{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5f785227",
   "metadata": {},
   "source": [
    "# Demo Notebook for the vivainsights Python package\n",
    "\n",
    "This notebook provides a demo for the **vivainsights** package. For more information about the package, please see:\n",
    "- [Documentation](https://microsoft.github.io/vivainsights-py/)\n",
    "- [GitHub Page](https://github.com/microsoft/vivainsights-py/)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90e53e1a",
   "metadata": {},
   "source": [
    "### Loading the library and dataset\n",
    "\n",
    "The following code loads the library 'vivainsights', and the function `load_pq_data()` loads a sample Person Query data to the environment. The first five rows of the data looks like the following: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "da67d55b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import vivainsights as vi\n",
    "\n",
    "# load in-built datasets\n",
    "pq_data = vi.load_pq_data() # load and assign in-built person query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7659175c",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "247ab3d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<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>Unnamed: 0</th>\n",
       "      <th>PersonId</th>\n",
       "      <th>MetricDate</th>\n",
       "      <th>After_hours_call_hours</th>\n",
       "      <th>After_hours_chat_hours</th>\n",
       "      <th>After_hours_collaboration_hours</th>\n",
       "      <th>After_hours_email_hours</th>\n",
       "      <th>After_hours_meeting_hours</th>\n",
       "      <th>After_hours_scheduled_call_hours</th>\n",
       "      <th>After_hours_unscheduled_call_hours</th>\n",
       "      <th>...</th>\n",
       "      <th>Working_hours_meeting_hours</th>\n",
       "      <th>Working_hours_scheduled_call_hours</th>\n",
       "      <th>Working_hours_unscheduled_call_hours</th>\n",
       "      <th>LevelDesignation</th>\n",
       "      <th>Layer</th>\n",
       "      <th>SupervisorIndicator</th>\n",
       "      <th>Organization</th>\n",
       "      <th>FunctionType</th>\n",
       "      <th>WeekendDays</th>\n",
       "      <th>IsActive</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>a6afe34c-8524-32d3-a368-1517b29b68cd</td>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.675938</td>\n",
       "      <td>0.722722</td>\n",
       "      <td>18.25</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>19.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Manager</td>\n",
       "      <td>3</td>\n",
       "      <td>Manager</td>\n",
       "      <td>Sales and Marketing</td>\n",
       "      <td>G_and_A</td>\n",
       "      <td>[SUNDAY, SATURDAY]</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>d6368140-9312-380b-bbc9-9a32bcef4b83</td>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.827803</td>\n",
       "      <td>0.925556</td>\n",
       "      <td>4.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>8.75</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Support</td>\n",
       "      <td>3</td>\n",
       "      <td>Individual Contributor</td>\n",
       "      <td>Finance</td>\n",
       "      <td>Sales</td>\n",
       "      <td>[SUNDAY, SATURDAY]</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60bf99b0-65fd-3c3f-94fb-8ceb451d59e7</td>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.497806</td>\n",
       "      <td>0.812806</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>12.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Support</td>\n",
       "      <td>3</td>\n",
       "      <td>Individual Contributor</td>\n",
       "      <td>Product</td>\n",
       "      <td>IT</td>\n",
       "      <td>[SUNDAY, SATURDAY]</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>93fddd74-3667-392b-ba5a-92d855772cb0</td>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>59.265892</td>\n",
       "      <td>2.283668</td>\n",
       "      <td>59.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>28.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Director</td>\n",
       "      <td>2</td>\n",
       "      <td>Manager+</td>\n",
       "      <td>Sales and Marketing</td>\n",
       "      <td>Analytics</td>\n",
       "      <td>[SUNDAY, SATURDAY]</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>53183116-2cb2-32ee-9042-d62eb7061407</td>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.146806</td>\n",
       "      <td>0.520167</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>...</td>\n",
       "      <td>7.50</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Support</td>\n",
       "      <td>3</td>\n",
       "      <td>Individual Contributor</td>\n",
       "      <td>Sales and Marketing</td>\n",
       "      <td>IT</td>\n",
