notebooks/Modeling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center style=\"font-size:48px;\">Modeling</center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>My attempt at utilizing machine learning to identify some initial data ppints to further invesigate</center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import Libraries and Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data Science\n",
    "import pandas as pd\n",
    "import joblib\n",
    "\n",
    "# Machine Learning\n",
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.ensemble import IsolationForest\n",
    "from sklearn.neighbors import LocalOutlierFactor\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.preprocessing import OneHotEncoder"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Location\n",
    "locations = pd.read_csv('../CheckPoints/Locations_Clean.csv', parse_dates=['Timestamp'], index_col=0)\n",
    "# Purchase Data\n",
    "buys = pd.read_csv('../CheckPoints/Buys_Clean.csv', parse_dates=['timestamp'], index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Helper Functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "def findOutliers(model, df):\n",
    "    preds = model.fit_predict(df)\n",
    "    temp = pd.DataFrame(preds)\n",
    "    if len(temp[0].unique()) == 1:\n",
    "        print('No Outliers Detected. All points belong to same cluster.')\n",
    "    else:\n",
    "        outs = [ True if x == -1 else False for x in preds]\n",
    "        display(df[outs])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Machine Learning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Location"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a preprocessing pipeline. We need to drop the timestamp column as we already have the datetime parts seperated into their own variable. We can also drop the CarID variable as there is a one to one relationship with the CarID. We will need to encode the names variables as well as the job title and type."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "locPreprocessor = ColumnTransformer(\n",
    "    [\n",
    "        ( 'dropper', 'drop', ['Timestamp', 'id'] ),\n",
    "        ('encoder', OneHotEncoder(), ['LastName', 'FirstName', 'CurrentEmploymentType', 'CurrentEmploymentTitle'])\n",
    "    ],\n",
    "    remainder='passthrough'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use two algorithms that are implmented in scikit-learn; IsolationForest and LocalOutlierFactor. First lets look at IsolationForest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No Outliers Detected. All points belong to same cluster.\n"
     ]
    }
   ],
   "source": [
    "# Model Pipeline\n",
    "locIso = Pipeline(\n",
    "    [\n",
    "        ('preprocessor', locPreprocessor),\n",
    "        ('model', IsolationForest())\n",
    "    ]\n",
    ")\n",
    "# Find Outliers\n",
    "findOutliers(locIso, locations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks like this algorithm didnt find any outliers.\n",
    "\n",
    "Now lets try LocalOutlierFactor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FirstName</th>\n",
       "      <th>LastName</th>\n",
       "      <th>CurrentEmploymentType</th>\n",
       "      <th>CurrentEmploymentTitle</th>\n",
       "      <th>Timestamp</th>\n",
       "      <th>id</th>\n",
       "      <th>lat</th>\n",
       "      <th>long</th>\n",
       "      <th>day</th>\n",
       "      <th>hour</th>\n",
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       "      <th>Weekend</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "    <tr>\n",
       "      <th>66601</th>\n",
       "      <td>Bertrand</td>\n",
       "      <td>Ovan</td>\n",
       "      <td>Facilities</td>\n",
       "      <td>Facilities Group Manager</td>\n",
       "      <td>2014-01-12 00:00:00</td>\n",
       "      <td>29.0</td>\n",
       "      <td>36.059926</td>\n",
       "      <td>24.893272</td>\n",
       "      <td>12.0</td>\n",
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       "      <td>Elsa</td>\n",
       "      <td>Orilla</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Drill Technician</td>\n",
       "      <td>2014-01-19 00:00:00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>36.068748</td>\n",
       "      <td>24.882666</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>154321</th>\n",
       "      <td>Elsa</td>\n",
       "      <td>Orilla</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Drill Technician</td>\n",
       "      <td>2014-01-19 00:01:00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>36.071066</td>\n",
       "      <td>24.879613</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>154322</th>\n",
       "      <td>Elsa</td>\n",
       "      <td>Orilla</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Drill Technician</td>\n",
       "      <td>2014-01-19 00:02:00</td>\n",
       "      <td>28.0</td>\n",
       "      <td>36.072861</td>\n",
       "      <td>24.876743</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225301</th>\n",
