",
       "      <td>74.439974</td>\n",
       "      <td>24.813325</td>\n",
       "      <td>29.699989</td>\n",
       "      <td>3</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>21.500066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101326</th>\n",
       "      <td>16375416</td>\n",
       "      <td>2014-11-04</td>\n",
       "      <td>3</td>\n",
       "      <td>26.701035</td>\n",
       "      <td>26.701035</td>\n",
       "      <td>26.701035</td>\n",
       "      <td>1</td>\n",
       "      <td>39.899994</td>\n",
       "      <td>62.679826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101335</th>\n",
       "      <td>16377680</td>\n",
       "      <td>2014-10-15</td>\n",
       "      <td>4</td>\n",
       "      <td>15.949997</td>\n",
       "      <td>15.949997</td>\n",
       "      <td>15.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>18.616378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101344</th>\n",
       "      <td>16380720</td>\n",
       "      <td>2014-10-13</td>\n",
       "      <td>2</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>3.949999</td>\n",
       "      <td>17.042345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101362</th>\n",
       "      <td>16390024</td>\n",
       "      <td>2014-10-19</td>\n",
       "      <td>1</td>\n",
       "      <td>12.949997</td>\n",
       "      <td>12.949997</td>\n",
       "      <td>12.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>12.949997</td>\n",
       "      <td>32.436018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101406</th>\n",
       "      <td>16417739</td>\n",
       "      <td>2014-11-03</td>\n",
       "      <td>2</td>\n",
       "      <td>25.849993</td>\n",
       "      <td>25.849993</td>\n",
       "      <td>25.849993</td>\n",
       "      <td>1</td>\n",
       "      <td>11.949997</td>\n",
       "      <td>66.888646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101425</th>\n",
       "      <td>16430859</td>\n",
       "      <td>2014-11-22</td>\n",
       "      <td>7</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>10.904994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101434</th>\n",
       "      <td>16435478</td>\n",
       "      <td>2014-11-10</td>\n",
       "      <td>2</td>\n",
       "      <td>79.899963</td>\n",
       "      <td>79.899963</td>\n",
       "      <td>79.899963</td>\n",
       "      <td>1</td>\n",
       "      <td>79.899963</td>\n",
       "      <td>68.459407</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14729 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              id    orddate  weekday  TotalPrecedingSpend  AvgPrecedingSpend  \\\n",
       "12           957 2014-07-19        7           333.244995          27.770416   \n",
       "13           957 2014-07-29        3           356.044989          27.388076   \n",
       "28          2062 2014-06-02        2           945.168905          67.512065   \n",
       "29          2062 2014-07-13        1          1035.007483          69.000499   \n",
       "65          2232 2014-02-02        1          1343.310947          38.380313   \n",
       "66          2232 2014-03-12        4          1353.260944          37.590582   \n",
       "101         4251 2014-10-12        1           607.213722          55.201247   \n",
       "103         4642 2014-01-05        1            27.799988          27.799988   \n",
       "123         5002 2014-10-19        1           642.402832          33.810675   \n",
       "163         6084 2014-02-19        4          1532.841331          39.303624   \n",
       "164         6084 2014-03-08        7          1569.691322          39.242283   \n",
       "165         6084 2014-03-19        4          1622.231297          39.566617   \n",
       "166         6084 2014-04-01        3          1678.881275          39.973364   \n",
       "167         6084 2014-04-22        3          1735.681263          40.364681   \n",
       "168         6084 2014-05-05        2          1784.281246          40.551847   \n",
       "169         6084 2014-06-02        2          1840.381222          40.897360   \n",
       "170         6084 2014-06-17        3          1873.211208          40.721983   \n",
       "171         6084 2014-06-30        2          1905.961195          40.552366   \n",
       "172         6084 2014-07-13        1          1956.201179          40.754191   \n",
       "173         6084 2014-09-01        2          1998.851158          40.792881   \n",
       "174         6084 2014-09-07        1          2049.591143          40.991823   \n",
       "175         6084 2014-09-21        1          2072.391130          40.635120   \n",
       "176         6084 2014-10-05        1          2107.591114          40.530598   \n",
       "177         6084 2014-10-22        4          2155.341103          40.666813   \n",
       "178         6084 2014-10-29        4          2198.041084          40.704465   \n",
       "187         6130 2014-08-09        7           227.789341          28.473668   \n",
       "202         7072 2014-02-05        4           158.096554          22.585222   \n",
       "203         7072 2014-10-13        2           171.046551          21.380819   \n",
       "226         8648 2014-01-07        3           114.979996          11.498000   \n",
       "227         8648 2014-06-15        1           127.879990          11.625454   \n",
       "...          ...        ...      ...                  ...                ...   \n",
       "101225  16332377 2014-09-22        2            24.839989          24.839989   \n",
       "101231  16333241 2014-11-18        3            33.389992          33.389992   \n",
       "101236  16336330 2014-10-04        7            49.889984          49.889984   \n",
       "101237  16336330 2014-11-16        1            59.839981          29.919991   \n",
       "101243  16339150 2014-11-23        1            17.889992          17.889992   \n",
       "101247  16342585 2014-09-30        3            19.899994          19.899994   \n",
       "101248  16342585 2014-10-19        1            53.649981          26.824990   \n",
       "101253  16344090 2014-10-19        1            26.799992          26.799992   \n",
       "101255  16344855 2014-09-29        2           213.929960         213.929960   \n",
       "101256  16344855 2014-10-27        2           221.429960         110.714980   \n",
       "101285  16360249 2014-11-11        3             7.949997           7.949997   \n",
       "101289  16360974 2014-11-11        3            98.249966          98.249966   \n",
       "101291  16362497 2014-09-23        3             0.000000           0.000000   \n",
       "101292  16362497 2014-09-27        7             0.000000           0.000000   \n",
       "101293  16362497 2014-09-30        3             0.000000           0.000000   \n",
       "101294  16362497 2014-10-05        1             0.000000           0.000000   \n",
       "101296  16362551 2014-11-16        1             9.989998           9.989998   \n",
       "101302  16363302 2014-11-02        1             7.949997           7.949997   \n",
       "101303  16363302 2014-11-10        2            61.639980          30.819990   \n",
       "101310  16369106 2014-10-18        7            42.748880          42.748880   \n",
       "101322  16374851 2014-11-11        3             8.949997           8.949997   \n",