       "      <td>[SUNDAY, SATURDAY]</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 155 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0                              PersonId  MetricDate   \n",
       "0           1  a6afe34c-8524-32d3-a368-1517b29b68cd  2022-05-01  \\\n",
       "1           2  d6368140-9312-380b-bbc9-9a32bcef4b83  2022-05-01   \n",
       "2           3  60bf99b0-65fd-3c3f-94fb-8ceb451d59e7  2022-05-01   \n",
       "3           4  93fddd74-3667-392b-ba5a-92d855772cb0  2022-05-01   \n",
       "4           5  53183116-2cb2-32ee-9042-d62eb7061407  2022-05-01   \n",
       "\n",
       "   After_hours_call_hours  After_hours_chat_hours   \n",
       "0                     0.0                     0.0  \\\n",
       "1                     0.0                     0.0   \n",
       "2                     0.0                     0.0   \n",
       "3                     0.0                     0.0   \n",
       "4                     0.0                     0.0   \n",
       "\n",
       "   After_hours_collaboration_hours  After_hours_email_hours   \n",
       "0                        18.675938                 0.722722  \\\n",
       "1                         4.827803                 0.925556   \n",
       "2                         1.497806                 0.812806   \n",
       "3                        59.265892                 2.283668   \n",
       "4                         2.146806                 0.520167   \n",
       "\n",
       "   After_hours_meeting_hours  After_hours_scheduled_call_hours   \n",
       "0                      18.25                               0.0  \\\n",
       "1                       4.00                               0.0   \n",
       "2                       0.75                               0.0   \n",
       "3                      59.00                               0.0   \n",
       "4                       1.75                               0.0   \n",
       "\n",
       "   After_hours_unscheduled_call_hours  ...  Working_hours_meeting_hours   \n",
       "0                                   0  ...                        19.50  \\\n",
       "1                                   0  ...                         8.75   \n",
       "2                                   0  ...                        12.50   \n",
       "3                                   0  ...                        28.50   \n",
       "4                                   0  ...                         7.50   \n",
       "\n",
       "   Working_hours_scheduled_call_hours  Working_hours_unscheduled_call_hours   \n",
       "0                                   0                                     0  \\\n",
       "1                                   0                                     0   \n",
       "2                                   0                                     0   \n",
       "3                                   0                                     0   \n",
       "4                                   0                                     0   \n",
       "\n",
       "   LevelDesignation  Layer     SupervisorIndicator         Organization   \n",
       "0           Manager      3                 Manager  Sales and Marketing  \\\n",
       "1           Support      3  Individual Contributor              Finance   \n",
       "2           Support      3  Individual Contributor              Product   \n",
       "3          Director      2                Manager+  Sales and Marketing   \n",
       "4           Support      3  Individual Contributor  Sales and Marketing   \n",
       "\n",
       "   FunctionType         WeekendDays  IsActive  \n",
       "0       G_and_A  [SUNDAY, SATURDAY]      True  \n",
       "1         Sales  [SUNDAY, SATURDAY]      True  \n",
       "2            IT  [SUNDAY, SATURDAY]      True  \n",
       "3     Analytics  [SUNDAY, SATURDAY]      True  \n",
       "4            IT  [SUNDAY, SATURDAY]      True  \n",
       "\n",
       "[5 rows x 155 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pq_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "caf67b86",
   "metadata": {},
   "source": [
    "### Run visuals\n",
    "\n",
    "There are currently several visuals that you can run with the Person Query dataset. The first of these that you can run is a bar plot, which produces a person-average (first averaging by person, then averaging by group) for the groups in question. The parameters that you can provide to `create_bar()` are:\n",
    "\n",
    "- `metric` - metric to analyze\n",
    "- `hrvar` - grouping HR variable\n",
    "- `mingroup` - minimum group size to display\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f64fb0fe",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_bar = vi.create_bar(data=pq_data, metric='Emails_sent', hrvar='Organization', mingroup=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a738776",
