NAICS/NAICS.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3fcbaeac",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.rcParams[\"figure.figsize\"] = (20,10) ##Change the figsize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "00514399",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LMO_Detailed_Industry</th>\n",
       "      <th>NAICS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Support activities for mining and oil and gas ...</td>\n",
       "      <td>213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Mining</td>\n",
       "      <td>212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Utilities</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Construction</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Food, beverage and tobacco manufacturing</td>\n",
       "      <td>311 &amp; 312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Wood product manufacturing</td>\n",
       "      <td>321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Paper manufacturing</td>\n",
       "      <td>322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Primary metal manufacturing</td>\n",
       "      <td>331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Fabricated metal product manufacturing</td>\n",
       "      <td>332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Machinery manufacturing</td>\n",
       "      <td>333</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                LMO_Detailed_Industry      NAICS\n",
       "5   Support activities for mining and oil and gas ...        213\n",
       "6                                              Mining        212\n",
       "7                                           Utilities         22\n",
       "8                                        Construction         23\n",
       "9            Food, beverage and tobacco manufacturing  311 & 312\n",
       "10                         Wood product manufacturing        321\n",
       "11                                Paper manufacturing        322\n",
       "12                        Primary metal manufacturing        331\n",
       "13             Fabricated metal product manufacturing        332\n",
       "14                            Machinery manufacturing        333"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "industries=pd.read_excel('./data/LMO_Detailed_Industries_by_NAICS.xlsx')\n",
    "industries.head(15).tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c644c1cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LMO_Detailed_Industry</th>\n",
       "      <th>NAICS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Farms</td>\n",
       "      <td>111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Farms</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Fishing, hunting and trapping</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Forestry and logging</td>\n",
       "      <td>113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Support activities for agriculture and forestry</td>\n",
       "      <td>115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Federal government public administration</td>\n",
       "      <td>911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>Provincial and territorial public administration</td>\n",
       "      <td>912</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>Local and Indigenous public administration</td>\n",
       "      <td>913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Local and Indigenous public administration</td>\n",
       "      <td>914</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Local and Indigenous public administration</td>\n",
       "      <td>919</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>107 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                LMO_Detailed_Industry NAICS\n",
       "0                                               Farms   111\n",
       "1                                               Farms   112\n",
       "2                       Fishing, hunting and trapping   114\n",
       "3                                Forestry and logging   113\n",
       "4     Support activities for agriculture and forestry   115\n",
       "..                                                ...   ...\n",
       "102          Federal government public administration   911\n",
       "103  Provincial and territorial public administration   912\n",
       "104        Local and Indigenous public administration   913\n",
       "105        Local and Indigenous public administration   914\n",
       "106        Local and Indigenous public administration   919\n",
       "\n",
       "[107 rows x 2 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "industries['NAICS']=industries['NAICS'].astype(str).str.replace('&',',')\n",
    "indust = []\n",
    "naics = []\n",
    "for i,row in industries.iterrows():\n",
    "    x = row['NAICS'].split(',')\n",
    "    for val in x:\n",
    "        val = val.strip()\n",
    "        indust.append(row['LMO_Detailed_Industry'])#Store the name\n",
    "        naics.append(val)#Store the code\n",
    "x = {'LMO_Detailed_Industry':indust,'NAICS':naics}\n",
    "industries = pd.DataFrame(x)\n",
    "display(industries)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6802c9ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['data\\\\RTRA_Employ_2NAICS_00_05.csv', 'data\\\\RTRA_Employ_2NAICS_06_10.csv', 'data\\\\RTRA_Employ_2NAICS_11_15.csv', 'data\\\\RTRA_Employ_2NAICS_16_20.csv', 'data\\\\RTRA_Employ_2NAICS_97_99.csv']\n"
     ]
    }
   ],
   "source": [
    "import glob\n",
    "files_2 = glob.glob('data/*2NAICS*.csv')\n",
    "files_3 = glob.glob('data/*3NAICS*.csv')\n",
    "files_4 = glob.glob('data/*4NAICS*.csv')\n",
    "print(files_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1cf6a954",
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_data_based_on_digits(files, four_digits = False):\n",
    "    \"\"\"\"      \n",
    "    The function will create a dataframe with the NAICS hiearchy level         \n",
    "    Args:      \n",
    "    -----------------------------------------      \n",
    "    files: list of csv files\n",
    "    four_digits: bool that checks if its the files containing 4 digits IDs or not.\n",
    "    Returns:      \n",
    "    ----------------------------------------      \n",
    "    final_data: Pandas dataframe        \n",
    "    \"\"\"\n",
    "    ##LOAD THE DATA\n",
    "    employment = pd.read_csv(files[0])\n",
    "    for f in files[1:]:\n",
    "        df = pd.read_csv(f)\n",
    "        employment = employment.append(df,ignore_index=True)#Load the next file\n",
    "    print('First time loading the files')\n",
    "    display(employment)\n",
    "    if not four_digits:\n",
    "        ##CLEAN UP THE NAICS NAME AND CODE COLUMN BY SEPERATING THEM \n",
    "        naics = employment.NAICS.astype(str)#Get the name\n",
    "        naics = naics.astype(str).str.split('[').values #Get the code in the Brackets [\"Code]\"\n",
    "        nc , codes = list(),list()\n",
    "        for n in naics:\n",
    "            try:\n",
    "                nc.append(n[0]) #store the name\n",