       "101323  16374851 2014-11-15        7            44.739985          22.369992   \n",
       "101324  16374851 2014-11-24        2            74.439974          24.813325   \n",
       "101326  16375416 2014-11-04        3            26.701035          26.701035   \n",
       "101335  16377680 2014-10-15        4            15.949997          15.949997   \n",
       "101344  16380720 2014-10-13        2             9.899994           9.899994   \n",
       "101362  16390024 2014-10-19        1            12.949997          12.949997   \n",
       "101406  16417739 2014-11-03        2            25.849993          25.849993   \n",
       "101425  16430859 2014-11-22        7             5.949997           5.949997   \n",
       "101434  16435478 2014-11-10        2            79.899963          79.899963   \n",
       "\n",
       "        PreviousSpend  NumPrecedingVisits  dailySpend     y_pred  \n",
       "12          19.949997                  12   22.799994  33.513387  \n",
       "13          22.799994                  13   26.799990  17.834220  \n",
       "28          90.799971                  14   89.838577  80.521267  \n",
       "29          89.838577                  15   43.599985  57.606519  \n",
       "65          59.699984                  35    9.949997  31.583850  \n",
       "66           9.949997                  36    3.949999  27.544093  \n",
       "101         17.949997                  11   81.389975  47.400041  \n",
       "103         27.799988                   1   22.899994  25.056789  \n",
       "123         28.899994                  19   33.849997  54.553231  \n",
       "163         89.099976                  39   36.849991  47.298953  \n",
       "164         36.849991                  40   52.539974  37.615624  \n",
       "165         52.539974                  41   56.649979  43.988467  \n",
       "166         56.649979                  42   56.799988  35.233944  \n",
       "167         56.799988                  43   48.599983  40.124376  \n",
       "168         48.599983                  44   56.099976  35.062185  \n",
       "169         56.099976                  45   32.829987  37.943221  \n",
       "170         32.829987                  46   32.749987  31.655455  \n",
       "171         32.749987                  47   50.239985  31.027067  \n",
       "172         50.239985                  48   42.649979  42.924256  \n",
       "173         42.649979                  49   50.739985  41.946927  \n",
       "174         50.739985                  50   22.799988  45.309762  \n",
       "175         22.799988                  51   35.199984  35.332422  \n",
       "176         35.199984                  52   47.749989  31.755457  \n",
       "177         47.749989                  53   42.699982  31.991172  \n",
       "178         42.699982                  54   37.739986  34.144523  \n",
       "187         20.849991                   8   16.849991  15.248178  \n",
       "202         21.351490                   7   12.949997  24.073217  \n",
       "203         12.949997                   8   32.889992  27.347693  \n",
       "226         12.799995                  10   12.899994  20.871008  \n",
       "227         12.899994                  11   37.699982  17.093708  \n",
       "...               ...                 ...         ...        ...  \n",
       "101225      24.839989                   1    7.949997  32.839901  \n",
       "101231      33.389992                   1   52.699982  26.362364  \n",
       "101236      49.889984                   1    9.949997  62.731695  \n",
       "101237       9.949997                   2   19.899994  42.123049  \n",
       "101243      17.889992                   1   40.679987  25.862160  \n",
       "101247      19.899994                   1   33.749987  27.637490  \n",
       "101248      33.749987                   2   19.899994  26.723388  \n",
       "101253      26.799992                   1   60.699986  24.189993  \n",
       "101255     213.929960                   1    7.500000  26.946820  \n",
       "101256       7.500000                   2   38.899996  50.653695  \n",
       "101285       7.949997                   1   12.899994  15.343608  \n",
       "101289      98.249966                   1   21.849991  64.831007  \n",
       "101291       0.000000                   1    0.000000  26.658382  \n",
       "101292       0.000000                   2    0.000000  27.682647  \n",
       "101293       0.000000                   3    0.000000  16.330613  \n",
       "101294       0.000000                   4    0.000000   3.352122  \n",
       "101296       9.989998                   1   59.729980  22.403268  \n",
       "101302       7.949997                   1   53.689983  14.847086  \n",
       "101303      53.689983                   2    7.949997  21.295353  \n",
       "101310      42.748880                   1   23.349994  76.540371  \n",
       "101322       8.949997                   1   35.789988   9.011663  \n",
       "101323      35.789988                   2   29.699989  35.500155  \n",
       "101324      29.699989                   3    9.949997  21.500066  \n",
       "101326      26.701035                   1   39.899994  62.679826  \n",
       "101335      15.949997                   1   19.899994  18.616378  \n",
       "101344       9.899994                   1    3.949999  17.042345  \n",
       "101362      12.949997                   1   12.949997  32.436018  \n",
       "101406      25.849993                   1   11.949997  66.888646  \n",
       "101425       5.949997                   1    5.949997  10.904994  \n",
       "101434      79.899963                   1   79.899963  68.459407  \n",
       "\n",
       "[14729 rows x 9 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "residuals = df_test.y_pred - df_test.dailySpend"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(residuals, range=(-50,50));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20.50122664872518"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean_absolute_error(df_test.dailySpend, df_test.y_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prediction for the future"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>weekday</th>\n",
       "      <th>TotalPrecedingSpend</th>\n",
       "      <th>AvgPrecedingSpend</th>\n",
       "      <th>PreviousSpend</th>\n",
       "      <th>NumPrecedingVisits</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>957</td>\n",
       "      <td>2</td>\n",
       "      <td>382.844978</td>\n",
       "      <td>27.346070</td>\n",
       "      <td>45.837303</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2062</td>\n",
       "      <td>2</td>\n",
       "      <td>1078.607468</td>\n",
       "      <td>67.412967</td>\n",
       "      <td>62.658798</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2232</td>\n",
       "      <td>2</td>\n",
       "      <td>1357.210943</td>\n",
       "      <td>36.681377</td>\n",
       "      <td>86.331577</td>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2623</td>\n",
       "      <td>2</td>\n",
       "      <td>152.059544</td>\n",
       "      <td>30.411909</td>\n",
       "      <td>44.431252</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3000</td>\n",
       "      <td>2</td>\n",
       "      <td>258.645792</td>\n",
       "      <td>19.895830</td>\n",
       "      <td>22.854744</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3689</td>\n",