   "metadata": {},
   "source": [
    "You can also ask the function to return a summary table by specifying the parameter `return_type`. This summary table can be copied to a clipboard with `export()`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "60dae622",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "          Organization     metric   n\n",
      "0              Finance  46.566667  27\n",
      "3  Sales and Marketing  45.625806  31\n",
      "1                   HR  38.971429  21\n",
      "2              Product  35.433333  21\n"
     ]
    }
   ],
   "source": [
    "tb = vi.create_bar(data=pq_data, metric='Emails_sent', hrvar='Organization', mingroup=5, return_type='table')\n",
    "print(tb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ba37d24b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data frame copied to clipboard.\n",
      "You may paste the contents directly to Excel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "()"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vi.export(tb)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f5d5fa5",
   "metadata": {},
   "source": [
    "Here are some other visual outputs, and their accompanying summary table outputs:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a511e696",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_line = vi.create_line(data=pq_data, metric='Emails_sent', hrvar='Organization', mingroup=5, return_type='plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "963db182",
   "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>MetricDate</th>\n",
       "      <th>Organization</th>\n",
       "      <th>metric</th>\n",
       "      <th>n</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>Finance</td>\n",
       "      <td>52.370370</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>HR</td>\n",
       "      <td>43.238095</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>Product</td>\n",
       "      <td>38.428571</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>Sales and Marketing</td>\n",
       "      <td>49.193548</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2022-05-08</td>\n",
       "      <td>Finance</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MetricDate         Organization     metric   n\n",
       "0  2022-05-01              Finance  52.370370  27\n",
       "1  2022-05-01                   HR  43.238095  21\n",
       "2  2022-05-01              Product  38.428571  21\n",
       "3  2022-05-01  Sales and Marketing  49.193548  31\n",
       "4  2022-05-08              Finance  50.000000  27"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vi.create_line(data=pq_data, metric='Emails_sent', hrvar='Organization', mingroup=5, return_type='table').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "437e069a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_box = vi.create_boxplot(data=pq_data, metric='Emails_sent', hrvar='Organization', mingroup=5, return_type='plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c8aaa5a1",
   "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>index</th>\n",
       "      <th>group</th>\n",
       "      <th>mean</th>\n",
       "      <th>median</th>\n",
       "      <th>sd</th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>n</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Finance</td>\n",
       "      <td>46.566667</td>\n",
       "      <td>39.6</td>\n",
       "      <td>21.739330</td>\n",
       "      <td>28.5</td>\n",
       "      <td>134.5</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>HR</td>\n",
       "      <td>38.971429</td>\n",
       "      <td>36.0</td>\n",
       "      <td>16.793366</td>\n",
       "      <td>22.1</td>\n",
       "      <td>98.9</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Product</td>\n",
       "      <td>35.433333</td>\n",
       "      <td>33.4</td>\n",
       "      <td>6.608505</td>\n",
       "      <td>29.6</td>\n",
       "      <td>59.5</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Sales and Marketing</td>\n",
       "      <td>45.625806</td>\n",
       "      <td>38.4</td>\n",
       "      <td>20.387577</td>\n",
       "      <td>24.4</td>\n",
       "      <td>119.0</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index                group       mean  median         sd   min    max   n\n",
       "0      0              Finance  46.566667    39.6  21.739330  28.5  134.5  27\n",
       "1      1                   HR  38.971429    36.0  16.793366  22.1   98.9  21\n",
       "2      2              Product  35.433333    33.4   6.608505  29.6   59.5  21\n",
       "3      3  Sales and Marketing  45.625806    38.4  20.387577  24.4  119.0  31"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vi.create_boxplot(data=pq_data, metric='Emails_sent', hrvar='Organization', mingroup=5, return_type='table')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "851fcbf8",