    "                codes.append(n[1].strip(']').replace('-',',')) #Remove the bracket and remove the dash\n",
    "            except:\n",
    "                #Other label in 3 digits files\n",
    "                codes.append('99999')\n",
    "        employment['NAICS_CODE'] = codes\n",
    "        employment['NAICS'] = nc\n",
    "        #display(employment[employment['NAICS'] == 'Other']) #DEBUG FOR 3 DIGITS FILES\n",
    "    \n",
    "        #MERGE THE DATA TO GET THE RTRA DATA WE DESIRE FROM THE RELEVENT INDUSTRIES FILES\n",
    "        final_data = employment.merge(industries,left_on='NAICS_CODE',right_on='NAICS',how='left') #A left merge to get the codes and match them to names\n",
    "        final_data = final_data.drop(['NAICS_x','NAICS_y'],axis=1)\n",
    "        final_data.dropna(inplace=True)\n",
    "        print('Cleaning the NAICS column and merging the data')\n",
    "    else:\n",
    "        employment['NAICS'] = employment.NAICS.astype(str)\n",
    "        #MERGE THE DATA TO GET THE RTRA DATA WE DESIRE FROM THE RELEVENT INDUSTRIES FILES\n",
    "        final_data = employment.merge(industries,left_on='NAICS',right_on='NAICS',how='left')\n",
    "        print('merging the data')\n",
    "    display(final_data.head())\n",
    "    #CREATE THE DATETIME INDEX\n",
    "    final_data['Sdate'] = final_data.SMTH.astype(str) + ' ' + final_data.SYEAR.astype(str)\n",
    "    final_data['Sdate'] = pd.to_datetime(final_data['Sdate']).dt.strftime('%Y-%m')\n",
    "    final_data.set_index('Sdate',inplace=True)\n",
    "    if four_digits:\n",
    "        final_data = final_data.rename(columns={'NAICS':'NAICS_CODE'})\n",
    "    final_data = final_data.drop(['SYEAR','SMTH'],axis=1)\n",
    "    final_data = final_data.dropna()\n",
    "\n",
    "    print('Fixing the Date index and dropping unecessary rows (having missing values)')\n",
    "    display(final_data)\n",
    "            \n",
    "    return final_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0c8912f1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First time loading the files\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SYEAR</th>\n",
       "      <th>SMTH</th>\n",
       "      <th>NAICS</th>\n",
       "      <th>_EMPLOYMENT_</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>Accommodation and food services [72]</td>\n",
       "      <td>148000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>Administrative and support, waste management a...</td>\n",
       "      <td>59250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>Agriculture, forestry, fishing and hunting [11]</td>\n",
       "      <td>61750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>Arts, entertainment and recreation [71]</td>\n",
       "      <td>39500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>Construction [23]</td>\n",
       "      <td>106250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5467</th>\n",
       "      <td>1999</td>\n",
       "      <td>12</td>\n",
       "      <td>Real estate, rental and leasing [53]</td>\n",
       "      <td>37000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5468</th>\n",
       "      <td>1999</td>\n",
       "      <td>12</td>\n",
       "      <td>Retail trade  [44-45]</td>\n",
       "      <td>230750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5469</th>\n",
       "      <td>1999</td>\n",
       "      <td>12</td>\n",
       "      <td>Transportation and warehousing [48-49]</td>\n",
       "      <td>117500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5470</th>\n",
       "      <td>1999</td>\n",
       "      <td>12</td>\n",
       "      <td>Utilities [22]</td>\n",
       "      <td>10250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5471</th>\n",
       "      <td>1999</td>\n",
       "      <td>12</td>\n",
       "      <td>Wholesale trade  [41]</td>\n",
       "      <td>74000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5472 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      SYEAR  SMTH                                              NAICS  \\\n",
       "0      2000     1               Accommodation and food services [72]   \n",
       "1      2000     1  Administrative and support, waste management a...   \n",
       "2      2000     1    Agriculture, forestry, fishing and hunting [11]   \n",
       "3      2000     1            Arts, entertainment and recreation [71]   \n",
       "4      2000     1                                  Construction [23]   \n",
       "...     ...   ...                                                ...   \n",
       "5467   1999    12               Real estate, rental and leasing [53]   \n",
       "5468   1999    12                              Retail trade  [44-45]   \n",
       "5469   1999    12             Transportation and warehousing [48-49]   \n",
       "5470   1999    12                                     Utilities [22]   \n",
       "5471   1999    12                              Wholesale trade  [41]   \n",
       "\n",
       "      _EMPLOYMENT_  \n",
       "0           148000  \n",
       "1            59250  \n",
       "2            61750  \n",
       "3            39500  \n",
       "4           106250  \n",
       "...            ...  \n",
       "5467         37000  \n",
       "5468        230750  \n",
       "5469        117500  \n",
       "5470         10250  \n",
       "5471         74000  \n",
       "\n",
       "[5472 rows x 4 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cleaning the NAICS column and merging the data\n"
     ]
    },
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SYEAR</th>\n",
       "      <th>SMTH</th>\n",
       "      <th>_EMPLOYMENT_</th>\n",
       "      <th>NAICS_CODE</th>\n",
       "      <th>LMO_Detailed_Industry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>59250</td>\n",
       "      <td>56</td>\n",
       "      <td>Business, building and other support services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>106250</td>\n",
       "      <td>23</td>\n",
       "      <td>Construction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>1000</td>\n",
       "      <td>55</td>\n",
       "      <td>Business, building and other support services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>100250</td>\n",
       "      <td>81</td>\n",
       "      <td>Repair, personal and non-profit services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2000</td>\n",
       "      <td>1</td>\n",
       "      <td>37500</td>\n",
       "      <td>53</td>\n",
       "      <td>Real estate rental and leasing</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "    SYEAR  SMTH  _EMPLOYMENT_ NAICS_CODE  \\\n",
       "1    2000     1         59250         56   \n",
       "4    2000     1        106250         23   \n",
       "9    2000     1          1000         55   \n",
       "12   2000     1        100250         81   \n",
       "15   2000     1         37500         53   \n",
       "\n",
       "                            LMO_Detailed_Industry  \n",
       "1   Business, building and other support services  \n",