       "      <td>2</td>\n",
       "      <td>137.147575</td>\n",
       "      <td>27.429515</td>\n",
       "      <td>20.349411</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4251</td>\n",
       "      <td>2</td>\n",
       "      <td>688.603697</td>\n",
       "      <td>57.383641</td>\n",
       "      <td>25.436768</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4642</td>\n",
       "      <td>2</td>\n",
       "      <td>50.699982</td>\n",
       "      <td>25.349991</td>\n",
       "      <td>27.799988</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5002</td>\n",
       "      <td>2</td>\n",
       "      <td>676.252829</td>\n",
       "      <td>33.812641</td>\n",
       "      <td>43.204155</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>6084</td>\n",
       "      <td>2</td>\n",
       "      <td>2235.781071</td>\n",
       "      <td>40.650565</td>\n",
       "      <td>15.287621</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6130</td>\n",
       "      <td>2</td>\n",
       "      <td>244.639332</td>\n",
       "      <td>27.182148</td>\n",
       "      <td>34.461063</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6610</td>\n",
       "      <td>2</td>\n",
       "      <td>27.021767</td>\n",
       "      <td>6.755442</td>\n",
       "      <td>6.595665</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>6670</td>\n",
       "      <td>2</td>\n",
       "      <td>138.132240</td>\n",
       "      <td>46.044080</td>\n",
       "      <td>8.589699</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>7072</td>\n",
       "      <td>2</td>\n",
       "      <td>203.936543</td>\n",
       "      <td>22.659616</td>\n",
       "      <td>27.916534</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>7285</td>\n",
       "      <td>2</td>\n",
       "      <td>119.115490</td>\n",
       "      <td>29.778872</td>\n",
       "      <td>40.775513</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7862</td>\n",
       "      <td>2</td>\n",
       "      <td>103.726276</td>\n",
       "      <td>12.965785</td>\n",
       "      <td>10.200272</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8648</td>\n",
       "      <td>2</td>\n",
       "      <td>165.579971</td>\n",
       "      <td>13.798331</td>\n",
       "      <td>12.680031</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>9121</td>\n",
       "      <td>2</td>\n",
       "      <td>231.188212</td>\n",
       "      <td>23.118821</td>\n",
       "      <td>22.369011</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>9377</td>\n",
       "      <td>2</td>\n",
       "      <td>1150.753798</td>\n",
       "      <td>18.560545</td>\n",
       "      <td>8.666389</td>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>9423</td>\n",
       "      <td>2</td>\n",
       "      <td>54.196907</td>\n",
       "      <td>27.098454</td>\n",
       "      <td>39.880737</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>9784</td>\n",
       "      <td>2</td>\n",
       "      <td>520.972939</td>\n",
       "      <td>28.942941</td>\n",
       "      <td>26.382656</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>10855</td>\n",
       "      <td>2</td>\n",
       "      <td>299.886415</td>\n",
       "      <td>29.988642</td>\n",
       "      <td>49.825375</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>11134</td>\n",
       "      <td>2</td>\n",
       "      <td>17.741825</td>\n",
       "      <td>17.741825</td>\n",
       "      <td>17.741825</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>13978</td>\n",
       "      <td>2</td>\n",
       "      <td>9.637848</td>\n",
       "      <td>9.637848</td>\n",
       "      <td>9.637848</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>14001</td>\n",
       "      <td>2</td>\n",
       "      <td>131.350845</td>\n",
       "      <td>13.135085</td>\n",
       "      <td>15.210926</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>14389</td>\n",
       "      <td>2</td>\n",
       "      <td>29.629349</td>\n",
       "      <td>29.629349</td>\n",
       "      <td>29.629349</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>14575</td>\n",
       "      <td>2</td>\n",
       "      <td>63.499973</td>\n",
       "      <td>31.749987</td>\n",
       "      <td>30.799988</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>15113</td>\n",
       "      <td>2</td>\n",
       "      <td>257.214924</td>\n",
       "      <td>13.537628</td>\n",
       "      <td>19.940369</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>15652</td>\n",
       "      <td>2</td>\n",
       "      <td>42.699989</td>\n",
       "      <td>42.699989</td>\n",
       "      <td>42.699989</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>16004</td>\n",
       "      <td>2</td>\n",
       "      <td>180.710178</td>\n",
       "      <td>45.177545</td>\n",
       "      <td>111.972885</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16723</th>\n",
       "      <td>16441249</td>\n",
       "      <td>2</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16724</th>\n",
       "      <td>16441311</td>\n",
       "      <td>2</td>\n",
       "      <td>36.698883</td>\n",
       "      <td>36.698883</td>\n",
       "      <td>36.698883</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16725</th>\n",
       "      <td>16441753</td>\n",
       "      <td>2</td>\n",
       "      <td>25.349993</td>\n",
       "      <td>25.349993</td>\n",
       "      <td>25.349993</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16726</th>\n",
       "      <td>16442440</td>\n",
       "      <td>2</td>\n",
       "      <td>50.650417</td>\n",
       "      <td>50.650417</td>\n",
       "      <td>50.650417</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16727</th>\n",
       "      <td>16442512</td>\n",
       "      <td>2</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16728</th>\n",
       "      <td>16442601</td>\n",
       "      <td>2</td>\n",
       "      <td>24.899994</td>\n",
       "      <td>24.899994</td>\n",
       "      <td>24.899994</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16729</th>\n",
       "      <td>16444124</td>\n",
       "      <td>2</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16730</th>\n",
       "      <td>16444167</td>\n",
       "      <td>2</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16731</th>\n",
       "      <td>16444299</td>\n",
       "      <td>2</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16732</th>\n",
       "      <td>16444426</td>\n",
       "      <td>2</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16733</th>\n",
       "      <td>16444779</td>\n",
       "      <td>2</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16734</th>\n",
       "      <td>16444809</td>\n",
       "      <td>2</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16735</th>\n",
       "      <td>16444868</td>\n",
       "      <td>2</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16736</th>\n",
       "      <td>16445139</td>\n",
       "      <td>2</td>\n",
       "      <td>19.949997</td>\n",
       "      <td>19.949997</td>\n",
       "      <td>19.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16737</th>\n",
       "      <td>16446020</td>\n",
       "      <td>2</td>\n",
       "      <td>17.899994</td>\n",
       "      <td>17.899994</td>\n",
       "      <td>17.899994</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16738</th>\n",