       "      <td>Hennie</td>\n",
       "      <td>Osvaldo</td>\n",
       "      <td>Security</td>\n",
       "      <td>Perimeter Control</td>\n",
       "      <td>2014-01-14 03:43:00</td>\n",
       "      <td>21.0</td>\n",
       "      <td>36.060828</td>\n",
       "      <td>24.904150</td>\n",
       "      <td>14.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>330356</th>\n",
       "      <td>Isia</td>\n",
       "      <td>Vann</td>\n",
       "      <td>Security</td>\n",
       "      <td>Perimeter Control</td>\n",
       "      <td>2014-01-07 01:10:00</td>\n",
       "      <td>16.0</td>\n",
       "      <td>36.076832</td>\n",
       "      <td>24.865878</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464669</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-07 01:10:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.050386</td>\n",
       "      <td>24.879576</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>464670</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-07 01:11:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.053128</td>\n",
       "      <td>24.882471</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464671</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-07 01:12:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.058610</td>\n",
       "      <td>24.882478</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>464672</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-07 01:13:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.063921</td>\n",
       "      <td>24.882584</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>464673</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-07 01:14:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.066439</td>\n",
       "      <td>24.882594</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>477568</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-16 00:09:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.050603</td>\n",
       "      <td>24.879577</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477569</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-16 00:10:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.053303</td>\n",
       "      <td>24.882473</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477570</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-16 00:11:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.058443</td>\n",
       "      <td>24.882485</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477571</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-16 00:12:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.063360</td>\n",
       "      <td>24.882597</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>477572</th>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "      <td>2014-01-16 00:13:00</td>\n",
       "      <td>1.0</td>\n",
       "      <td>36.066387</td>\n",
       "      <td>24.882620</td>\n",
       "      <td>16.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "       FirstName LastName   CurrentEmploymentType    CurrentEmploymentTitle  \\\n",
       "66601   Bertrand     Ovan              Facilities  Facilities Group Manager   \n",
       "154320      Elsa   Orilla             Engineering          Drill Technician   \n",
       "154321      Elsa   Orilla             Engineering          Drill Technician   \n",
       "154322      Elsa   Orilla             Engineering          Drill Technician   \n",
       "225301    Hennie  Osvaldo                Security         Perimeter Control   \n",
       "330356      Isia     Vann                Security         Perimeter Control   \n",
       "464669     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "464670     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "464671     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "464672     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "464673     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "477568     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "477569     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "477570     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "477571     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "477572     Lucas  Alcazar  Information Technology               IT Helpdesk   \n",
       "\n",
       "                 Timestamp    id        lat       long   day  hour  minute  \\\n",
       "66601  2014-01-12 00:00:00  29.0  36.059926  24.893272  12.0   0.0     0.0   \n",
       "154320 2014-01-19 00:00:00  28.0  36.068748  24.882666  19.0   0.0     0.0   \n",
       "154321 2014-01-19 00:01:00  28.0  36.071066  24.879613  19.0   0.0     1.0   \n",
       "154322 2014-01-19 00:02:00  28.0  36.072861  24.876743  19.0   0.0     2.0   \n",
       "225301 2014-01-14 03:43:00  21.0  36.060828  24.904150  14.0   3.0    43.0   \n",
       "330356 2014-01-07 01:10:00  16.0  36.076832  24.865878   7.0   1.0    10.0   \n",
       "464669 2014-01-07 01:10:00   1.0  36.050386  24.879576   7.0   1.0    10.0   \n",
       "464670 2014-01-07 01:11:00   1.0  36.053128  24.882471   7.0   1.0    11.0   \n",