       "4                                    Construction  \n",
       "9   Business, building and other support services  \n",
       "12       Repair, personal and non-profit services  \n",
       "15                 Real estate rental and leasing  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fixing the Date index and dropping unecessary rows (having missing values)\n"
     ]
    },
    {
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       "      <th></th>\n",
       "      <th>_EMPLOYMENT_</th>\n",
       "      <th>NAICS_CODE</th>\n",
       "      <th>LMO_Detailed_Industry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sdate</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01</th>\n",
       "      <td>59250</td>\n",
       "      <td>56</td>\n",
       "      <td>Business, building and other support services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01</th>\n",
       "      <td>106250</td>\n",
       "      <td>23</td>\n",
       "      <td>Construction</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01</th>\n",
       "      <td>1000</td>\n",
       "      <td>55</td>\n",
       "      <td>Business, building and other support services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01</th>\n",
       "      <td>100250</td>\n",
       "      <td>81</td>\n",
       "      <td>Repair, personal and non-profit services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01</th>\n",
       "      <td>37500</td>\n",
       "      <td>53</td>\n",
       "      <td>Real estate rental and leasing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>1250</td>\n",
       "      <td>55</td>\n",
       "      <td>Business, building and other support services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>99500</td>\n",
       "      <td>81</td>\n",
       "      <td>Repair, personal and non-profit services</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>37000</td>\n",
       "      <td>53</td>\n",
       "      <td>Real estate rental and leasing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>10250</td>\n",
       "      <td>22</td>\n",
       "      <td>Utilities</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>74000</td>\n",
       "      <td>41</td>\n",
       "      <td>Wholesale trade</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1884 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         _EMPLOYMENT_ NAICS_CODE  \\\n",
       "Sdate                              \n",
       "2000-01         59250         56   \n",
       "2000-01        106250         23   \n",
       "2000-01          1000         55   \n",
       "2000-01        100250         81   \n",
       "2000-01         37500         53   \n",
       "...               ...        ...   \n",
       "1999-12          1250         55   \n",
       "1999-12         99500         81   \n",
       "1999-12         37000         53   \n",
       "1999-12         10250         22   \n",
       "1999-12         74000         41   \n",
       "\n",
       "                                 LMO_Detailed_Industry  \n",
       "Sdate                                                   \n",
       "2000-01  Business, building and other support services  \n",
       "2000-01                                   Construction  \n",
       "2000-01  Business, building and other support services  \n",
       "2000-01       Repair, personal and non-profit services  \n",
       "2000-01                 Real estate rental and leasing  \n",
       "...                                                ...  \n",
       "1999-12  Business, building and other support services  \n",
       "1999-12       Repair, personal and non-profit services  \n",
       "1999-12                 Real estate rental and leasing  \n",
       "1999-12                                      Utilities  \n",
       "1999-12                                Wholesale trade  \n",
       "\n",
       "[1884 rows x 3 columns]"
      ]
     },
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "First time loading the files\n"
     ]
    },
    {
     "data": {
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       "      <th>SYEAR</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>Aboriginal public administration[914]</td>\n",
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       "      <th>1</th>\n",
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       "      <td>Accommodation services[721]</td>\n",
       "      <td>33750</td>\n",
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       "      <th>2</th>\n",
       "      <td>2000</td>\n",
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       "      <th>28135</th>\n",
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       "      <td>10000</td>\n",
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       "      <th>28136</th>\n",
       "      <td>1999</td>\n",
       "      <td>12</td>\n",
       "      <td>Warehousing and storage[493]</td>\n",
       "      <td>4500</td>\n",
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       "    <tr>\n",
       "      <th>28137</th>\n",
       "      <td>1999</td>\n",
       "      <td>12</td>\n",
       "      <td>Waste management and remediation services[562]</td>\n",
       "      <td>4500</td>\n",
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       "      <th>28138</th>\n",
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       "      <th>28139</th>\n",
       "      <td>1999</td>\n",
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       "      <td>44250</td>\n",
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       "<p>28140 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       SYEAR  SMTH                                           NAICS  \\\n",
       "0       2000     1           Aboriginal public administration[914]   \n",
       "1       2000     1                     Accommodation services[721]   \n",
       "2       2000     1        Administrative and support services[561]   \n",
       "3       2000     1                         Air transportation[481]   \n",
       "4       2000     1            Ambulatory health care services[621]   \n",
       "...      ...   ...                                             ...   \n",
       "28135   1999    12                                  Utilities[221]   \n",
       "28136   1999    12                    Warehousing and storage[493]   \n",
       "28137   1999    12  Waste management and remediation services[562]   \n",
       "28138   1999    12                       Water transportation[483]   \n",
       "28139   1999    12                 Wood product manufacturing[321]   \n",
       "\n",
       "       _EMPLOYMENT_  \n",
       "0               500  \n",
       "1             33750  \n",
       "2             55250  \n",
       "3             17500  \n",
       "4             53000  \n",
       "...             ...  \n",
       "28135         10000  \n",
       "28136          4500  \n",
       "28137          4500  \n",
       "28138          6750  \n",
       "28139         44250  \n",
       "\n",
       "[28140 rows x 4 columns]"
      ]
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     "text": [