       "      <td>16447050</td>\n",
       "      <td>2</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16739</th>\n",
       "      <td>16448030</td>\n",
       "      <td>2</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16740</th>\n",
       "      <td>16448065</td>\n",
       "      <td>2</td>\n",
       "      <td>49.949982</td>\n",
       "      <td>49.949982</td>\n",
       "      <td>49.949982</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16741</th>\n",
       "      <td>16448081</td>\n",
       "      <td>2</td>\n",
       "      <td>3.949999</td>\n",
       "      <td>3.949999</td>\n",
       "      <td>3.949999</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16742</th>\n",
       "      <td>16448510</td>\n",
       "      <td>2</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16743</th>\n",
       "      <td>16451821</td>\n",
       "      <td>2</td>\n",
       "      <td>89.699982</td>\n",
       "      <td>89.699982</td>\n",
       "      <td>89.699982</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16744</th>\n",
       "      <td>16451899</td>\n",
       "      <td>2</td>\n",
       "      <td>19.799988</td>\n",
       "      <td>19.799988</td>\n",
       "      <td>19.799988</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16745</th>\n",
       "      <td>16453115</td>\n",
       "      <td>2</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16746</th>\n",
       "      <td>16453182</td>\n",
       "      <td>2</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16747</th>\n",
       "      <td>16453395</td>\n",
       "      <td>2</td>\n",
       "      <td>24.799988</td>\n",
       "      <td>24.799988</td>\n",
       "      <td>24.799988</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16748</th>\n",
       "      <td>16453760</td>\n",
       "      <td>2</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16749</th>\n",
       "      <td>16455134</td>\n",
       "      <td>2</td>\n",
       "      <td>162.499941</td>\n",
       "      <td>162.499941</td>\n",
       "      <td>162.499941</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16750</th>\n",
       "      <td>16455606</td>\n",
       "      <td>2</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16751</th>\n",
       "      <td>16455720</td>\n",
       "      <td>2</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16752</th>\n",
       "      <td>16456238</td>\n",
       "      <td>2</td>\n",
       "      <td>93.439701</td>\n",
       "      <td>93.439701</td>\n",
       "      <td>93.439701</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16753 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  weekday  TotalPrecedingSpend  AvgPrecedingSpend  \\\n",
       "0           957        2           382.844978          27.346070   \n",
       "1          2062        2          1078.607468          67.412967   \n",
       "2          2232        2          1357.210943          36.681377   \n",
       "3          2623        2           152.059544          30.411909   \n",
       "4          3000        2           258.645792          19.895830   \n",
       "5          3689        2           137.147575          27.429515   \n",
       "6          4251        2           688.603697          57.383641   \n",
       "7          4642        2            50.699982          25.349991   \n",
       "8          5002        2           676.252829          33.812641   \n",
       "9          6084        2          2235.781071          40.650565   \n",
       "10         6130        2           244.639332          27.182148   \n",
       "11         6610        2            27.021767           6.755442   \n",
       "12         6670        2           138.132240          46.044080   \n",
       "13         7072        2           203.936543          22.659616   \n",
       "14         7285        2           119.115490          29.778872   \n",
       "15         7862        2           103.726276          12.965785   \n",
       "16         8648        2           165.579971          13.798331   \n",
       "17         9121        2           231.188212          23.118821   \n",
       "18         9377        2          1150.753798          18.560545   \n",
       "19         9423        2            54.196907          27.098454   \n",
       "20         9784        2           520.972939          28.942941   \n",
       "21        10855        2           299.886415          29.988642   \n",
       "22        11134        2            17.741825          17.741825   \n",
       "23        13978        2             9.637848           9.637848   \n",
       "24        14001        2           131.350845          13.135085   \n",
       "25        14389        2            29.629349          29.629349   \n",
       "26        14575        2            63.499973          31.749987   \n",
       "27        15113        2           257.214924          13.537628   \n",
       "28        15652        2            42.699989          42.699989   \n",
       "29        16004        2           180.710178          45.177545   \n",
       "...         ...      ...                  ...                ...   \n",
       "16723  16441249        2             9.949997           9.949997   \n",
       "16724  16441311        2            36.698883          36.698883   \n",
       "16725  16441753        2            25.349993          25.349993   \n",
       "16726  16442440        2            50.650417          50.650417   \n",
       "16727  16442512        2            29.949997          29.949997   \n",
       "16728  16442601        2            24.899994          24.899994   \n",
       "16729  16444124        2            24.949997          24.949997   \n",
       "16730  16444167        2             9.949997           9.949997   \n",
       "16731  16444299        2            18.000000          18.000000   \n",
       "16732  16444426        2            19.899994          19.899994   \n",
       "16733  16444779        2            29.899994          29.899994   \n",
       "16734  16444809        2            12.899994          12.899994   \n",
       "16735  16444868        2             8.949997           8.949997   \n",
       "16736  16445139        2            19.949997          19.949997   \n",
       "16737  16446020        2            17.899994          17.899994   \n",
       "16738  16447050        2            24.949997          24.949997   \n",
       "16739  16448030        2             5.949997           5.949997   \n",
       "16740  16448065        2            49.949982          49.949982   \n",
       "16741  16448081        2             3.949999           3.949999   \n",
       "16742  16448510        2             7.949997           7.949997   \n",
       "16743  16451821        2            89.699982          89.699982   \n",
       "16744  16451899        2            19.799988          19.799988   \n",
       "16745  16453115        2            19.899994          19.899994   \n",
       "16746  16453182        2            29.899994          29.899994   \n",
       "16747  16453395        2            24.799988          24.799988   \n",
       "16748  16453760        2             9.949997           9.949997   \n",
       "16749  16455134        2           162.499941         162.499941   \n",
       "16750  16455606        2            29.949997          29.949997   \n",