   "metadata": {},
   "source": [
    "## Exploratory data analysis\n",
    "\n",
    "Some functions are designed to perform a rapid exploratory analysis of the dataset, and one of these functions is `create_rank()`. With `create_rank()`, you can explore all the groupings within your population and rank them with respect to a metric you choose. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "93519176",
   "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>hrvar</th>\n",
       "      <th>attributes</th>\n",
       "      <th>metric</th>\n",
       "      <th>n</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SupervisorIndicator</td>\n",
       "      <td>Manager+</td>\n",
       "      <td>72.043614</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>LevelDesignation</td>\n",
       "      <td>Director</td>\n",
       "      <td>72.043614</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>FunctionType</td>\n",
       "      <td>Marketing</td>\n",
       "      <td>28.992283</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SupervisorIndicator</td>\n",
       "      <td>Manager</td>\n",
       "      <td>26.884630</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>LevelDesignation</td>\n",
       "      <td>Manager</td>\n",
       "      <td>26.884630</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Organization</td>\n",
       "      <td>Sales and Marketing</td>\n",
       "      <td>25.765574</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>LevelDesignation</td>\n",
       "      <td>Junior IC</td>\n",
       "      <td>21.447389</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>FunctionType</td>\n",
       "      <td>Sales</td>\n",
       "      <td>21.294210</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>FunctionType</td>\n",
       "      <td>Engineering</td>\n",
       "      <td>19.436244</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>FunctionType</td>\n",
       "      <td>Analytics</td>\n",
       "      <td>18.348926</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Organization</td>\n",
       "      <td>HR</td>\n",
       "      <td>17.775103</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FunctionType</td>\n",
       "      <td>IT</td>\n",
       "      <td>17.698799</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>FunctionType</td>\n",
       "      <td>G_and_A</td>\n",
       "      <td>17.478766</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Organization</td>\n",
       "      <td>Finance</td>\n",
       "      <td>16.694477</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>FunctionType</td>\n",
       "      <td>Customer_Service</td>\n",
       "      <td>15.080618</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SupervisorIndicator</td>\n",
       "      <td>Individual Contributor</td>\n",
       "      <td>13.752266</td>\n",
       "      <td>83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>LevelDesignation</td>\n",
       "      <td>Support</td>\n",
       "      <td>12.937993</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>FunctionType</td>\n",
       "      <td>R_and_D</td>\n",
       "      <td>12.365513</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>LevelDesignation</td>\n",
       "      <td>Senior IC</td>\n",
       "      <td>12.062528</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Organization</td>\n",
       "      <td>Product</td>\n",
       "      <td>11.746185</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 hrvar              attributes     metric   n\n",
       "2  SupervisorIndicator                Manager+  72.043614   6\n",
       "0     LevelDesignation                Director  72.043614   6\n",
       "5         FunctionType               Marketing  28.992283  12\n",
       "1  SupervisorIndicator                 Manager  26.884630  11\n",
       "2     LevelDesignation                 Manager  26.884630  11\n",
       "3         Organization     Sales and Marketing  25.765574  31\n",
       "1     LevelDesignation               Junior IC  21.447389  10\n",
       "7         FunctionType                   Sales  21.294210  11\n",
       "2         FunctionType             Engineering  19.436244  20\n",
       "0         FunctionType               Analytics  18.348926  12\n",
       "1         Organization                      HR  17.775103  21\n",
       "4         FunctionType                      IT  17.698799  11\n",
       "3         FunctionType                 G_and_A  17.478766   6\n",
       "0         Organization                 Finance  16.694477  27\n",
       "1         FunctionType        Customer_Service  15.080618  12\n",