      "Cleaning the NAICS column and merging the data\n"
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       "   SYEAR  SMTH  _EMPLOYMENT_ NAICS_CODE  \\\n",
       "0   2000     1           500        914   \n",
       "1   2000     1         33750        721   \n",
       "3   2000     1         17500        481   \n",
       "4   2000     1         53000        621   \n",
       "5   2000     1         22250        713   \n",
       "\n",
       "                           LMO_Detailed_Industry  \n",
       "0     Local and Indigenous public administration  \n",
       "1                         Accommodation services  \n",
       "3                             Air transportation  \n",
       "4                Ambulatory health care services  \n",
       "5  Amusement, gambling and recreation industries  "
      ]
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     "text": [
      "Fixing the Date index and dropping unecessary rows (having missing values)\n"
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       "      <td>29250</td>\n",
       "      <td>484</td>\n",
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       "      <th>1999-12</th>\n",
       "      <td>4500</td>\n",
       "      <td>493</td>\n",
       "      <td>Warehousing and storage</td>\n",
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       "      <th>1999-12</th>\n",
       "      <td>6750</td>\n",
       "      <td>483</td>\n",
       "      <td>Water transportation</td>\n",
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       "      <th>1999-12</th>\n",
       "      <td>44250</td>\n",
       "      <td>321</td>\n",
       "      <td>Wood product manufacturing</td>\n",
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       "<p>20736 rows × 3 columns</p>\n",
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      "text/plain": [
       "         _EMPLOYMENT_ NAICS_CODE  \\\n",
       "Sdate                              \n",
       "2000-01           500        914   \n",
       "2000-01         33750        721   \n",
       "2000-01         17500        481   \n",
       "2000-01         53000        621   \n",
       "2000-01         22250        713   \n",
       "...               ...        ...   \n",
       "1999-12         14000        485   \n",
       "1999-12         29250        484   \n",
       "1999-12          4500        493   \n",
       "1999-12          6750        483   \n",
       "1999-12         44250        321   \n",
       "\n",
       "                                     LMO_Detailed_Industry  \n",
       "Sdate                                                       \n",
       "2000-01         Local and Indigenous public administration  \n",
       "2000-01                             Accommodation services  \n",
       "2000-01                                 Air transportation  \n",
       "2000-01                    Ambulatory health care services  \n",
       "2000-01      Amusement, gambling and recreation industries  \n",
       "...                                                    ...  \n",
       "1999-12  Transit, sightseeing, and pipeline transportation  \n",
       "1999-12                               Truck transportation  \n",
       "1999-12                            Warehousing and storage  \n",
       "1999-12                               Water transportation  \n",
       "1999-12                         Wood product manufacturing  \n",
       "\n",
       "[20736 rows x 3 columns]"
      ]
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     "text": [
      "First time loading the files\n"
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     "data": {
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       "      <td>9120</td>\n",
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       "      <th>85569</th>\n",
       "      <td>1999</td>\n",
       "      <td>12</td>\n",
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       "      <td>30250</td>\n",
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       "      <th>85570</th>\n",
       "      <td>1999</td>\n",
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       "      <td>12</td>\n",
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       "      <td>750</td>\n",
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      ],
      "text/plain": [
       "       SYEAR  SMTH  NAICS  _EMPLOYMENT_\n",
       "0       2000     1   1100           500\n",
       "1       2000     1   1111             0\n",
       "2       2000     1   1112          2000\n",
       "3       2000     1   1113           250\n",
       "4       2000     1   1114          7750\n",
       "...      ...   ...    ...           ...\n",
       "85567   1999    12   9111          2250\n",
       "85568   1999    12   9120         28500\n",
       "85569   1999    12   9130         30250\n",
       "85570   1999    12   9141           500\n",
       "85571   1999    12   9191           750\n",
       "\n",
       "[85572 rows x 4 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "merging the data\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "   SYEAR  SMTH NAICS  _EMPLOYMENT_ LMO_Detailed_Industry\n",
       "0   2000     1  1100           500                   NaN\n",
       "1   2000     1  1111             0                   NaN\n",
       "2   2000     1  1112          2000                   NaN\n",
       "3   2000     1  1113           250                   NaN\n",
       "4   2000     1  1114          7750                   NaN"
      ]
     },
     "metadata": {},
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fixing the Date index and dropping unecessary rows (having missing values)\n"
     ]
    },
    {
     "data": {
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       "      <th>2000-01</th>\n",
       "      <td>3361</td>\n",
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       "    <tr>\n",
       "      <th>2000-01</th>\n",
       "      <td>3362</td>\n",
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       "      <td>Transportation equipment manufacturing (exclud...</td>\n",
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       "      <th>2000-01</th>\n",
       "      <td>3363</td>\n",
       "      <td>1250</td>\n",
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       "      <th>2000-01</th>\n",
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       "      <th>2000-01</th>\n",
       "      <td>3365</td>\n",
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       "      <th>1999-12</th>\n",
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       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>6114</td>\n",
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       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>6115</td>\n",
       "      <td>2250</td>\n",
       "      <td>Private and trades education</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>6116</td>\n",
       "      <td>14250</td>\n",
       "      <td>Private and trades education</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>6117</td>\n",
       "      <td>2000</td>\n",