       "16751  16455720        2             9.899994           9.899994   \n",
       "16752  16456238        2            93.439701          93.439701   \n",
       "\n",
       "       PreviousSpend  NumPrecedingVisits  \n",
       "0          45.837303                  14  \n",
       "1          62.658798                  16  \n",
       "2          86.331577                  37  \n",
       "3          44.431252                   5  \n",
       "4          22.854744                  13  \n",
       "5          20.349411                   5  \n",
       "6          25.436768                  12  \n",
       "7          27.799988                   2  \n",
       "8          43.204155                  20  \n",
       "9          15.287621                  55  \n",
       "10         34.461063                   9  \n",
       "11          6.595665                   4  \n",
       "12          8.589699                   3  \n",
       "13         27.916534                   9  \n",
       "14         40.775513                   4  \n",
       "15         10.200272                   8  \n",
       "16         12.680031                  12  \n",
       "17         22.369011                  10  \n",
       "18          8.666389                  62  \n",
       "19         39.880737                   2  \n",
       "20         26.382656                  18  \n",
       "21         49.825375                  10  \n",
       "22         17.741825                   1  \n",
       "23          9.637848                   1  \n",
       "24         15.210926                  10  \n",
       "25         29.629349                   1  \n",
       "26         30.799988                   2  \n",
       "27         19.940369                  19  \n",
       "28         42.699989                   1  \n",
       "29        111.972885                   4  \n",
       "...              ...                 ...  \n",
       "16723       9.949997                   1  \n",
       "16724      36.698883                   1  \n",
       "16725      25.349993                   1  \n",
       "16726      50.650417                   1  \n",
       "16727      29.949997                   1  \n",
       "16728      24.899994                   1  \n",
       "16729      24.949997                   1  \n",
       "16730       9.949997                   1  \n",
       "16731      18.000000                   1  \n",
       "16732      19.899994                   1  \n",
       "16733      29.899994                   1  \n",
       "16734      12.899994                   1  \n",
       "16735       8.949997                   1  \n",
       "16736      19.949997                   1  \n",
       "16737      17.899994                   1  \n",
       "16738      24.949997                   1  \n",
       "16739       5.949997                   1  \n",
       "16740      49.949982                   1  \n",
       "16741       3.949999                   1  \n",
       "16742       7.949997                   1  \n",
       "16743      89.699982                   1  \n",
       "16744      19.799988                   1  \n",
       "16745      19.899994                   1  \n",
       "16746      29.899994                   1  \n",
       "16747      24.799988                   1  \n",
       "16748       9.949997                   1  \n",
       "16749     162.499941                   1  \n",
       "16750      29.949997                   1  \n",
       "16751       9.899994                   1  \n",
       "16752      93.439701                   1  \n",
       "\n",
       "[16753 rows x 6 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_features_and_spends_for_prediction = pd.read_sql_query(\"\"\"SELECT id,\n",
    "    2 as weekday,\n",
    "       Sum(dailySpend)  as TotalPrecedingSpend,\n",
    "    Avg(dailySpend) \n",
    "         as AvgPrecedingSpend,\n",
    "        LAST_VALUE(dailySpend) OVER (partition by id order by id, orddate) as PreviousSpend,\n",
    "    Count(dailySpend)  as NumPrecedingVisits\n",
    "FROM   customerDailySpend \n",
    "GROUP  BY id\n",
    "ORDER BY id \"\"\", dbConnection)\n",
    "df_features_and_spends_for_prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_future = m.predict(df_features_and_spends_for_prediction.drop([\"id\"], axis=1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_features_and_spends_for_prediction[\"y_pred_future\"] = y_pred_future"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>weekday</th>\n",
       "      <th>TotalPrecedingSpend</th>\n",
       "      <th>AvgPrecedingSpend</th>\n",
       "      <th>PreviousSpend</th>\n",
       "      <th>NumPrecedingVisits</th>\n",
       "      <th>y_pred_future</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>957</td>\n",
       "      <td>2</td>\n",
       "      <td>382.844978</td>\n",
       "      <td>27.346070</td>\n",
       "      <td>45.837303</td>\n",
       "      <td>14</td>\n",
       "      <td>22.316426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2062</td>\n",
       "      <td>2</td>\n",
       "      <td>1078.607468</td>\n",
       "      <td>67.412967</td>\n",
       "      <td>62.658798</td>\n",
       "      <td>16</td>\n",
       "      <td>41.025150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2232</td>\n",
       "      <td>2</td>\n",
       "      <td>1357.210943</td>\n",
       "      <td>36.681377</td>\n",
       "      <td>86.331577</td>\n",
       "      <td>37</td>\n",
       "      <td>40.972302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2623</td>\n",
       "      <td>2</td>\n",
       "      <td>152.059544</td>\n",
       "      <td>30.411909</td>\n",
       "      <td>44.431252</td>\n",
       "      <td>5</td>\n",
       "      <td>31.733879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3000</td>\n",
       "      <td>2</td>\n",
       "      <td>258.645792</td>\n",
       "      <td>19.895830</td>\n",
       "      <td>22.854744</td>\n",
       "      <td>13</td>\n",
       "      <td>16.064438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3689</td>\n",
       "      <td>2</td>\n",
       "      <td>137.147575</td>\n",
       "      <td>27.429515</td>\n",
       "      <td>20.349411</td>\n",
       "      <td>5</td>\n",
       "      <td>29.277434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>4251</td>\n",
       "      <td>2</td>\n",
       "      <td>688.603697</td>\n",
       "      <td>57.383641</td>\n",
       "      <td>25.436768</td>\n",
       "      <td>12</td>\n",
       "      <td>47.425355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4642</td>\n",
       "      <td>2</td>\n",
       "      <td>50.699982</td>\n",
       "      <td>25.349991</td>\n",
       "      <td>27.799988</td>\n",
       "      <td>2</td>\n",
       "      <td>35.318720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>5002</td>\n",
       "      <td>2</td>\n",
       "      <td>676.252829</td>\n",
       "      <td>33.812641</td>\n",
       "      <td>43.204155</td>\n",
       "      <td>20</td>\n",
       "      <td>37.709102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>6084</td>\n",
       "      <td>2</td>\n",
       "      <td>2235.781071</td>\n",
       "      <td>40.650565</td>\n",
       "      <td>15.287621</td>\n",
       "      <td>55</td>\n",
       "      <td>53.625515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6130</td>\n",
       "      <td>2</td>\n",