       "0  SupervisorIndicator  Individual Contributor  13.752266  83\n",
       "4     LevelDesignation                 Support  12.937993  53\n",
       "6         FunctionType                 R_and_D  12.365513  16\n",
       "3     LevelDesignation               Senior IC  12.062528  20\n",
       "2         Organization                 Product  11.746185  21"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vi.create_rank(\n",
    "    data=pq_data,\n",
    "    metric='Collaboration_hours',\n",
    "    hrvar = ['Organization', 'FunctionType', 'LevelDesignation', 'SupervisorIndicator'],\n",
    "    mingroup=5,\n",
    "    return_type = 'table'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef4c4ce1",
   "metadata": {},
   "source": [
    "This can be visualized as well:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4a50f940",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_rank = vi.create_rank(\n",
    "    data=pq_data,\n",
    "    metric='Collaboration_hours',\n",
    "    hrvar = ['Organization', 'FunctionType', 'LevelDesignation', 'SupervisorIndicator'],\n",
    "    mingroup=5,\n",
    "    return_type = 'plot'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a04c0e5f",
   "metadata": {},
   "source": [
    "### Validating / exploring the data\n",
    "\n",
    "Since HR variables or organizational attributes are a key part of the analysis process, it is also possible to perform some exploration or validation before we begin the analysis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4d0a85e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KFTp+/LhycnI0ZMgQ9e/fXzVr1rTf5+HEiROScl+1jhgx4rK/Fw8PD/3zn//U0qVLJUkzZsxQiRIlVKZMGc2bN6/A6x0u/OuE/fv3a9GiRbr55pu1ePHia36OPu/nmJWVJSn3Wpvy5cu7BFzlypUVFBSkm2++2Q7XWbNm6f7779fvv/+uWbNmFbp9p9NpH+X59ttv5eHhIU9PT9WoUUO+vr4F3icgIEBt27a1f88nTZqk1NRUBQYGav78+Tp//ryk3Phu1arVFe8DALjarmk8SLkX1O3atUtbt27VmTNnLnndg5R7kWTPnj31xRdfyLIszZ8/X/Pnz3dZ54EHHijwIjIp9+jBlClT8t1+//33/+WRkqCgII0dO1Yvv/yyMjIytHbtWpdgyZP3/hWXKyQkRHv37tVzzz3ncruvr6+ef/75fOv36NHDjqk8l3PKIk9gYKCmTJmi5557TocPH1ZCQkKB+71UqVKKiIhQw4YNL3vbkjRkyBD99NNPOnnypFJSUjR+/HhJuddNXHjKJE+dOnXUsGFDbd++XVlZWZo0aZKk3AtR69atW+iplath06ZN9pOxJC1fvlzLly93WSfvfR4efvhh+3tZtWqVVq1aJUn2+0UU5B//+Ic9/3fffafvvvtOUu4pvUv9vo0cOVJ//PGHYmNjderUqXxv++7j46Nx48bl+0sLACgKrnk8lCxZUtOnT9fSpUu1cuVK7d+/3/5Ts9DQUDVu3Djfk/GLL76oZs2aafHixdq9e7dSUlLk6+trv0lUYeEgSSNGjND+/fv15Zdf6tixYypbtqweeOABPf7445c1b7t27RQZGanIyEht2bJFx48fl6enp8qUKaOqVavqzjvvNI6HihUr6vnnn9fUqVMVHR0ty7LUuHFjDR8+vMD3bGjevLkqVaqkw4cPS8o9rVClShWjx6xevbo+//xzLVu2TGvXrtWBAweUkpIiHx8fVapUSS1atFCPHj3y/Xnm5QgODtasWbPsN4mSci+cHDFihF555RV7vbwnPg8PD73zzjuaPHmyfvzxR6Wnp6tevXoaPny4vvjii2saDya6d+8uy7L0+eefKy4uTuXKlVOPHj1Uo0aNQuNhwIABSkpK0rp165SQkHDZ1xwEBwdr3rx59ptExcbGKjs7W2XLllXTpk31+OOP886UAIosh3UDXGFV0DsLFneTJ0/WvHnzJOW+EVJR+9t9y7LyXRNx5swZdenSxX6lHxkZme8NqgAAxd81P/KAy5eTk6Nz584pLi5Oq1evlpR7aqFTp05uniy/wYMHq2PHjqpXr56cTqcOHTqk6dOn2+FQs2bNAv+CAwBQ/BEPRchvv/2W7/+HYcCAAUXy7Yb//PNP+/qAiwUFBen111//23+2CwAo2oiHIsjDw0PlypXTgw8+6PKnqkXJQw89pJ9++klHjhxRSkqKSpYsqcqVK6tVq1Z6+OGHXd4UCwBwY7khrnkAAADXz+W9cQAAAMD/j3gAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIB6AAmZmZGjp0qEqXLq2goCANGzZMWVlZ7h7rsvTr10/e3t7y8/OzP/773/+6e6xCTZ06VXfccYdKliypbt26uSxLTk7WI488ooCAAIWGhur11193z5CFuNTsYWFhKlmypMvPIS4uzj2DFuD8+fMaOHCgqlWrJn9/f9WuXVuzZ8+2lxf1ff9X8xf1/S9Jw4YNU6VKlRQQEKCbb75ZI0aMUEZGhqSiv/+JB6AA48aN08aNG7V7927t2rVLP/zwg8aPH+/usS7bkCFDlJqaan+0aNHC3SMVqkKFCho9erQGDhyYb9mwYcN05swZxcbG6ocfftDHH3+suXPnumHKgl1qdkmaNGmSy8+hQoUK13nCwmVlZal8+fL6/vvvlZycrDlz5ui5557TqlWrJBX9ff9X80tFe/9Luf9O9+zZo+TkZG3btk3btm3Tm2++Kano73/iASjA7NmzNXr0aJUvX17ly5fXyy+/rFmzZrl7rBtS9+7d1a1bN5UpU8bl9rS0NC1YsEDjxo2T0+lUzZo1NWzYsCL1cyhs9uLA19dXr732mm655RY5HA41b95c7dq108aNG4vFvr/U/MVFnTp15OvrK0myLEseHh7av39/sdj/xANwkYSEBB05ckS33Xabfdttt92m2NhYJSUluW8wA3PnzlVQUJDq1aunt99+Wzk5Oe4eydjevXuVkZGR7+ewfft29w1laNy4cQoKClLjxo2L1KvGgpw7d04///yzGjZsWCz3/YXz5ykO+3/ixIny8/NTSEiItm3bpmHDhhWL/U88ABdJTU2VJDmdTvu2vM9TUlLcMJGZ4cOHa+/evTp58qRmzZqlyZMna/Lkye4ey1hqaqp8fX3l5eVl3+Z0OovFz0CSJkyYoD/++EPHjx/XxIkTNWzYMC1ZssTdYxXIsiw9+eSTqlGjhrp3717s9v3F80vFZ/+PHDlSqamp2r17t55++mmVK1euWOx/4gG4iJ+fnyS5HGXI+9zf398tM5m4/fbbVbZsWXl6eqp58+YaOXKkFi5c6O6xjPn5+SktLc3lQtWkpKRi8TOQpBYtWigwMFAlSpTQ3XffrUGDBhXJn4NlWRoyZIj27t2rr7/+Wh4eHsVq3xc0v1R89n+eOnXqqFGjRurXr1+x2P/EA3CR0qVLq2LFioqOjrZvi46OVqVKlRQYGOi+wf6mvP+YFje1atVSiRIltG3bNvu26OhoNWjQwI1T/X1F8edgWZbCw8O1efNmrVq1yv79Li77vrD5C1IU9//FMjMztX///mKx/4v+3gTcoH///nrjjTcUHx+v+Ph4jR8/Xk8++aS7x7osX3zxhZKTk2VZln755RdNnDhRDz74oLvHKlRWVpbOnTunrKws5eTk6Ny5c8rIyFCpUqXUq1cvvfLKK0pKStL+/fs1ZcqUIvVzKGz2xMRELV++XGlpacrOztaaNWs0Y8aMIvdzGDp0qH788UetXr1apUuXtm8vDvteKnz+4rD/U1NT9cknnygxMVGWZWnHjh0aN26c7r777uKx/y0A+WRkZFhDhgyxnE6n5XQ6raFDh1qZmZnuHuuy3HnnnVZgYKDl6+tr1axZ05o0aZKVnZ3t7rEK9eqrr1qSXD7atm1rWZZlJSUlWb1797b8/PyssmXLWmPHjnXvsBcpbPYTJ05YzZo1s/z9/S1/f3+rQYMG1qxZs9w9rouYmBhLklWyZEnL19fX/hg0aJBlWUV/319q/uKw/1NTU6277