       "464671 2014-01-07 01:12:00   1.0  36.058610  24.882478   7.0   1.0    12.0   \n",
       "464672 2014-01-07 01:13:00   1.0  36.063921  24.882584   7.0   1.0    13.0   \n",
       "464673 2014-01-07 01:14:00   1.0  36.066439  24.882594   7.0   1.0    14.0   \n",
       "477568 2014-01-16 00:09:00   1.0  36.050603  24.879577  16.0   0.0     9.0   \n",
       "477569 2014-01-16 00:10:00   1.0  36.053303  24.882473  16.0   0.0    10.0   \n",
       "477570 2014-01-16 00:11:00   1.0  36.058443  24.882485  16.0   0.0    11.0   \n",
       "477571 2014-01-16 00:12:00   1.0  36.063360  24.882597  16.0   0.0    12.0   \n",
       "477572 2014-01-16 00:13:00   1.0  36.066387  24.882620  16.0   0.0    13.0   \n",
       "\n",
       "        Weekend  \n",
       "66601      True  \n",
       "154320     True  \n",
       "154321     True  \n",
       "154322     True  \n",
       "225301    False  \n",
       "330356    False  \n",
       "464669    False  \n",
       "464670    False  \n",
       "464671    False  \n",
       "464672    False  \n",
       "464673    False  \n",
       "477568    False  \n",
       "477569    False  \n",
       "477570    False  \n",
       "477571    False  \n",
       "477572    False  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Model Pipeline\n",
    "locLocalpipe = Pipeline(\n",
    "    [\n",
    "        ('preprocessor', locPreprocessor),\n",
    "        ('model', LocalOutlierFactor(n_jobs = -1))\n",
    "    ]\n",
    ")\n",
    "# Find Outliers\n",
    "findOutliers(locLocalpipe, locations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Awesome, our model gave us a start with 5 suspects to look at. Lucas Alcazar also had two different times pointed out."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Purchases"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a preprocessing pipeline. We need to drop the timestamp column as we already have the datetime parts seperated into their own variable. We can also drop the CarID variable as there is a one to one relationship with the CarID. Lets also drop the minute and seconda columns. With a chunk of the purchases not haveing this because they were batch reported it could alter results. We will need to encode the names, locations,  job title and type variables."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "Buypreprocessor = ColumnTransformer(\n",
    "    [\n",
    "        ( 'dropper', 'drop', ['timestamp',  'CarID', 'minute', 'second'] ),\n",
    "        ('encoder', OneHotEncoder(), ['location', 'LastName', 'FirstName', 'CurrentEmploymentType', 'CurrentEmploymentTitle'])\n",
    "    ],\n",
    "    remainder='passthrough'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar to above we will use two algorithms that are implmented in scikit-learn; IsolationForest and LocalOutlierFactor. First lets look at IsolationForest."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No Outliers Detected. All points belong to same cluster.\n"
     ]
    }
   ],
   "source": [
    "# Model Pipeline\n",
    "BuyIso = Pipeline(\n",
    "    [\n",
    "        ('preprocessor', Buypreprocessor),\n",
    "        ('model', IsolationForest())\n",
    "    ]\n",
    ")\n",
    "# Find Outliers\n",
    "findOutliers(BuyIso, buys)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mhmmm, once again no outliers for this algorithm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>timestamp</th>\n",
       "      <th>location</th>\n",
       "      <th>price</th>\n",
       "      <th>FirstName</th>\n",
       "      <th>LastName</th>\n",
       "      <th>Is_Loyalty</th>\n",
       "      <th>day</th>\n",
       "      <th>hour</th>\n",
       "      <th>minute</th>\n",
       "      <th>second</th>\n",
       "      <th>Weekend</th>\n",
       "      <th>CarID</th>\n",
       "      <th>CurrentEmploymentType</th>\n",
       "      <th>CurrentEmploymentTitle</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2014-01-06 15:39:00</td>\n",
       "      <td>Abila Airport</td>\n",
       "      <td>612.47</td>\n",
       "      <td>Henk</td>\n",
       "      <td>Mies</td>\n",
       "      <td>True</td>\n",
       "      <td>6</td>\n",
       "      <td>15</td>\n",
       "      <td>39</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Facilities</td>\n",
       "      <td>Truck Driver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>414</th>\n",
       "      <td>2014-01-09 09:54:00</td>\n",
       "      <td>Carlyle Chemical Inc.</td>\n",
       "      <td>529.47</td>\n",
       "      <td>Valeria</td>\n",
       "      <td>Morlun</td>\n",
       "      <td>True</td>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>54</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Facilities</td>\n",
       "      <td>Truck Driver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>2014-01-09 14:26:00</td>\n",
       "      <td>Carlyle Chemical Inc.</td>\n",
       "      <td>382.43</td>\n",
       "      <td>Valeria</td>\n",
       "      <td>Morlun</td>\n",