       "      <td>244.639332</td>\n",
       "      <td>27.182148</td>\n",
       "      <td>34.461063</td>\n",
       "      <td>9</td>\n",
       "      <td>27.587429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>6610</td>\n",
       "      <td>2</td>\n",
       "      <td>27.021767</td>\n",
       "      <td>6.755442</td>\n",
       "      <td>6.595665</td>\n",
       "      <td>4</td>\n",
       "      <td>13.535738</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>6670</td>\n",
       "      <td>2</td>\n",
       "      <td>138.132240</td>\n",
       "      <td>46.044080</td>\n",
       "      <td>8.589699</td>\n",
       "      <td>3</td>\n",
       "      <td>30.522097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>7072</td>\n",
       "      <td>2</td>\n",
       "      <td>203.936543</td>\n",
       "      <td>22.659616</td>\n",
       "      <td>27.916534</td>\n",
       "      <td>9</td>\n",
       "      <td>10.439755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>7285</td>\n",
       "      <td>2</td>\n",
       "      <td>119.115490</td>\n",
       "      <td>29.778872</td>\n",
       "      <td>40.775513</td>\n",
       "      <td>4</td>\n",
       "      <td>40.749504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>7862</td>\n",
       "      <td>2</td>\n",
       "      <td>103.726276</td>\n",
       "      <td>12.965785</td>\n",
       "      <td>10.200272</td>\n",
       "      <td>8</td>\n",
       "      <td>13.643820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>8648</td>\n",
       "      <td>2</td>\n",
       "      <td>165.579971</td>\n",
       "      <td>13.798331</td>\n",
       "      <td>12.680031</td>\n",
       "      <td>12</td>\n",
       "      <td>14.579385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>9121</td>\n",
       "      <td>2</td>\n",
       "      <td>231.188212</td>\n",
       "      <td>23.118821</td>\n",
       "      <td>22.369011</td>\n",
       "      <td>10</td>\n",
       "      <td>27.734068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>9377</td>\n",
       "      <td>2</td>\n",
       "      <td>1150.753798</td>\n",
       "      <td>18.560545</td>\n",
       "      <td>8.666389</td>\n",
       "      <td>62</td>\n",
       "      <td>9.472996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>9423</td>\n",
       "      <td>2</td>\n",
       "      <td>54.196907</td>\n",
       "      <td>27.098454</td>\n",
       "      <td>39.880737</td>\n",
       "      <td>2</td>\n",
       "      <td>28.614620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>9784</td>\n",
       "      <td>2</td>\n",
       "      <td>520.972939</td>\n",
       "      <td>28.942941</td>\n",
       "      <td>26.382656</td>\n",
       "      <td>18</td>\n",
       "      <td>43.114114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>10855</td>\n",
       "      <td>2</td>\n",
       "      <td>299.886415</td>\n",
       "      <td>29.988642</td>\n",
       "      <td>49.825375</td>\n",
       "      <td>10</td>\n",
       "      <td>48.575933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>11134</td>\n",
       "      <td>2</td>\n",
       "      <td>17.741825</td>\n",
       "      <td>17.741825</td>\n",
       "      <td>17.741825</td>\n",
       "      <td>1</td>\n",
       "      <td>28.100597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>13978</td>\n",
       "      <td>2</td>\n",
       "      <td>9.637848</td>\n",
       "      <td>9.637848</td>\n",
       "      <td>9.637848</td>\n",
       "      <td>1</td>\n",
       "      <td>15.752969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>14001</td>\n",
       "      <td>2</td>\n",
       "      <td>131.350845</td>\n",
       "      <td>13.135085</td>\n",
       "      <td>15.210926</td>\n",
       "      <td>10</td>\n",
       "      <td>13.021636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>14389</td>\n",
       "      <td>2</td>\n",
       "      <td>29.629349</td>\n",
       "      <td>29.629349</td>\n",
       "      <td>29.629349</td>\n",
       "      <td>1</td>\n",
       "      <td>31.904606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>14575</td>\n",
       "      <td>2</td>\n",
       "      <td>63.499973</td>\n",
       "      <td>31.749987</td>\n",
       "      <td>30.799988</td>\n",
       "      <td>2</td>\n",
       "      <td>28.319865</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>15113</td>\n",
       "      <td>2</td>\n",
       "      <td>257.214924</td>\n",
       "      <td>13.537628</td>\n",
       "      <td>19.940369</td>\n",
       "      <td>19</td>\n",
       "      <td>11.098484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>15652</td>\n",
       "      <td>2</td>\n",
       "      <td>42.699989</td>\n",
       "      <td>42.699989</td>\n",
       "      <td>42.699989</td>\n",
       "      <td>1</td>\n",
       "      <td>38.684330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>16004</td>\n",
       "      <td>2</td>\n",
       "      <td>180.710178</td>\n",
       "      <td>45.177545</td>\n",
       "      <td>111.972885</td>\n",
       "      <td>4</td>\n",
       "      <td>51.192325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16723</th>\n",
       "      <td>16441249</td>\n",
       "      <td>2</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>21.905291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16724</th>\n",
       "      <td>16441311</td>\n",
       "      <td>2</td>\n",
       "      <td>36.698883</td>\n",
       "      <td>36.698883</td>\n",
       "      <td>36.698883</td>\n",
       "      <td>1</td>\n",
       "      <td>25.427546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16725</th>\n",
       "      <td>16441753</td>\n",
       "      <td>2</td>\n",
       "      <td>25.349993</td>\n",
       "      <td>25.349993</td>\n",
       "      <td>25.349993</td>\n",
       "      <td>1</td>\n",
       "      <td>23.395029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16726</th>\n",
       "      <td>16442440</td>\n",
       "      <td>2</td>\n",
       "      <td>50.650417</td>\n",
       "      <td>50.650417</td>\n",
       "      <td>50.650417</td>\n",
       "      <td>1</td>\n",
       "      <td>47.486390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16727</th>\n",
       "      <td>16442512</td>\n",
       "      <td>2</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>61.604539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16728</th>\n",
       "      <td>16442601</td>\n",
       "      <td>2</td>\n",
       "      <td>24.899994</td>\n",
       "      <td>24.899994</td>\n",
       "      <td>24.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>21.975495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16729</th>\n",
       "      <td>16444124</td>\n",
       "      <td>2</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>26.765508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16730</th>\n",
       "      <td>16444167</td>\n",
       "      <td>2</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>21.905291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16731</th>\n",
       "      <td>16444299</td>\n",
       "      <td>2</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>1</td>\n",
       "      <td>29.882251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16732</th>\n",
       "      <td>16444426</td>\n",