       "      <td>Private and trades education</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6348 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        NAICS_CODE  _EMPLOYMENT_  \\\n",
       "Sdate                              \n",
       "2000-01       3361          1000   \n",
       "2000-01       3362          2250   \n",
       "2000-01       3363          1250   \n",
       "2000-01       3364          2250   \n",
       "2000-01       3365             0   \n",
       "...            ...           ...   \n",
       "1999-12       6113         13750   \n",
       "1999-12       6114          1500   \n",
       "1999-12       6115          2250   \n",
       "1999-12       6116         14250   \n",
       "1999-12       6117          2000   \n",
       "\n",
       "                                     LMO_Detailed_Industry  \n",
       "Sdate                                                       \n",
       "2000-01  Transportation equipment manufacturing (exclud...  \n",
       "2000-01  Transportation equipment manufacturing (exclud...  \n",
       "2000-01  Transportation equipment manufacturing (exclud...  \n",
       "2000-01  Transportation equipment manufacturing (exclud...  \n",
       "2000-01  Transportation equipment manufacturing (exclud...  \n",
       "...                                                    ...  \n",
       "1999-12                                       Universities  \n",
       "1999-12                       Private and trades education  \n",
       "1999-12                       Private and trades education  \n",
       "1999-12                       Private and trades education  \n",
       "1999-12                       Private and trades education  \n",
       "\n",
       "[6348 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "employment2 = create_data_based_on_digits(files_2,False)\n",
    "employment3 = create_data_based_on_digits(files_3,False)\n",
    "employment4 = create_data_based_on_digits(files_4,True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "89410882",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2000-01</th>\n",
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       "      <th>1999-12</th>\n",
       "      <td>2250</td>\n",
       "      <td>6115</td>\n",
       "      <td>Private and trades education</td>\n",
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       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>14250</td>\n",
       "      <td>6116</td>\n",
       "      <td>Private and trades education</td>\n",
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       "    <tr>\n",
       "      <th>1999-12</th>\n",
       "      <td>2000</td>\n",
       "      <td>6117</td>\n",
       "      <td>Private and trades education</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>27720 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         _EMPLOYMENT_ NAICS_CODE  \\\n",
       "Sdate                              \n",
       "2000-01         59250         56   \n",
       "2000-01        106250         23   \n",
       "2000-01          1000         55   \n",
       "2000-01        100250         81   \n",
       "2000-01         37500         53   \n",
       "...               ...        ...   \n",
       "1999-12         13750       6113   \n",
       "1999-12          1500       6114   \n",
       "1999-12          2250       6115   \n",
       "1999-12         14250       6116   \n",
       "1999-12          2000       6117   \n",
       "\n",
       "                                 LMO_Detailed_Industry  \n",
       "Sdate                                                   \n",
       "2000-01  Business, building and other support services  \n",
       "2000-01                                   Construction  \n",
       "2000-01  Business, building and other support services  \n",
       "2000-01       Repair, personal and non-profit services  \n",
       "2000-01                 Real estate rental and leasing  \n",
       "...                                                ...  \n",
       "1999-12                                   Universities  \n",
       "1999-12                   Private and trades education  \n",
       "1999-12                   Private and trades education  \n",
       "1999-12                   Private and trades education  \n",
       "1999-12                   Private and trades education  \n",
       "\n",
       "[27720 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "employment = employment2.append(employment3)\n",
    "employment = employment.append(employment4) #Vertically stack the dataframes\n",
    "employment = employment[(employment.index >= '1997-01') & (employment.index <= '2018-12')] #Get the date range we're interested in\n",
    "display(employment)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8b38a615",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th rowspan=\"5\" valign=\"top\">1997-01</th>\n",
       "      <th>Accommodation services</th>\n",
       "      <td>24000</td>\n",
       "    </tr>\n",
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       "      <th>Air transportation</th>\n",
       "      <td>17000</td>\n",
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       "      <th>Ambulatory health care services</th>\n",
       "      <td>40000</td>\n",
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       "      <td>20000</td>\n",
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       "      <th>Architectural, engineering and related services</th>\n",
       "      <td>27000</td>\n",
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       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2018-12</th>\n",
       "      <th>Utilities</th>\n",
       "      <td>12250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Warehousing and storage</th>\n",
       "      <td>8750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Water transportation</th>\n",
       "      <td>5000</td>\n",
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       "    <tr>\n",
       "      <th>Wholesale trade</th>\n",
       "      <td>91500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wood product manufacturing</th>\n",
       "      <td>23750</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15576 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         _EMPLOYMENT_\n",
       "Sdate   LMO_Detailed_Industry                                        \n",
       "1997-01 Accommodation services                                  24000\n",
       "        Air transportation                                      17000\n",
       "        Ambulatory health care services                         40000\n",
       "        Amusement, gambling and recreation industries           20000\n",
       "        Architectural, engineering and related services         27000\n",
       "...                                                               ...\n",
       "2018-12 Utilities                                               12250\n",
       "        Warehousing and storage                                  8750\n",
       "        Water transportation                                     5000\n",