       "      <td>True</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Facilities</td>\n",
       "      <td>Truck Driver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>480</th>\n",
       "      <td>2014-01-09 14:28:00</td>\n",
       "      <td>Kronos Pipe and Irrigation</td>\n",
       "      <td>423.14</td>\n",
       "      <td>Irene</td>\n",
       "      <td>Nant</td>\n",
       "      <td>True</td>\n",
       "      <td>9</td>\n",
       "      <td>14</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Facilities</td>\n",
       "      <td>Truck Driver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>842</th>\n",
       "      <td>2014-01-13 19:20:00</td>\n",
       "      <td>Frydos Autosupply n' More</td>\n",
       "      <td>10000.00</td>\n",
       "      <td>Lucas</td>\n",
       "      <td>Alcazar</td>\n",
       "      <td>False</td>\n",
       "      <td>13</td>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Helpdesk</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>898</th>\n",
       "      <td>2014-01-14 08:12:00</td>\n",
       "      <td>Hallowed Grounds</td>\n",
       "      <td>39.52</td>\n",
       "      <td>Kare</td>\n",
       "      <td>Orilla</td>\n",
       "      <td>False</td>\n",
       "      <td>14</td>\n",
       "      <td>8</td>\n",
       "      <td>12</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>27.0</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Drill Technician</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>906</th>\n",
       "      <td>2014-01-14 11:01:00</td>\n",
       "      <td>Stewart and Sons Fabrication</td>\n",
       "      <td>540.19</td>\n",
       "      <td>Benito</td>\n",
       "      <td>Hawelon</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Facilities</td>\n",
       "      <td>Truck Driver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>907</th>\n",
       "      <td>2014-01-14 11:45:00</td>\n",
       "      <td>Nationwide Refinery</td>\n",
       "      <td>570.95</td>\n",
       "      <td>Valeria</td>\n",
       "      <td>Morlun</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>11</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Facilities</td>\n",
       "      <td>Truck Driver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1158</th>\n",
       "      <td>2014-01-16 09:52:00</td>\n",
       "      <td>Carlyle Chemical Inc.</td>\n",
       "      <td>419.93</td>\n",
       "      <td>Valeria</td>\n",
       "      <td>Morlun</td>\n",
       "      <td>True</td>\n",
       "      <td>16</td>\n",
       "      <td>9</td>\n",
       "      <td>52</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Facilities</td>\n",
       "      <td>Truck Driver</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1372</th>\n",
       "      <td>2014-01-18 12:03:00</td>\n",
       "      <td>Chostus Hotel</td>\n",
       "      <td>600.00</td>\n",
       "      <td>Sten</td>\n",
       "      <td>Sanjorge Jr.</td>\n",
       "      <td>True</td>\n",
       "      <td>18</td>\n",
       "      <td>12</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>31.0</td>\n",
       "      <td>Executive</td>\n",
       "      <td>President/CEO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1493</th>\n",
       "      <td>2014-01-09 00:00:00</td>\n",
       "      <td>Coffee Cameleon</td>\n",
       "      <td>4.88</td>\n",
       "      <td>Carla</td>\n",
       "      <td>Forluniau</td>\n",
       "      <td>True</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Other</td>\n",
       "      <td>Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1508</th>\n",
       "      <td>2014-01-06 00:00:00</td>\n",
       "      <td>Brew've Been Served</td>\n",
       "      <td>10.68</td>\n",
       "      <td>Isia</td>\n",
       "      <td>Vann</td>\n",
       "      <td>True</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>16.0</td>\n",
       "      <td>Security</td>\n",
       "      <td>Perimeter Control</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1526</th>\n",
       "      <td>2014-01-09 00:00:00</td>\n",
       "      <td>Bean There Done That</td>\n",
       "      <td>4.05</td>\n",
       "      <td>Vira</td>\n",
       "      <td>Frente</td>\n",
       "      <td>True</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>Hydraulic Technician</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1572</th>\n",
       "      <td>2014-01-16 00:00:00</td>\n",
       "      <td>Coffee Cameleon</td>\n",
       "      <td>5.20</td>\n",
       "      <td>Linnea</td>\n",
       "      <td>Bergen</td>\n",
       "      <td>True</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>IT Group Manager</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               timestamp                      location     price FirstName  \\\n",
       "92   2014-01-06 15:39:00                 Abila Airport    612.47      Henk   \n",
       "414  2014-01-09 09:54:00         Carlyle Chemical Inc.    529.47   Valeria   \n",
       "479  2014-01-09 14:26:00         Carlyle Chemical Inc.    382.43   Valeria   \n",