       "      <td>2</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>28.019995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16733</th>\n",
       "      <td>16444779</td>\n",
       "      <td>2</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>22.323099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16734</th>\n",
       "      <td>16444809</td>\n",
       "      <td>2</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>12.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>12.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16735</th>\n",
       "      <td>16444868</td>\n",
       "      <td>2</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>8.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>7.891627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16736</th>\n",
       "      <td>16445139</td>\n",
       "      <td>2</td>\n",
       "      <td>19.949997</td>\n",
       "      <td>19.949997</td>\n",
       "      <td>19.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>18.651662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16737</th>\n",
       "      <td>16446020</td>\n",
       "      <td>2</td>\n",
       "      <td>17.899994</td>\n",
       "      <td>17.899994</td>\n",
       "      <td>17.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>19.106525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16738</th>\n",
       "      <td>16447050</td>\n",
       "      <td>2</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>24.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>26.765508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16739</th>\n",
       "      <td>16448030</td>\n",
       "      <td>2</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>5.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>27.582176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16740</th>\n",
       "      <td>16448065</td>\n",
       "      <td>2</td>\n",
       "      <td>49.949982</td>\n",
       "      <td>49.949982</td>\n",
       "      <td>49.949982</td>\n",
       "      <td>1</td>\n",
       "      <td>32.192838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16741</th>\n",
       "      <td>16448081</td>\n",
       "      <td>2</td>\n",
       "      <td>3.949999</td>\n",
       "      <td>3.949999</td>\n",
       "      <td>3.949999</td>\n",
       "      <td>1</td>\n",
       "      <td>22.151856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16742</th>\n",
       "      <td>16448510</td>\n",
       "      <td>2</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>7.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>23.147243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16743</th>\n",
       "      <td>16451821</td>\n",
       "      <td>2</td>\n",
       "      <td>89.699982</td>\n",
       "      <td>89.699982</td>\n",
       "      <td>89.699982</td>\n",
       "      <td>1</td>\n",
       "      <td>49.000439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16744</th>\n",
       "      <td>16451899</td>\n",
       "      <td>2</td>\n",
       "      <td>19.799988</td>\n",
       "      <td>19.799988</td>\n",
       "      <td>19.799988</td>\n",
       "      <td>1</td>\n",
       "      <td>19.715698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16745</th>\n",
       "      <td>16453115</td>\n",
       "      <td>2</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>19.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>28.019995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16746</th>\n",
       "      <td>16453182</td>\n",
       "      <td>2</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>29.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>22.323099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16747</th>\n",
       "      <td>16453395</td>\n",
       "      <td>2</td>\n",
       "      <td>24.799988</td>\n",
       "      <td>24.799988</td>\n",
       "      <td>24.799988</td>\n",
       "      <td>1</td>\n",
       "      <td>28.829294</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16748</th>\n",
       "      <td>16453760</td>\n",
       "      <td>2</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>9.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>21.905291</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16749</th>\n",
       "      <td>16455134</td>\n",
       "      <td>2</td>\n",
       "      <td>162.499941</td>\n",
       "      <td>162.499941</td>\n",
       "      <td>162.499941</td>\n",
       "      <td>1</td>\n",
       "      <td>93.044714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16750</th>\n",
       "      <td>16455606</td>\n",
       "      <td>2</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>29.949997</td>\n",
       "      <td>1</td>\n",
       "      <td>61.604539</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16751</th>\n",
       "      <td>16455720</td>\n",
       "      <td>2</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>9.899994</td>\n",
       "      <td>1</td>\n",
       "      <td>17.042345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16752</th>\n",
       "      <td>16456238</td>\n",
       "      <td>2</td>\n",
       "      <td>93.439701</td>\n",
       "      <td>93.439701</td>\n",
       "      <td>93.439701</td>\n",
       "      <td>1</td>\n",
       "      <td>41.417183</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16753 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             id  weekday  TotalPrecedingSpend  AvgPrecedingSpend  \\\n",
       "0           957        2           382.844978          27.346070   \n",
       "1          2062        2          1078.607468          67.412967   \n",
       "2          2232        2          1357.210943          36.681377   \n",
       "3          2623        2           152.059544          30.411909   \n",
       "4          3000        2           258.645792          19.895830   \n",
       "5          3689        2           137.147575          27.429515   \n",
       "6          4251        2           688.603697          57.383641   \n",
       "7          4642        2            50.699982          25.349991   \n",
       "8          5002        2           676.252829          33.812641   \n",
       "9          6084        2          2235.781071          40.650565   \n",
       "10         6130        2           244.639332          27.182148   \n",
       "11         6610        2            27.021767           6.755442   \n",
       "12         6670        2           138.132240          46.044080   \n",
       "13         7072        2           203.936543          22.659616   \n",
       "14         7285        2           119.115490          29.778872   \n",
       "15         7862        2           103.726276          12.965785   \n",
       "16         8648        2           165.579971          13.798331   \n",
       "17         9121        2           231.188212          23.118821   \n",
       "18         9377        2          1150.753798          18.560545   \n",
       "19         9423        2            54.196907          27.098454   \n",
       "20         9784        2           520.972939          28.942941   \n",
       "21        10855        2           299.886415          29.988642   \n",
       "22        11134        2            17.741825          17.741825   \n",
       "23        13978        2             9.637848           9.637848   \n",