       "        Wholesale trade                                         91500\n",
       "        Wood product manufacturing                              23750\n",
       "\n",
       "[15576 rows x 1 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "employment = employment.groupby(['Sdate','LMO_Detailed_Industry']).agg({'_EMPLOYMENT_':sum}) #Group by industry name\n",
    "employment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "71341616",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>1997-01</th>\n",
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       "      <th>1997-01</th>\n",
       "      <td>1997</td>\n",
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       "      <td>2018</td>\n",
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       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Warehousing and storage</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Water transportation</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Wholesale trade</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Wood product manufacturing</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15576 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         SYEAR  SMTH                            LMO_Detailed_Industry  \\\n",
       "Sdate                                                                   \n",
       "1997-01   1997     1                           Accommodation services   \n",
       "1997-01   1997     1                               Air transportation   \n",
       "1997-01   1997     1                  Ambulatory health care services   \n",
       "1997-01   1997     1    Amusement, gambling and recreation industries   \n",
       "1997-01   1997     1  Architectural, engineering and related services   \n",
       "...        ...   ...                                              ...   \n",
       "2018-12   2018    12                                        Utilities   \n",
       "2018-12   2018    12                          Warehousing and storage   \n",
       "2018-12   2018    12                             Water transportation   \n",
       "2018-12   2018    12                                  Wholesale trade   \n",
       "2018-12   2018    12                       Wood product manufacturing   \n",
       "\n",
       "         Employment  \n",
       "Sdate                \n",
       "1997-01         NaN  \n",
       "1997-01         NaN  \n",
       "1997-01         NaN  \n",
       "1997-01         NaN  \n",
       "1997-01         NaN  \n",
       "...             ...  \n",
       "2018-12         NaN  \n",
       "2018-12         NaN  \n",
       "2018-12         NaN  \n",
       "2018-12         NaN  \n",
       "2018-12         NaN  \n",
       "\n",
       "[15576 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output= pd.read_excel('data/Data_Output_Template.xlsx')\n",
    "output['Sdate'] = output.SMTH.astype(str) + ' ' + output.SYEAR.astype(str)\n",
    "output['Sdate'] = pd.to_datetime(output['Sdate']).dt.strftime('%Y-%m')\n",
    "output.set_index('Sdate',inplace=True)\n",
    "#output = output.drop(['SYEAR','SMTH'],axis=1)\n",
    "output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "cf74a390",
   "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>SYEAR</th>\n",
       "      <th>SMTH</th>\n",
       "      <th>LMO_Detailed_Industry</th>\n",
       "      <th>Employment</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sdate</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1997-01</th>\n",
       "      <td>1997</td>\n",
       "      <td>1</td>\n",
       "      <td>Accommodation services</td>\n",
       "      <td>24000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997-01</th>\n",
       "      <td>1997</td>\n",
       "      <td>1</td>\n",
       "      <td>Air transportation</td>\n",
       "      <td>17000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997-01</th>\n",
       "      <td>1997</td>\n",
       "      <td>1</td>\n",
       "      <td>Ambulatory health care services</td>\n",
       "      <td>40000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997-01</th>\n",
       "      <td>1997</td>\n",
       "      <td>1</td>\n",
       "      <td>Amusement, gambling and recreation industries</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997-01</th>\n",
       "      <td>1997</td>\n",
       "      <td>1</td>\n",
       "      <td>Architectural, engineering and related services</td>\n",
       "      <td>27000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Utilities</td>\n",
       "      <td>12250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Warehousing and storage</td>\n",
       "      <td>8750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Water transportation</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Wholesale trade</td>\n",
       "      <td>91500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>Wood product manufacturing</td>\n",
       "      <td>23750</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>15576 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         SYEAR  SMTH                            LMO_Detailed_Industry  \\\n",
       "Sdate                                                                   \n",
       "1997-01   1997     1                           Accommodation services   \n",
       "1997-01   1997     1                               Air transportation   \n",
       "1997-01   1997     1                  Ambulatory health care services   \n",
       "1997-01   1997     1    Amusement, gambling and recreation industries   \n",
       "1997-01   1997     1  Architectural, engineering and related services   \n",
       "...        ...   ...                                              ...   \n",
       "2018-12   2018    12                                        Utilities   \n",
       "2018-12   2018    12                          Warehousing and storage   \n",
       "2018-12   2018    12                             Water transportation   \n",
       "2018-12   2018    12                                  Wholesale trade   \n",
       "2018-12   2018    12                       Wood product manufacturing   \n",
       "\n",
       "         Employment  \n",
       "Sdate                \n",
       "1997-01       24000  \n",
       "1997-01       17000  \n",
       "1997-01       40000  \n",
       "1997-01       20000  \n",
       "1997-01       27000  \n",
       "...             ...  \n",
       "2018-12       12250  \n",
       "2018-12        8750  \n",
       "2018-12        5000  \n",
       "2018-12       91500  \n",
       "2018-12       23750  \n",
       "\n",
       "[15576 rows x 4 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out = output.merge(employment, \n",
    "left_on=['Sdate','LMO_Detailed_Industry'], \n",
    "right_on=['Sdate','LMO_Detailed_Industry'], how='left')\n",
    "out = out.drop(['Employment'],axis=1).rename(columns={'_EMPLOYMENT_':'Employment'}) ##Drop the old empty Employment column and set the new one \n",
    "display(out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4a29d7d0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SYEAR                    0\n",