       "480  2014-01-09 14:28:00    Kronos Pipe and Irrigation    423.14     Irene   \n",
       "842  2014-01-13 19:20:00     Frydos Autosupply n' More  10000.00     Lucas   \n",
       "898  2014-01-14 08:12:00              Hallowed Grounds     39.52      Kare   \n",
       "906  2014-01-14 11:01:00  Stewart and Sons Fabrication    540.19    Benito   \n",
       "907  2014-01-14 11:45:00           Nationwide Refinery    570.95   Valeria   \n",
       "1158 2014-01-16 09:52:00         Carlyle Chemical Inc.    419.93   Valeria   \n",
       "1372 2014-01-18 12:03:00                 Chostus Hotel    600.00      Sten   \n",
       "1493 2014-01-09 00:00:00               Coffee Cameleon      4.88     Carla   \n",
       "1508 2014-01-06 00:00:00           Brew've Been Served     10.68      Isia   \n",
       "1526 2014-01-09 00:00:00          Bean There Done That      4.05      Vira   \n",
       "1572 2014-01-16 00:00:00               Coffee Cameleon      5.20    Linnea   \n",
       "\n",
       "          LastName  Is_Loyalty  day  hour  minute  second  Weekend  CarID  \\\n",
       "92            Mies        True    6    15      39       0    False  100.0   \n",
       "414         Morlun        True    9     9      54       0    False  100.0   \n",
       "479         Morlun        True    9    14      26       0    False  100.0   \n",
       "480           Nant        True    9    14      28       0    False  100.0   \n",
       "842        Alcazar       False   13    19      20       0    False    1.0   \n",
       "898         Orilla       False   14     8      12       0    False   27.0   \n",
       "906        Hawelon        True   14    11       1       0    False  100.0   \n",
       "907         Morlun        True   14    11      45       0    False  100.0   \n",
       "1158        Morlun        True   16     9      52       0    False  100.0   \n",
       "1372  Sanjorge Jr.        True   18    12       3       0     True   31.0   \n",
       "1493     Forluniau        True    9     0       0       0    False    0.0   \n",
       "1508          Vann        True    6     0       0       0    False   16.0   \n",
       "1526        Frente        True    9     0       0       0    False   19.0   \n",
       "1572        Bergen        True   16     0       0       0    False    6.0   \n",
       "\n",
       "       CurrentEmploymentType CurrentEmploymentTitle  \n",
       "92                Facilities           Truck Driver  \n",
       "414               Facilities           Truck Driver  \n",
       "479               Facilities           Truck Driver  \n",
       "480               Facilities           Truck Driver  \n",
       "842   Information Technology            IT Helpdesk  \n",
       "898              Engineering       Drill Technician  \n",
       "906               Facilities           Truck Driver  \n",
       "907               Facilities           Truck Driver  \n",
       "1158              Facilities           Truck Driver  \n",
       "1372               Executive          President/CEO  \n",
       "1493                   Other                  Other  \n",
       "1508                Security      Perimeter Control  \n",
       "1526             Engineering   Hydraulic Technician  \n",
       "1572  Information Technology       IT Group Manager  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Model Pipeline\n",
    "BuyLocal = Pipeline(\n",
    "    [\n",
    "        ('preprocessor', Buypreprocessor),\n",
    "        ('model', LocalOutlierFactor(n_jobs = -1))\n",
    "    ]\n",
    ")\n",
    "# Find Outliers\n",
    "findOutliers(BuyLocal, buys)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Thats a decent list we can go through."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Save our two models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['../models/PurchaseLocalOutlierFactor.sav']"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "locLocalpipe.fit(locations)\n",
    "joblib.dump(locLocalpipe, '../models/LocationLocalOutlierFactor.sav')\n",
    "BuyLocal.fit(buys)\n",
    "joblib.dump(BuyLocal, '../models/PurchaseLocalOutlierFactor.sav')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div>\n",
    "    <span  style=\"width:600px;display:inline-block;text-align:left\">\n",
    "        <a href=\"./CleanUp.ipynb\">&#60;&#60;Data Cleanup</a>\n",
    "    </span>\n",
    "    <span style=\"width:600px;display:inline-block;text-align:right\">\n",
    "        <a href=\"./ObservationsQ1.ipynb\">Observations Question 1&#62;&#62;</a>\n",
    "    </span>\n",
    "</div>\n",
    "<div>\n",
    "    <center>\n",
    "        <span style=\"width:200px;display:inline-block;text-align:center\">\n",
    "            <a href=\"./Master.ipynb\">Master Notebook</a>\n",
    "        </span>\n",
    "        <span style=\"width:200px;display:inline-block;text-align:center\">\n",
    "            <a href=\"../README.md\">Table of Contents</a>\n",
    "        </span>\n",
    "    </center>\n",
    "</div>"
   ]
  }
 ],
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