rrLCgoKsnx9fa1q1apZzz//vHX27FnLsor+/ndYlmW5K1wAAEDxw2kLAABghHgAAABGiAcAAGCEeAAAAEaIB6AQgwcP1uDBg909BgAUOcQDUIgdO3Zo3Q8/KrOY/F9xXywzK0tfrd5QLOcvzrNLxXv+4jy7xPzXC/EAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjDgsy7LcPQRQFLVu3Vpb9scq9L7+7h4FKJJiZ4119wj5ZGZlaVnUT+rarqVKeHm5exxjxWV+jjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwDgqpkwYYKaNm0qf39/hYSEqFu3btq7d6/LOh999JHCwsIUEBAgh8OhxMRE9wyLv414gFuMGDFC/fr1c/cYAK6y9evXKzw8XJs2bdLq1auVmZmpjh076uzZs/Y6aWlp6tSpk0aNGuXGSXElvNw9AIqusLAw/fe//1WJEiXk7e2thg0b6u2331aTJk3cPZpt3bp16tatG69cgCJi5cqVLl/PmTNHISEh2rp1q9q0aSMp98WDlPvvF8UTRx5wSZMmTVJqaqri4uLUuHFj3X///fnWyczMdMNkAIqDpKQkSVJQUJCbJ8HVRDzgsvj4+GjAgAE6evSounTpogEDBqhnz54KCAjQjBkzlJKSoqeeekrly5dX+fLl9fTTT7scptywYYMaNGggPz8/de/eXSkpKfaydevWyel0ujxet27dFBERYX+9detWtW/fXkFBQSpbtqyGDRum06dPq3PnzkpKSpKfn5/8/Pz0ww8/XOtdAeAy5eTkaMSIEWrVqpXq16/v7nFwFREPuCxpaWmaOXOmqlSpouDgYH3++ecaMGCAEhMTNWDAAD3zzDM6cOCAdu7cqR07dmjPnj3617/+JUlKSEhQ165dNXToUCUmJqp///6aP3/+ZT/20aNH1b59ez300EOKi4vToUOH1LNnTwUHB2vFihUKDAxUamqqUlNTdeedd16rXQDAUHh4uHbu3KkFCxa4exRcZcQDLumll16S0+lU9erVtWfPHi1btkyS1LFjR919993y8PCQj4+PPvvsM02YMEHBwcEqU6aMxo8fr7lz5yonJ0fffvutKlSooEGDBsnLy0tdunRR+/btL3uG+fPnq0mTJhoyZIh8fHxUqlQpIgEo4oYOHapvv/1WUVFRqlixorvHwVXGBZO4pAkTJtgXN12ocuXK9ucnT55URkaGqlatat9WvXp1nT9/XqdOnVJcXJyqVKnicv8qVaro3LlzlzXDoUOHVKNGjb81P4Dry7IsDRs2TEuWLNG6detUrVo1d4+Ea4AjD/hbPDz+369O2bJl5e3trZiYGPu2mJgYlSxZUmXKlFGFChV06NAhl/vHxsban/v5+Sk9PV2WZdm3HTt2zP68SpUqOnDgwF/OAcD9wsPDNX/+fEVGRsrf31/x8fGKj49Xenq6vU58fLyio6Ptf9c7duxQdHS0zpw5466xYYj/8uKKeXh46JFHHtHLL7+sM2fO6PTp0xo1apT69u0rDw8P3XvvvTp69Kg+/vhjZWVl6bvvvtPatWvt+9esWVMlSpRQZGSksrOz9fnnn+u3336zl/fp00c///yzZsyYofPnzystLc2+MDI0NFQpKSk6ceLEdf++AeQ3ffp0JSUlKSwszL6Aunz58lq4cKG9zowZM9S4cWMNHDhQktSmTRs1btzYPi2Koo94wFUxefJkVa1aVXXr1lW9evV066236p133pGU+ydaS5cu1eTJk+V0OjVz5kz16dPHvm9AQIA+/vhjjRw5UsHBwfrxxx91991328srVqyoNWvWKDIyUqGhoapataq+/PJLSVKtWrU0YMAA1a1bV06nUxs3bry+3zgAF5ZlFfhx4ZvCRURE/OU6KNoc1oXHigHYWrdurS37YxV6X393jwIUSbGzxrp7hHwys7K0LOondW3XUiW8it9lfcVlfo48AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADDi5e4BgKKselmntn/4ikp4Fb9/KplZWVoW9ZO6tmtZ7OYvzrNLxXv+4jw7rh+OPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAw4rAsy3L3EEBR1Lp1a23ZH6vQ+/q7exSgSIqdNdbdI+STmZWlZVE/qWu7lirh5eXucYwVl/k58gAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjBAPAICrZsKECWratKn8/f0VEhKibt26ae/evS7rfPTRRwoLC1NAQIAcDocSExPdMyz+NuIBAHDVrF+/XuHh4dq0aZNWr16tzMxMdezYUWfPnrXXSUtLU6dOnTRq1Cg3Toor4eXuAYALhYWFqVu3bhoxYoTL7Q6HQ7/99puio6M1YMAA3XTTTXI4HAoNDVV4eLj+9a9/uWdgAC5Wrlzp8vWcOXMUEhKirVu3qk2bNpJk//tet27ddZ4OVwvxgGKnQYMGio6OliT99NNPuuuuu9SoUSO1b9/evYMByCcpKUmSFBQU5OZJcDVx2gLFWsuWLVWvXj1t3brV3aMAuEhOTo5GjBihVq1aqX79+u4eB1cR8YBiy7IsbdiwQTt37lTNmjXdPQ6Ai4SHh2vnzp1asGCBu0fBVUY8oMh56aWX5HQ6XT4utGPHDjmdTvn4+Kht27Z67rnn1LVrV/cMC6BAQ4cO1bfffquoqChVrFjR3ePgKiMeUORMmDBBiYmJLh8XatCggRITE5WSkqJXXnlFa9euVVZWlnuGBeDCsiwNHTpUS5Ys0dq1a1WtWjV3j4RrgHhAseXt7a2xY8cqPT1d06ZNc/c4AJR7qmL+/PmKjIyUv7+/4uPjFR8fr/T0dHud+Ph4RUdH68CBA5JyjyZGR0frzJkz7hobhogHFGsOh0Mvv/yyxo8fr7S0NHePA/zPmz59upKSkhQWFqby5cvbHwsXLrTXmTFjhho3bqyBAwdKktq0aaPGjRtr2bJl7hobhogHFHvdu3dXUFCQpk6d6u5RgP95lmUV+NGvXz97nYiIiL9cB0Ub7/OAIqWwN42xLEuSdNttt+X7D4yHh4d+//33azwZACAPRx4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGPFy9wBAUVa9rFPbP3xFJbyK3z+VzKwsLYv6SV3btSx28xfn2aXiPX9xnh3XD0ceAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBGHZVmWu4cAiqLWrVtry/5Yhd7X392jAHCT2Fljr+vjZWZlaVnUT+rarqVKeHld18c2wZEHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAwMCECRPUtGlT+fv7KyQkRN26ddPevXvt5TExMXI4HAV+LFq0yI2TXz3EA4w8/fTT+ve//+3uMQDAbdavX6/w8HBt2rRJq1evVmZmpjp27KizZ89KkipVqqRjx465fIwdO1Z+fn7q3Lmzm6e/OrzcPQCKrrCwMP33v/9ViRIl7NvefPNNDRkyxI1TAYB7rVy50uXrOXPmKCQkRFu3blWbNm3k6empcuXKuayzZMkS9ezZU35+ftdz1GuGeMAlTZo0SSNGjHD3GABQZCUlJUmSgoKCCly+detWRUdH64MPPrieY11TnLaAkX79+tkxkXdeb968ebr11lvldDrVr18/ZWZmSpJSU1N1//33KyQkRIGBgWrTpo22bdtmbysiIkJdunTR0KFD5XQ6VblyZS1cuNBenpOTo/fff1+1a9eWv7+/atSoYRe/ZVn2MqfTqbCwMP3+++/Xb0cAgHL/OzVixAi1atVK9evXL3CdWbNmqU6dOmrZsuV1nu7aIR5wxVasWKHffvtNu3fv1po1a/TZZ59Jyv1H9cgjj+jgwYM6fvy4GjdurJ49e8qyLPu+//nPf9SmTRudPn1a48aN05NPPqmUlBRJ0tSpU/Xee+/ps88+U3JystasWaMqVapIkqZPn65Zs2bpm2++0alTp9S9e3d16dJFGRkZ138HAPifFR4erp07d2rBggUFLk9PT1dkZKQGDBhwnSe7togHXNJLL70kp9Npf+RdEHShMWPGyN/fXxUqVFCnTp20detWSVJAQIB69eolX19f+fj4aOzYsdq3b5/i4uLs+95+++3q2bOnPD091bdvX2VkZGjfvn2ScgMhIiJCTZo0kcPhUOXKlVWnTh1J0gcffKDXXntNNWrUkJeXl4YPH6709HRt3rz5OuwVAJCGDh2qb7/9VlFRUapYsWKB63z55ZdKS0vTY489dp2nu7aIB1zShAkTlJiYaH/4+vrmW+fCC4N8fX3tIwfp6ekaMmSIqlatqoCAAFWtWlWSdOrUqQLv63A4dNNNN9n3P3TokGrUqFHgXDExMXr00UddwiYhIUFHjhy54u8ZAC7FsiwNHTpUS5Ys0dq1a1WtWrVC1501a5a6du2qsmXLXscJrz0umMQ18/bbb2vr1q3auHGjKlasqMTERJUuXdrltMWlVKlSRQcOHFCLFi3yLatUqZLee+89derU6WqPDQCXFB4ersjISC1dulT+/v6Kj4+XJAUGBuqmm26y1ztw4IA2bNig5cuXu2vUa4YjD7hmkpOT5ePjo9KlSys1NVWjRo0yuv+gQYM0duxYRUdHy7IsxcbG2hdFhoeHa8yYMfYbsyQnJ2vp0qX2UQsAuFamT5+upKQkhYWFqXz58vbHhRd8S9Ls2bNVsWJFdezY0U2TXjvEA66ZZ599Vp6engoNDVX9+vULPIJwKcOHD9fgwYPVs2dP+fv766677lJsbKyk3HON/fr1U/fu3RUQEKA6deooMjLyWnwbAODCsqwCP/r16+ey3vjx4xUbGysPjxvvqdZhXe4xZOB/TOvWrbVlf6xC7+vv7lEAuEnsrLHX9fEys7K0LOondW3XUiW8iu6VBTdeDgEAgGuKeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARrzcPQBQlFUv69T2D19RCa/i908lMytLy6J+Utd2LYvd/MV5dql4z1+cZ5eK//zFBUceAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABghHgAAgBHiAQAAGCEeAACAEeIBAAAYIR4AAIAR4gEAABhxWJZluXsIoChq3bq1tuyPVeh9/d09CgC4iJ011q2Pz5EHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAA4AYwffp0NWzYUAEBAQoICFCLFi20YsUKe/lHH32ksLAwBQQEyOFwKDEx8W8/FvFQiJiYmCveuddDdHS0HA6HWx77au+jzp07a9q0aVdlWwDwv6ZixYqaOHGitm7dql9++UXt27fX/fffr127dkmS0tLS1KlTJ40aNeqKH+uGjoe9e/eqS5cuKlOmjAICAlS7dm1NmjTJ3WNdV/369ZPD4dDMmTNdbl+0aJEcDoe6devmtrlGjBjhctuKFSs0ZMgQt8wDAMVdly5ddM8996hGjRqqWbOm3njjDfn5+WnTpk2SpBEjRmjkyJFq3rz5FT/WDR0P9957rxo1aqTY2FglJCToq6++UvXq1d091nVXq1YtffLJJy63ffLJJ6pdu/bf3mZmZuaVjgUAuEays7O1YMECnT17Vi1atLjq279h4+HUqVP6448/NGjQIJUqVUqenp6qV6+eevToYa/zzjvvqEaNGvL399ctt9yiqVOnFro9y7L0/vvvq3bt2nI6nQoLC9Pvv//usq3KlSvL399fVatWzfdKP09sbKw6dOigsmXLqnTp0rr33nsVExNjL+/Xr58GDhyo3r17y9/fX7Vq1dK6devs5YmJierZs6ecTqdq166tDRs2/OW+6NChgw4dOqR9+/ZJkuLi4rRly5Z8Rx1efPFFValSRf7+/qpbt64WLVpkL1u3bp2cTqemT5+uypUrq2XLlvkeZ9OmTbr55pu1ePFiSdL333+vZs2ayel0ql69elq2bJkk6f3339dnn32madOmyc/PT/Xq1ZMkhYWF6b333nN5vJkzZ6pSpUoKDg7Wiy++6PJ4U6ZMsZeNHj1at912m+bMmfOX+wMAblQ7duyQn5+fSpYsqaefflpLlixR3bp1r/rj3LDxEBwcrFq1aql///764osvdOjQoXzrVKlSRWvXrlVycrJmzpypF154QT/++GOB25s+fbpmzZqlb775RqdOnVL37t3VpUsXZWRkaN++fRo9erRWrVqllJQUbd68Wc2aNStwOzk5OXr22Wd1+PBhHTp0SKVKldLAgQNd1lm4cKGefvppJSYmqm/fvurXr5+9bPjw4UpMTFRMTIzWrl2ruXPn/uW+8PT01GOPPabZs2dLkj799FP17NlTJUuWdFmvUaNG2rJlixITEzVmzBj17dtXBw8etJenpKRo27Zt2rNnj9avX+9y3++++07du3dXZGSkunfvru3bt6tHjx6aOHGizpw5ow8//FB9+/bV3r17NXz4cPXp00dDhgxRamqqfT7uYikpKdq9e7f279+vjRs36oMPPrBDas2aNRozZoy++uorHTt2TB4eHoVuBwD+V9SqVUvR0dHavHmzBg8erMcff1y7d+++6o9zw8aDw+HQunXr1KhRI40dO1bVq1dX3bp1tXr1anudBx98UJUqVZLD4VC7du109913u7zKv9AHH3yg1157TTVq1JCXl5eGDx+u9PR0bd68WZ6enrIsS7t27VJ6erpCQ0PVsGHDArdTtWpVde7cWT4+PgoICNDLL7+sH374QTk5OfY699xzj8LCwuTp6an+/fvr0KFDOn36tLKzs7Vw4UKNGzdOTqdTFSpU0AsvvHBZ+6Nfv36aN2+esrKyNGfOHPXv3z/fOn369FFISIg8PT3Vu3dv1a5dWz/99JO9PCcnRxMnTlSpUqVUqlQp+/ZPPvlEgwcP1sqVK9W2bVtJ0ocffqh+/fqpffv28vDwUOvWrXXffffpiy++uKx5pdyjPePGjZOPj4/q1Kmjli1bauvWrZKkyMhI9enTR82aNZO3t7deeeUV+fr6Xva2AeBG5O3trVtvvVVNmjTRhAkT1KhRI02ePPmqP84NGw+SVK5cOb399tvatWuXTp48qc6dO+uBBx7QmTNnJEmfffaZbr/9dgUFBcnpdGr58uU6depUgduKiYnRo48+KqfTaX8kJCToyJEjuuWWW/Tpp59q6tSpCg0NVceOHRUdHV3gdk6ePKlHHnlElSpVUkBAgNq0aaPz588rJSXFZe48eU+IKSkpOnXqlDIyMlSlShV7+YWfX0rNmjVVrVo1jRkzRt7e3rrjjjvyrfPuu++qXr16CgwMlNPp1M6dO132h7+/v5xOZ777TZo0SY8++qhLMMXExGjGjBku+2vp0qWKi4u7rHklKSAgwCVSfH197f0UFxenSpUq2ctKlCih8uXLX/a2AeB/QU5Ojs6fP3/Vt3tDx8OFgoKCFBERobNnz+rgwYOKjY3V448/rjfffFMnTpxQYmKi7rnnHlmWVeD9K1WqpEWLFikxMdH+SEtL08MPPyxJ6tmzp6KionT8+HE1atRIffv2LXA7L730ktLS0vTrr78qOTnZvmahsMe9UJkyZVSiRAmXUzCxsbGXvQ/69++viRMnFnjUYePGjYqIiNDcuXOVkJCgxMRE1a9f32UuD4+Cf11WrFihyMhIvfXWW/ZtlSpV0jPPPOOyv1JTUzV9+vRLbutyVahQQYcPH7a/zsrK0rFjx65omwBQnL300kvasGGDYmJitGPHDr300ktat26d+vTpI0mKj49XdHS0Dhw4ICn3+ojo6Gj7BbWJGzYeEhISNHr0aO3Zs0fZ2dlKS0vTO++8o6CgINWuXVupqamyLEshISHy8PDQ8uXLtWrVqkK3Fx4erjFjxmjv3r2SpOTkZC1dulQpKSnau3evVq9erfT0dHl7e8vPz09eXl4Fbic5OVmlSpWS0+nU6dOnNXbs2Mv+njw9PdWzZ0+NGTNGiYmJiouLc3nC/iuPPPKIVq1ale8ai7y5PD09VbZsWeXk5Gj27NnauXPnZW23WrVqWr9+vaZPn64JEyZIkgYNGqRPPvlEUVFRys7O1vnz5/Xf//7Xvsg0NDRUf/7552VFU0EefvhhRUZG6pdfflFmZqbGjRuns2fP/q1tAcCN4MSJE3rsscdUq1Yt/fOf/9SWLVv0n//8Rx06dJAkzZgxQ40bN7afA9q0aaPGjRvbF7ObuGHjwdvbW0ePHtU999yjwMBAVa5cWT/++KNWrFghX19f1a1bVy+//LLat2+v4OBgLVy4UF27di10e0OHDlW/fv3UvXt3BQQEqE6dOoqMjJQkZWRk6JVXXlFoaKiCg4O1du3aQq/6Hzt2rA4cOKDSpUurVatW6ty5s9H3NWXKFPn5+alKlSpq3759oUc4CnLTTTfprrvukr+/f75lnTp10kMPPaQGDRqoQoUK2rVrl1q1anXZ265SpYrWr1+vWbNm6fXXX1fjxo31+eefa/To0SpbtqxuvvlmvfLKK/bhsyeffFJHjx5VUFBQodeHXMpdd92lV199Vd26dVO5cuWUlZWlmjVr5rsIFAD+V8yaNUsxMTE6f/68Tpw4oe+//94OB0mKiIiQZVn5Pi68KP9yOay/+9IPKEIyMjIUHByslStXGkXPpbRu3Vpb9scq9L78p3kAwJ1iZ13+Uetr4YY98oAb3+LFi5Wenq6zZ8/q3//+t4KDg9W0aVN3jwUANzziAcXWvHnzVL58eVWoUEG//vqrli1bJm9vb3ePBQA3vIKv6gOKgSVLlrh7BAD4n8SRBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABghHgAAABGiAcAAGCEeAAAAEaIBwAAYMTL3QMARVn1sk5t//AVlfAqfv9UMrOytCzqJ3Vt17LYzV+cZ5eK9/zFeXaJ+a8XjjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAI8QDAAAwQjwAAAAjxAMAADBCPAAAACPEAwAAMEI8AAAAIw7Lsix3DwEURYMHD5YkTZ8+3c2TAEDRQjwAAAAjnLYAAABGiAcAAGCEeAAAAEaIBwAAYIR4AAAARogHAABgxMvdA/wdSUlJevPNN7V//37dfvvtGjlypLtHAgDgf4ZRPLz00kvas2ePvLy85OHhoTJlyuj222/XQw89pMDAwMvaRmRkpP7880+NHj36bw0sSStXrpSHh4cWLlwoh8Pxt7dzJWbPnq2ff/5Zp0+fVkBAgDp16qQePXrYy7OysjRz5kytW7dODodDYWFhevLJJ+Xp6anMzEzNmDFD0dHRSk5OVnBwsB588EF16NBBUm4cffzxx9q5c6fS0tJUvnx5PfLII/rHP/5xyZlWrlyphQsXKiUlRQ0aNNCwYcMUFBQkSVqzZo0mT56skiVL2uv37t1bDz74YKHbO3PmjN5//33t3LlT/v7+6t27t+6++257+dSpU7Vz507FxcVpwIABuv/++wvd1o4dO/TGG29owYIFl96xl1Dc9nlERIR27dplr5udna2srCzNnz9fAQEBBW7vUvs8MzNTY8aM0eHDh5WRkaGgoCB169ZNnTp1+tv7FAD+FsvAyJEjra+//tqyLMvKycmxYmNjrUmTJln9+vWzEhISLmsbn332mfX666+bPGw+kydPtj766KNCl2dmZl7R9i/HvHnzrEOHDlnZ2dnW4cOHrSeeeMJasWKFvXz+/PnWsGHDrNOnT1unT5+2hg0bZn3++eeWZVlWenq6NX/+fCsuLs7Kycmx9uzZY/Xq1cv69ddfLcuyrGPHjlmLFy+2Tp48aeXk5FibN2+2HnzwQSs2NrbQebZt22b16tXL2rNnj5Wenm6999571qhRo+zl33//vTVs2DCj73HkyJHWe++9Z6Wnp9sz7tixw17+7bffWtHR0dZzzz1n/14UZvv27VavXr2MHv9ixW2fX2zGjBnW6NGjL/k9XmqfZ2dnWwcPHrSysrIsy7Ks2NhYq0+fPtbOnTsvbwcCwFXyt695cDgcqlSpkp577jmVKlVKS5YskSSdO3dO48aN06OPPqpevXpp5MiROnjwoCRp06ZNWrRokbZs2aIePXrYrxp/++03/etf/1KvXr302GOPafr06crIyCjwcSdOnKi1a9dq+fLl6tGjh1avXq01a9Zo+PDh+uyzz9S3b1+99dZbsixLS5Ys0cCBA/Xwww/r1VdfVXx8vL2dAQMGaNGiRXr22Wf10EMPKSIiQikpKZo+fbp69+6tp556Sr///nuh3/+jjz6qypUry8PDQxUrVlSLFi20e/due/n333+vXr16KSgoSEFBQerZs6dWrVolSfLx8VGfPn1Uvnx5ORwO1apVSw0bNrTvX65cOT3wwAMqU6aMHA6HmjVrpptvvll79uwpdJ7vv/9eYWFhqlWrlnx8fPT4449rx44dLt+ziWPHjmnXrl16/PHH5ePjo1q1aqlt27ZavXq1vc69996rRo0aqUSJEpfcVkpKiiIiInT27Fn75573ijwqKkqDBw9W79699eKLL+qPP/4odDvFeZ9nZGRo3bp16tixY6Hb+6t97uHhoapVq8rT09O+j8Ph0LFjxwrdJgBcC1d8waSnp6eaN2+unTt3SpJycnLUtm1bzZw5U/PmzVP16tU1adIkWZal5s2bq0ePHmratKkWLVqkRYsWSZK8vb01bNgwff7553rzzTe1fft2ff311wU+3siRIxUWFqZ77rlHixYtsg87Hzp0SJ6envrkk0/07LPPKioqSl9//bVefvllffrpp6pcubJee+01ZWdn29v64YcfNGrUKH366ac6efKknn/+eTVq1EiRkZFq27atpk2bdln7wLIs7dq1S9WqVZMkpaam6tSpU6pevbq9TvXq1XXy5EmdPXs23/0zMjK0b98+Va1atcDtJyUl6ciRI4Uul6SDBw+6PJ7T6VTp0qV16NAh+7ajR4/q0Ucf1YABAzR9+vQCZ8kTExOjoKAgOZ1Ol+8hJiam0PsUxt/fXxEREfL19bV/7vXq1dPOnTs1bdo0hYeHa/78+WrVqpVeffXVS86Vp7js8zybNm2Sw+FQixYtCt3e5e7z1157Td27d9eQIUPkdDovuU0AuBauyl9bBAcHKyUlRZJUqlQp3XnnnfLx8ZG3t7f69Omjo0eP6syZM4Xev169eqpevbo8PDxUrlw5derUSTt27DCawdfXV7169ZKXl5dKliypqKgodenSRVWrVpW3t7cee+wxnTp1Svv27bPvc88996hMmTLy9fXVHXfcIX9/f7Vs2VIeHh5q06aNDh06pKysrL987Pnz5+v8+fPq3LmzpNyjL3kzXTifJKWnp7vc17IsTZkyRRUqVFDLli3zbTsrK0tvvvmmWrdurRo1ahQ6w7lz51weL+8x09LSJOXu46lTp2revHkaP368jh49qnfffdd4exfPfyWioqLUrl071a9fX15eXrr//vvl5+enX3755S/vWxz2+YX+85//qH379vLyKvwyo8vd52PGjNGXX36pCRMmqFWrVvL29i50mwBwLVyVv7Y4ffq0/P39JeW+ops1a5Z++eUXpaSkyMMjt0/yLlIryP79+/Xpp58qJiZGGRkZys7OVsWKFY1mCA4Odrl48tSpUwoNDbW/LlGihIKCgnT69Gn7tgtf4ZUsWTLf15Zl6fz585f8D/6XX36pDRs2aMKECfLx8ZEk+3/Pnj1rXxiX94Ry00032fe1LEvTp0/X0aNH9frrr+e7+DMrK0sTJkxQyZIlNWzYMPv2Dz74QOvWrZMkhYWFKTw8XD4+PvmetNLS0lSqVClJuYfl84SGhmrQoEEKDw/X+fPnlZycrCFDhtjLp02bVuj2Lpz/Sp0+fVr169d3uS00NFSnTp265P2Kyz7Pc/z4ce3YsUNPPfWUfdvJkyevaJ97eHiofv36+uGHH7R48WL16tXrEnsMAK6uK46H7Oxsbd68WXfccYckacmSJTpw4IAmTZqkMmXK6OzZs+rdu7es////vDMvJi701ltv6a677tLo0aPl4+OjpUuXas2aNUZzXPwkUKZMGR0/ftz+OisrS2fOnCk0YP6OL7/8UitWrNCECRNUpkwZ+3Y/Pz+VKVNGBw8eVPny5SVJf/75p32UQ8p9EpsxY4b27t2rN954I98rzqysLE2cOFFZWVkaPXq0S8CEh4crPDzcZf1q1arpzz//tL9OSkrSmTNnVKVKlQJnz9tflmWpbNmy9imkCx//9OnTSkpKsv+S5s8//yx0e3+loL+KCQ4O1okTJ1xuO378uMu+vFhx3OerVq1SzZo1XW6/Wvs8OztbcXFxhS4HgGvhik5bHDlyRO+++67Onj2rbt26Scp9peTt7S0/Pz+dO3dOc+fOdbmP0+nUyZMnXa49SEtLk6+vr3x8fHT48GGtWLHiSsaSlPvq8LvvvtPhw4eVmZmpefPmKTg4WDVr1rzibUvSV199pe+++07jx49XSEhIvuV33XWXFi5cqISEBCUkJOiLL75w+TPHGTNmaPfu3Ro3bpz8/Pxc7pv3JHbu3Dm9/PLLf3lBYt7jRUVFad++fTp//rw+/fRTNWjQwD7i8Msvv9injk6dOqWPPvpITZo0sV+xX6x8+fKqW7euPv30U50/f1779u3Ld8FfVlaWMjIyZFmWcnJy7KNGBSldurTS0tKUlJRk39auXTutW7dOv//+u7Kzs/XNN98oJSXFDtGLFbd9LuVeA7RmzRr72pxL+at9/ueffyo6Otrez1u2bNG6det0++23/+W2AeBqMj7yMGfOHM2fP18eHh4KDg5WkyZN9N5779mvlLp166b/+7//U9++fRUQEKBHH31Uy5cvt+/fqlUrrV+/Xn369JEkLViwQOHh4Zo5c6bmzJmjW2+9VXfeeac2b958Rd9Y+/btlZiYqLFjxyo1NVU1a9bUmDFjXK5UvxJz5syRl5eXhg4dat9Wr149RURESJJ69eql5ORkDR48WFLuE2XeX5ecOHFCy5cvV4kSJfTEE0/Y9887HL5nzx5t3rzZvmYkT48ePdSzZ88C52nYsKEef/xxjR8/Xqmpqapfv76ee+45e/n27ds1efJkpaWlKSAgQE2bNlXfvn0v+T2+8MILmjJlivr06SN/f3/179/f5TTDK6+8Yl8ou2vXLs2ePVsPP/ywHnnkkXzbuvnmm9WxY0cNHjxYOTk5GjNmjOrXr69BgwZp8uTJSkhIUJUqVewLK2+EfS5Jv/76q86ePas2bdoUup8vdKl9np2drblz5+rIkSNyOBwKCQnRk08+qbZt217WtgHganFYeecTAAAALgP/3xYAAMAI8QAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACMEA8AAMAI8QAAAIwQDwAAwAjxAAAAjBAPAADACPEAAACM/H/WEO+7QpvCggAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_hrcount = vi.hrvar_count(data=pq_data, hrvar='Organization', return_type='plot')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3be31d31",
   "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>Organization</th>\n",
       "      <th>n</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Sales and Marketing</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Finance</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>HR</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Product</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Organization   n\n",
       "3  Sales and Marketing  31\n",
       "0              Finance  27\n",
       "1                   HR  21\n",
       "2              Product  21"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vi.hrvar_count(data=pq_data, hrvar='Organization', return_type='table')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}