       "24        14001        2           131.350845          13.135085   \n",
       "25        14389        2            29.629349          29.629349   \n",
       "26        14575        2            63.499973          31.749987   \n",
       "27        15113        2           257.214924          13.537628   \n",
       "28        15652        2            42.699989          42.699989   \n",
       "29        16004        2           180.710178          45.177545   \n",
       "...         ...      ...                  ...                ...   \n",
       "16723  16441249        2             9.949997           9.949997   \n",
       "16724  16441311        2            36.698883          36.698883   \n",
       "16725  16441753        2            25.349993          25.349993   \n",
       "16726  16442440        2            50.650417          50.650417   \n",
       "16727  16442512        2            29.949997          29.949997   \n",
       "16728  16442601        2            24.899994          24.899994   \n",
       "16729  16444124        2            24.949997          24.949997   \n",
       "16730  16444167        2             9.949997           9.949997   \n",
       "16731  16444299        2            18.000000          18.000000   \n",
       "16732  16444426        2            19.899994          19.899994   \n",
       "16733  16444779        2            29.899994          29.899994   \n",
       "16734  16444809        2            12.899994          12.899994   \n",
       "16735  16444868        2             8.949997           8.949997   \n",
       "16736  16445139        2            19.949997          19.949997   \n",
       "16737  16446020        2            17.899994          17.899994   \n",
       "16738  16447050        2            24.949997          24.949997   \n",
       "16739  16448030        2             5.949997           5.949997   \n",
       "16740  16448065        2            49.949982          49.949982   \n",
       "16741  16448081        2             3.949999           3.949999   \n",
       "16742  16448510        2             7.949997           7.949997   \n",
       "16743  16451821        2            89.699982          89.699982   \n",
       "16744  16451899        2            19.799988          19.799988   \n",
       "16745  16453115        2            19.899994          19.899994   \n",
       "16746  16453182        2            29.899994          29.899994   \n",
       "16747  16453395        2            24.799988          24.799988   \n",
       "16748  16453760        2             9.949997           9.949997   \n",
       "16749  16455134        2           162.499941         162.499941   \n",
       "16750  16455606        2            29.949997          29.949997   \n",
       "16751  16455720        2             9.899994           9.899994   \n",
       "16752  16456238        2            93.439701          93.439701   \n",
       "\n",
       "       PreviousSpend  NumPrecedingVisits  y_pred_future  \n",
       "0          45.837303                  14      22.316426  \n",
       "1          62.658798                  16      41.025150  \n",
       "2          86.331577                  37      40.972302  \n",
       "3          44.431252                   5      31.733879  \n",
       "4          22.854744                  13      16.064438  \n",
       "5          20.349411                   5      29.277434  \n",
       "6          25.436768                  12      47.425355  \n",
       "7          27.799988                   2      35.318720  \n",
       "8          43.204155                  20      37.709102  \n",
       "9          15.287621                  55      53.625515  \n",
       "10         34.461063                   9      27.587429  \n",
       "11          6.595665                   4      13.535738  \n",
       "12          8.589699                   3      30.522097  \n",
       "13         27.916534                   9      10.439755  \n",
       "14         40.775513                   4      40.749504  \n",
       "15         10.200272                   8      13.643820  \n",
       "16         12.680031                  12      14.579385  \n",
       "17         22.369011                  10      27.734068  \n",
       "18          8.666389                  62       9.472996  \n",
       "19         39.880737                   2      28.614620  \n",
       "20         26.382656                  18      43.114114  \n",
       "21         49.825375                  10      48.575933  \n",
       "22         17.741825                   1      28.100597  \n",
       "23          9.637848                   1      15.752969  \n",
       "24         15.210926                  10      13.021636  \n",
       "25         29.629349                   1      31.904606  \n",
       "26         30.799988                   2      28.319865  \n",
       "27         19.940369                  19      11.098484  \n",
       "28         42.699989                   1      38.684330  \n",
       "29        111.972885                   4      51.192325  \n",
       "...              ...                 ...            ...  \n",
       "16723       9.949997                   1      21.905291  \n",
       "16724      36.698883                   1      25.427546  \n",
       "16725      25.349993                   1      23.395029  \n",
       "16726      50.650417                   1      47.486390  \n",
       "16727      29.949997                   1      61.604539  \n",
       "16728      24.899994                   1      21.975495  \n",
       "16729      24.949997                   1      26.765508  \n",
       "16730       9.949997                   1      21.905291  \n",
       "16731      18.000000                   1      29.882251  \n",
       "16732      19.899994                   1      28.019995  \n",
       "16733      29.899994                   1      22.323099  \n",
       "16734      12.899994                   1      12.000000  \n",
       "16735       8.949997                   1       7.891627  \n",
       "16736      19.949997                   1      18.651662  \n",
       "16737      17.899994                   1      19.106525  \n",
       "16738      24.949997                   1      26.765508  \n",
       "16739       5.949997                   1      27.582176  \n",
       "16740      49.949982                   1      32.192838  \n",
       "16741       3.949999                   1      22.151856  \n",
       "16742       7.949997                   1      23.147243  \n",
       "16743      89.699982                   1      49.000439  \n",
       "16744      19.799988                   1      19.715698  \n",
       "16745      19.899994                   1      28.019995  \n",
       "16746      29.899994                   1      22.323099  \n",
       "16747      24.799988                   1      28.829294  \n",
       "16748       9.949997                   1      21.905291  \n",
       "16749     162.499941                   1      93.044714  \n",
       "16750      29.949997                   1      61.604539  \n",
       "16751       9.899994                   1      17.042345  \n",
       "16752      93.439701                   1      41.417183  \n",
       "\n",
       "[16753 rows x 7 columns]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_features_and_spends_for_prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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