       "SMTH                     0\n",
       "LMO_Detailed_Industry    0\n",
       "Employment               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "out.isnull().sum() #This confirms a good matching of data? the merge was clean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5025066e",
   "metadata": {},
   "outputs": [],
   "source": [
    "out.to_excel('data_output.xlsx')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b30fb562",
   "metadata": {},
   "source": [
    "## Visualizations and analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7dd55b4c",
   "metadata": {},
   "source": [
    "### Construction vs total employment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "27a7952a",
   "metadata": {},
   "outputs": [],
   "source": [
    "total_emp = out.groupby('SYEAR').agg({'Employment':sum})\n",
    "total_emp['Construction'] = out[out.LMO_Detailed_Industry == 'Construction'].groupby('SYEAR').agg({'Employment':sum}) #Get the sum of employment yearly\n",
    "total_emp = total_emp.rename(columns={'Employment':'Total_employment'})\n",
    "#total_emp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e07b1f77",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='SYEAR'>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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vtbYmGQ2hkuy7hWP8XZKHkqxN8jf9VAoAAADARPW+i1xV7Z7k6iRnt9YeraqtGqe1dnxV7Zrk8iSvTHLDOPdalGRRkkybsU9G1l261XWzCYuvH3YFAAAATMDKpScOuwR2cL3OYKqqnTIaLl3eWruma36wqmZ152dldFbSFmmtrUtyXUYfsxvv/MWttfmttfnTdps5WPEAAAAAbJE+d5GrJJckWdFaO3/MqeuSLOyOFya5djPj7D4mkJqe5DVJ7p38igEAAADYGn0+Ind0ktOS3FVVd3Zt5yZZmuSqqjojyQMZsyNcVa1MMiPJzlV1UpLjknw/yXVVtUuSaUn+d5KP9lg3AAAAABPQW8DU7Qi3sQWXjt3INSMb6f+iyagJAAAAgMk3JbvIAQAAALDj6n0XuWGZN3tmllslHwAAAKB3ZjABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADmT7sAnqz+o5kycxhV7HjWPLIsCsAAAAAtlFmMAEAAAAwkN4Cpqo6oKpurKoVVXV3VZ3Vte9VVTdU1X3d+55d+95d/8eq6qIx4+xWVddX1b3dOEv7qhkAAACAietzBtP6JOe01g5OclSSM6tqbpLFSZa11uYkWdZ9TpJ1Sd6f5F3jjPWh1tqvJjkiydFV9eoe6wYAAABgAnoLmFpra1prt3fHa5OsSDI7yYIkl3XdLktyUtfnh621mzMaNI0d50ettRu7458kuT3J/n3VDQAAAMDETMkaTFU1ktHZR7ck2a+1tiYZDaGS7DuBcZ6Z5N9ldOYTAAAAANuA3neRq6rdk1yd5OzW2qNVtbXjTE9yRZILW2v/tJE+i5IsSpJpM/bJyLpLt65oftHi64ddAQAAAFtg5dITh10CT0G9zmCqqp0yGi5d3lq7pmt+sKpmdednJXloC4e7OMl9rbULNtahtXZxa21+a23+tN1mDlA5AAAAAFuqz13kKsklSVa01s4fc+q6JAu744VJrt2CsT6QZGaSsye5TAAAAAAG1OcjckcnOS3JXVV1Z9d2bpKlSa6qqjOSPJDk5A0XVNXKJDOS7FxVJyU5LsmjSd6X5N4kt3eP2F3UWvvzHmsHAAAAYAv1FjB1O8JtbMGlYzdyzchG+m/dwk0AAAAA9G5KdpEDAAAAYMfV+y5ywzJv9swst3I+AAAAQO/MYAIAAABgIAImAAAAAAYiYAIAAABgIAImAAAAAAYiYAIAAABgIAImAAAAAAYiYAIAAABgIAImAAAAAAYiYAIAAABgIAImAAAAAAYiYAIAAABgINOHXUBvVt+RLJk57Cp2HEseGXYFAAAAwDbKDCYAAAAABiJgAgAAAGAgvQVMVXVAVd1YVSuq6u6qOqtr36uqbqiq+7r3Pbv2vbv+j1XVRU8a67yq+k5VPdZXvQAAAABsnT5nMK1Pck5r7eAkRyU5s6rmJlmcZFlrbU6SZd3nJFmX5P1J3jXOWJ9OcmSPtQIAAACwlXoLmFpra1prt3fHa5OsSDI7yYIkl3XdLktyUtfnh621mzMaND15rH9sra3pq1YAAAAAtt6UrMFUVSNJjkhyS5L9NoRF3fu+U1EDAAAAAP2Y3vcNqmr3JFcnObu19mhV9XmvRUkWJcm0GftkZN2lvd3rKWfx9cOuAAAA4Cln5dITh10CbJFeZzBV1U4ZDZcub61d0zU/WFWzuvOzkjw0WfdrrV3cWpvfWps/bbeZkzUsAAAAAJvQ5y5yleSSJCtaa+ePOXVdkoXd8cIk1/ZVAwAAAAD963MG09FJTkvyyqq6s3u9JsnSJK+qqvuSvKr7nCSpqpVJzk9yelWt6nadS1V9sKpWJdmta1/SY90AAAAATEBvazB1O8JtbMGlYzdyzchG2n83ye9OTmUAAAAATKYp2UUOAAAAgB1X77vIDcu82TOz3Gr7AAAAAL0zgwkAAACAgQiYAAAAABiIgAkAAACAgQiYAAAAABiIgAkAAACAgQiYAAAAABiIgAkAAACAgQiYAAAAABiIgAkAAACAgQiYAAAAABiIgAkAAACAgUwfdgG9WX1HsmTmsKvYcSx5ZNgVAAAAANsoM5gAAAAAGEhvAVNVHVBVN1bViqq6u6rO6tr3qqobquq+7n3Prn3vrv9jVXXRk8Z6YVXdVVX3V9WFVVV91Q0AAADAxPQ5g2l9knNaawcnOSrJmVU1N8niJMtaa3OSLOs+J8m6JO9P8q5xxvrTJIuSzOleJ/RYNwAAAAAT0FvA1Fpb01q7vTtem2RFktlJFiS5rOt2WZKTuj4/bK3dnNGg6QlVNSvJjNbal1prLclfbLgGAAAAgOGbkjWYqmokyRFJbkmyX2ttTTIaQiXZdzOXz06yasznVV0bAAAAANuA3neRq6rdk1yd5OzW2qNbsXzSeBe0jdxrUUYfpcu0GftkZN2lE70XG7P4+mFXAAAA8JSwcumJwy4BJqzXGUxVtVNGw6XLW2vXdM0Pdo+9bXj87aHNDLMqyf5jPu+fZPV4HVtrF7fW5rfW5k/bbeZgxQMAAACwRfrcRa6SXJJkRWvt/DGnrkuysDtemOTaTY3TPUa3tqqO6sb8jc1dAwAAAMDU6fMRuaOTnJbkrqq6s2s7N8nSJFdV1RlJHkhy8oYLqmplkhlJdq6qk5Ic11q7J8k7knw8ydOTfKZ7AQAAALAN6C1g6naE29iCS8du5JqRjbQvT3Lo5FQGAAAAwGSakl3kAAAAANhx9b6L3LDMmz0zy628DwAAANA7M5gAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBTB92Ab1ZfUeyZOawq9gxLXlk2BUAAAAA2xAzmAAAAAAYSG8BU1UdUFU3VtWKqrq7qs7q2veqqhuq6r7ufc8x17y3qu6vqq9X1fFj2n+9qr7ajfPBvmoGAAAAYOL6nMG0Psk5rbWDkxyV5MyqmptkcZJlrbU5SZZ1n9OdOyXJIUlOSPKRqppWVXsn+cMkx7bWDkmyX1Ud22PdAAAAAExAbwFTa21Na+327nhtkhVJZidZkOSyrttlSU7qjhckubK19uPW2reS3J/kyCTPSfKN1tp3u36fS/KGvuoGAAAAYGKmZA2mqhpJckSSW5Ls11pbk4yGUEn27brNTvKdMZet6truT/KrVTVSVdMzGkgdMBV1AwAAALB5ve8iV1W7J7k6ydmttUeraqNdx2lrrbX/U1XvSPKJJI8n+WJGZzWNd69FSRYlybQZ+2Rk3aWDls94Fl8/7AoAAAC2eSuXnjjsEmDK9DqDqap2ymi4dHlr7Zqu+cGqmtWdn5Xkoa59VX5+ZtL+SVYnSWvt0621F7fWXpLk60nuG+9+rbWLW2vzW2vzp+02c/L/IAAAAAB+QZ+7yFWSS5KsaK2dP+bUdUkWdscLk1w7pv2Uqtqlqg5MMifJrd1Y+3bveyb5rSR/3lfdAAAAAExMn4/IHZ3ktCR3VdWdXdu5SZYmuaqqzkjyQJKTk6S1dndVXZXknozuQHdma+1n3XUfrqrDuuM/aK19o8e6AQAAAJiA3gKm1trNGX9dpSQ5diPXnJfkvHHaT53E0gAAAACYRFOyixwAAAAAO67ed5EblnmzZ2a5FfsBAAAAemcGEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADmT7sAnqz+o5kycxhV/HUsuSRYVcAAAAADIEZTAAAAAAMRMAEAAAAwEB6C5iq6oCqurGqVlTV3VV1Vte+V1XdUFX3de97jrnmvVV1f1V9vaqOH9N+alXdVVVfrarPVtWz+qobAAAAgInpcwbT+iTntNYOTnJUkjOram6SxUmWtdbmJFnWfU537pQkhyQ5IclHqmpaVU1P8uEkr2itPT/JV5P8xx7rBgAAAGACtipgqqpXVdUNm+rTWlvTWru9O16bZEWS2UkWJLms63ZZkpO64wVJrmyt/bi19q0k9yc5Mkl1r2dUVSWZkWT11tQNAAAAwOTbZMBUVa+sqm9U1WNV9f9U1dyqWp5kaZI/3dKbVNVIkiOS3JJkv9bammQ0hEqyb9dtdpLvjLlsVZLZrbWfJnlHkrsyGizNTXLJlt4bAAAAgH5N38z5P0qyKMmXkrw6yT8meX9r7cNbeoOq2j3J1UnObq09OjoJafyu47S1qtopowHTEUn+KckfJ3lvkg+Mc69FXb2ZNmOfjKy7dEvLZDIsvn7YFQAAADwlrFx64rBLgJ+zuUfkWmvtpu6xtU8l+e4Ew6WdMhouXd5au6ZrfrCqZnXnZyV5qGtfleSAMZfvn9EZS4d3hXyztdaSXJXk32yk2Itba/Nba/On7TZzS8sEAAAAYACbm8H0zKr6tTGfa+znMaHRL+jWS7okyYrW2vljTl2XZGFGH7NbmOTaMe1/VVXnJ3l2kjlJbk2yX5K5VbVPa+27SV6V0fWcAAAAANgGbC5g+vsk/24jn1uSjQZMSY5OclqSu6rqzq7t3IwGS1dV1RlJHkhycpK01u6uqquS3JPRHejObK39LMnqqvovST5fVT9N8u0kp2/RXwcAAABA72r0qbOtuLBqv9bag5Ncz6TZZdacNmvhBcMuAwAAACadNZgYlqq6rbU2/8ntm1uD6cmDzKyqt1TV55LcPmnVAQAAALDd2twjcqmqpyd5XZJ/n+QFSfZIclKSz/da2YDmzZ6Z5RJdAAAAgN5tcgZTVV2e5BtJjktyUZKRJP+n21nu8f7LAwAAAGBbt7lH5A5N8n8yumvbvd2i21u3aBMAAAAAO6RNBkyttcOSvCnJjCSfq6p/SLJHVf3SVBQHAAAAwLZvs4t8t9buba39XmvteUnemeQvktxaVV/svToAAAAAtnmbXeR7rNba8iTLq+pdSV7WT0kAAAAAbE82t8j3VWOO/8eG49ZaS/K+HusCAAAAYDuxuUfk5ow5ftWTzu0zybUAAAAAsB3aXMC0qR3j7CYHAAAAwGbXYNqtqo7IaBD19O64utfT+y4OAAAAgG3f5gKmf0ly/jjHGz4DAAAA8BS3uYDpda21R6ekEgAAAAC2S5sLmO6oqve11q6ckmom0+o7kiUzh13F9m3JI8OuAAAAANgObG6R71cm+fWquqGqnjsVBQEAAACwfdlkwNRa+3Zr7fVJ/ijJF6rqb6vqug2vTV1bVQdU1Y1VtaKq7q6qs7r2vbrA6r7ufc8x17y3qu6vqq9X1fFd2x5VdeeY1/eq6oKB/3IAAAAAJsXmHpFLVT0vye8m+Yckf5Lk8S0ce32Sc1prt1fVHkluq6obkpyeZFlrbWlVLU6yOMl7qmpuklOSHJLk2Uk+V1UHtdbWJjl8TD23JblmC2sAAAAAoGebDJiqammS12U0KPrMRAZura1JsqY7XltVK5LMTrIgyTFdt8uS3JTkPV37la21Hyf5VlXdn+TIJF8aU8+cJPtmNOwCAAAAYBuwuTWY5iX5vzeES1X1G1V1bVVdWFV7belNqmokyRFJbkmyXxc+bQih9u26zU7ynTGXreraxjo1ySdaa21L7w0AAABAvzb3iNysJOuSpKpelmRpkt/O6CNrFyd54+ZuUFW7J7k6ydmttUeraqNdx2l7cpB0SpLTNnGvRUkWJcm0GftkZN2lmyuPTVl8/bArAAAA2KGsXHrisEuAXmxuBtPTWms/6I5/PcnFrbWrW2vvT7LZXeWqaqeMhkuXt9Y2rJv0YFXN6s7PSvJQ174qyQFjLt8/yeoxYx2WZHpr7baN3a+1dnFrbX5rbf603WZurjwAAAAAJsHmAqbpVbVhltOxSf732HOburBGpypdkmRFa+38MaeuS7KwO16Y5Nox7adU1S5VdWCSOUluHXPdqUmu2Ey9AAAAAEyxzT0id0WSv6+q7yX513SLa1fVc5M8splrj87o42x3VdWdXdu5GX3M7qqqOiPJA0lOTpLW2t1VdVWSezK6A92ZrbWfjRnvTUles4V/FwAAAABTZJMBU2vtvKpaltG1mP7XmMW1n5bRtZg2de3NGX9dpWR0NtS490ty3kbOPWdT9wMAAABgODY3gymttX8cp+0b/ZQDAAAAwPZmc2swAQAAAMAmbXYG0/Zq3uyZWW77RwAAAIDemcEEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwECmD7uA3qy+I1kyc9hVbPuWPDLsCgAAAIDtnBlMAAAAAAykt4Cpqg6oqhurakVV3V1VZ3Xte1XVDVV1X/e+55hr3ltV91fV16vq+DHtO1fVxVX1jaq6t6re0FfdAAAAAExMnzOY1ic5p7V2cJKjkpxZVXOTLE6yrLU2J8my7nO6c6ckOSTJCUk+UlXTurHel+Sh1tpBSeYm+fse6wYAAABgAnoLmFpra1prt3fHa5OsSDI7yYIkl3XdLktyUne8IMmVrbUft9a+leT+JEd2596S5L93Yz3eWvteX3UDAAAAMDFTsgZTVY0kOSLJLUn2a62tSUZDqCT7dt1mJ/nOmMtWJZldVc/sPv/Xqrq9qv66qvabiroBAAAA2Lzed5Grqt2TXJ3k7Nbao1W10a7jtLWM1rh/ki+01n6nqn4nyYeSnDbOvRYlWZQk02bsk5F1l07CX7CDW3z9sCsAAAAYmpVLTxx2CbBD6HUGU1XtlNFw6fLW2jVd84NVNas7PyvJQ137qiQHjLl8/ySrk3w/yY+SfLJr/+skLxjvfq21i1tr81tr86ftNnNS/xYAAAAAxtfnLnKV5JIkK1pr5485dV2Shd3xwiTXjmk/pap2qaoDk8xJcmtrrSX5dJJjun7HJrmnr7oBAAAAmJg+H5E7OqOPsd1VVXd2becmWZrkqqo6I8kDSU5Oktba3VV1VUbDo/VJzmyt/ay77j1J/rKqLkjy3SS/2WPdAAAAAExAbwFTa+3mjL+uUjI6C2m8a85Lct447d9O8rLJqw4AAACAyTIlu8gBAAAAsOPqfRe5YZk3e2aW2w0AAAAAoHdmMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAOZPuwCerP6jmTJzGFXse1Z8siwKwAAAAB2MGYwAQAAADCQ3gKmqjqgqm6sqhVVdXdVndW171VVN1TVfd37nmOueW9V3V9VX6+q48e039S13dm99u2rbgAAAAAmps8ZTOuTnNNaOzjJUUnOrKq5SRYnWdZam5NkWfc53blTkhyS5IQkH6mqaWPGe3Nr7fDu9VCPdQMAAAAwAb0FTK21Na2127vjtUlWJJmdZEGSy7pulyU5qTtekOTK1tqPW2vfSnJ/kiP7qg8AAACAyTElazBV1UiSI5LckmS/1tqaZDSESrLhcbfZSb4z5rJVXdsGl3aPx72/qqr/qgEAAADYEr3vIldVuye5OsnZrbVHN5ENjXeide9vbq39c1Xt0Y11WpK/GOdei5IsSpJpM/bJyLpLBy1/x7P4+mFXAAAAsFVWLj1x2CUAG9HrDKaq2imjgdDlrbVruuYHq2pWd35Wkg3rKa1KcsCYy/dPsjpJWmv/3L2vTfJX2cijc621i1tr81tr86ftNnOy/xwAAAAAxtHnLnKV5JIkK1pr5485dV2Shd3xwiTXjmk/pap2qaoDk8xJcmtVTa+qZ3Vj7pTktUm+1lfdAAAAAExMn4/IHZ3RR9nuqqo7u7ZzkyxNclVVnZHkgSQnJ0lr7e6quirJPRndge7M1trPquoZSf6uC5emJflckj/rsW4AAAAAJqC3gKm1dnPGX1cpSY7dyDXnJTnvSW0/TPLCya0OAAAAgMkyJbvIAQAAALDj6n0XuWGZN3tmltthAAAAAKB3ZjABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMJDpwy6gN6vvSJbMHHYVU2fJI8OuAAAAAHiKMoMJAAAAgIH0FjBV1QFVdWNVraiqu6vqrK59r6q6oaru6973HHPNe6vq/qr6elUdP86Y11XV1/qqGQAAAICJ63MG0/ok57TWDk5yVJIzq2puksVJlrXW5iRZ1n1Od+6UJIckOSHJR6pq2obBqurXkjzWY70AAAAAbIXeAqbW2prW2u3d8dokK5LMTrIgyWVdt8uSnNQdL0hyZWvtx621byW5P8mRSVJVuyf5nSQf6KteAAAAALbOlKzBVFUjSY5IckuS/Vpra5LRECrJvl232Um+M+ayVV1bkvzXJH+U5EdTUS8AAAAAW673XeS62UdXJzm7tfZoVW206zhtraoOT/Lc1to7u6BqU/dalGRRkkybsU9G1l261XVvdxZfP+wKAACAp6CVS08cdgnANqDXGUxVtVNGw6XLW2vXdM0PVtWs7vysJA917auSHDDm8v2TrE7ykiQvrKqVSW5OclBV3TTe/VprF7fW5rfW5k/bbeZk/zkAAAAAjKPPXeQqySVJVrTWzh9z6rokC7vjhUmuHdN+SlXtUlUHJpmT5NbW2p+21p7dWhtJ8tIk32itHdNX3QAAAABMTJ+PyB2d5LQkd1XVnV3buUmWJrmqqs5I8kCSk5OktXZ3VV2V5J6M7kB3ZmvtZz3WBwAAAMAk6C1gaq3dnPHXVUqSYzdyzXlJztvEmCuTHDpwcQAAAABMminZRQ4AAACAHZeACQAAAICB9LkG01DNmz0zy22XCQAAANA7M5gAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGMj0YRfQm9V3JEtmDruKwS15ZNgVAAAAAGySGUwAAAAADKS3gKmqDqiqG6tqRVXdXVVnde17VdUNVXVf977nmGveW1X3V9XXq+r4Me2fraqvdON8tKqm9VU3AAAAABPT5wym9UnOaa0dnOSoJGdW1dwki5Msa63NSbKs+5zu3ClJDklyQpKPjAmS3tRaOyzJoUn2SXJyj3UDAAAAMAG9BUyttTWttdu747VJViSZnWRBksu6bpclOak7XpDkytbaj1tr30pyf5Iju+sf7fpMT7JzktZX3QAAAABMzJSswVRVI0mOSHJLkv1aa2uS0RAqyb5dt9lJvjPmslVd24Yx/i7JQ0nWJvmb/qsGAAAAYEv0votcVe2e5OokZ7fWHq2qjXYdp+2JmUqtteOratcklyd5ZZIbxrnXoiSLkmTajH0ysu7SAavfBiy+ftgVAAAATyErl5447BKA7VCvM5iqaqeMhkuXt9au6ZofrKpZ3flZGZ2VlIzOWDpgzOX7J1k9drzW2rok12X0cbpf0Fq7uLU2v7U2f9puMyfvDwEAAABgo/rcRa6SXJJkRWvt/DGnrkuysDtemOTaMe2nVNUuVXVgkjlJbq2q3ccEUtOTvCbJvX3VDQAAAMDE9PmI3NFJTktyV1Xd2bWdm2Rpkquq6owkD6TbEa61dndVXZXknozuQHdma+1nVfWMJNdV1S5JpiX530k+2mPdAAAAAExAbwFTa+3mjL+uUpIcu5Frzkty3pPaHkzyosmtDgAAAIDJMiW7yAEAAACw4+p9F7lhmTd7Zpbb/QAAAACgd2YwAQAAADAQARMAAAAAAxEwAQAAADAQARMAAAAAAxEwAQAAADAQARMAAAAAAxEwAQAAADAQARMAAAAAAxEwAQAAADAQARMAAAAAAxEwAQAAADAQARMAAAAAA5k+7AJ6s/qOZMnMYVcxmCWPDLsCAAAAgM0ygwkAAACAgfQWMFXVAVV1Y1WtqKq7q+qsrn2vqrqhqu7r3vccc817q+r+qvp6VR3fte1WVddX1b3dOEv7qhkAAACAietzBtP6JOe01g5OclSSM6tqbpLFSZa11uYkWdZ9TnfulCSHJDkhyUeqalo31odaa7+a5IgkR1fVq3usGwAAAIAJ6C1gaq2taa3d3h2vTbIiyewkC5Jc1nW7LMlJ3fGCJFe21n7cWvtWkvuTHNla+1Fr7cZunJ8kuT3J/n3VDQAAAMDETMkaTFU1ktHZR7ck2a+1tiYZDaGS7Nt1m53kO2MuW9W1jR3nmUn+XUZnPgEAAACwDeh9F7mq2j3J1UnObq09WlUb7TpOWxszzvQkVyS5sLX2Txu516Iki5Jk2ox9MrLu0kFKH77F1w+7AgAAYDuwcumJwy4BeIrrdQZTVe2U0XDp8tbaNV3zg1U1qzs/K8lDXfuqJAeMuXz/JKvHfL44yX2ttQs2dr/W2sWttfmttfnTdps5SX8FAAAAAJvS5y5yleSSJCtaa+ePOXVdkoXd8cIk145pP6WqdqmqA5PMSXJrN9YHksxMcnZf9QIAAACwdfp8RO7oJKcluauq7uzazk2yNMlVVXVGkgeSnJwkrbW7q+qqJPdkdAe6M1trP6uq/ZO8L8m9SW7vHrG7qLX25z3WDgAAAMAW6i1gaq3dnPHXVUqSYzdyzXlJzntS26pNjAMAAADAkE3JLnIAAAAA7Lh630VuWObNnpnldlIAAAAA6J0ZTAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMRMAEAAAAwEAETAAAAAAMZPqwC+jN6juSJTOHXcXWW/LIsCsAAAAA2CJmMAEAAAAwEAETAAAAAAPpLWCqqgOq6saqWlFVd1fVWV37XlV1Q1Xd173vOeaa91bV/VX19ao6fkz7eVX1nap6rK96AQAAANg6fc5gWp/knNbawUmOSnJmVc1NsjjJstbanCTLus/pzp2S5JAkJyT5SFVN68b6dJIje6wVAAAAgK3UW8DUWlvTWru9O16bZEWS2UkWJLms63ZZkpO64wVJrmyt/bi19q0k96cLlVpr/9haW9NXrQAAAABsvSlZg6mqRpIckeSWJPttCIu69327brOTfGfMZau6NgAAAAC2YdP7vkFV7Z7k6iRnt9YeraqNdh2nrU3wXouSLEqSaTP2yci6Sydy+bZl8fXDrgAAAJhiK5eeOOwSALZKrzOYqmqnjIZLl7fWrumaH6yqWd35WUke6tpXJTlgzOX7J1k9kfu11i5urc1vrc2fttvMwYoHAAAAYIv0uYtcJbkkyYrW2vljTl2XZGF3vDDJtWPaT6mqXarqwCRzktzaV30AAAAATI4+ZzAdneS0JK+sqju712uSLE3yqqq6L8mrus9prd2d5Kok9yT5bJIzW2s/S5Kq+mBVrUqyW1WtqqolPdYNAAAAwAT0tgZTa+3mjL+uUpIcu5Frzkty3jjtv5vkdyevOgAAAAAmy5TsIgcAAADAjqv3XeSGZd7smVluBwYAAACA3pnBBAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBApg+7gN6sviNZMnPYVWy9JY8MuwIAAACALWIGEwAAAAAD6S1gqqoDqurGqlpRVXdX1Vld+15VdUNV3de97znmmvdW1f1V9fWqOn5M+wur6q7u3IVVVX3VDQAAAMDE9DmDaX2Sc1prByc5KsmZVTU3yeIky1prc5Is6z6nO3dKkkOSnJDkI1U1rRvrT5MsSjKne53QY90AAAAATEBvAVNrbU1r7fbueG2SFUlmJ1mQ5LKu22VJTuqOFyS5srX249bat5Lcn+TIqpqVZEZr7UuttZbkL8ZcAwAAAMCQTckaTFU1kuSIJLck2a+1tiYZDaGS7Nt1m53kO2MuW9W1ze6On9wOAAAAwDag913kqmr3JFcnObu19ugmlk8a70TbRPt491qU0UfpMm3GPhlZd+nEC95WLL5+2BUAAADbiJVLTxx2CQCb1OsMpqraKaPh0uWttWu65ge7x97SvT/Uta9KcsCYy/dPsrpr33+c9l/QWru4tTa/tTZ/2m4zJ+8PAQAAAGCj+txFrpJckmRFa+38MaeuS7KwO16Y5Nox7adU1S5VdWBGF/O+tXuMbm1VHdWN+RtjrgEAAABgyPp8RO7oJKcluauq7uzazk2yNMlVVXVGkgeSnJwkrbW7q+qqJPdkdAe6M1trP+uue0eSjyd5epLPdC8AAAAAtgG9BUyttZsz/vpJSXLsRq45L8l547QvT3Lo5FUHAAAAwGSZkl3kAAAAANhx9b6L3LDMmz0zy+20AAAAANA7M5gAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBCJgAAAAAGIiACQAAAICBTB92Ab1ZfUeyZOawq9h6Sx4ZdgUAAAAAW8QMJgAAAAAG0lvAVFUfq6qHquprY9oOq6ovVdVdVfXpqprRte9cVZd27V+pqmPGXPPrVfXVqrq7qj7YV70AAAAAbJ0+ZzB9PMkJT2r78ySLW2vzknwyybu79rclSdf+qiR/VFVPq6q9k/xhkmNba4ck2a+qju2xZgAAAAAmqLeAqbX2+SQ/eFLz85J8vju+IckbuuO5SZZ11z2U5OEk85M8J8k3Wmvf7fp9bsw1AAAAAGwDpnoNpq8leV13fHKSA7rjryRZUFXTq+rAJC/szt2f5FeraqSqpic5acw1AAAAAGwDpnoXubckubCqfi/JdUl+0rV/LMnBSZYn+XaSLyZZ31r7P1X1jiSfSPJ41/6cjQ1eVYuSLEqSaTP2yci6S/v6O/q3+PphVwAAAAxo5dITh10CwJSY0oCptXZvkuOSpKoOSnJi174+yTs39KuqLya5rzv36SSf7toXJfnZJsa/OMnFSbLLrDmtlz8CAAAAgJ8zpY/IVdW+3fvTkvznJB/tPu9WVc/ojl+V0dlL9zzpmj2T/FZGFwoHAAAAYBvR2wymqroiyTFJnlVVq5L8fpLdq+rMrss1STY8w7Zvkr+rqseT/HOS08YM9eGqOqw7/oPW2jf6qhkAAACAiestYGqtnbqRUx8ep+/KjO4wN5FxAAAAANgGTPUucgAAAADsYKZ6F7kpM2/2zCy3YwMAAABA78xgAgAAAGAgAiYAAAAABiJgAgAAAGAgAiYAAAAABiJgAgAAAGAgAiYAAAAABiJgAgAAAGAgAiYAAAAABiJgAgAAAGAgAiYAAAAABiJgAgAAAGAgAiYAAAAABjJ92AX0ZvUdyZKZw65icEseGXYFAAAAAJtkBhMAAAAAA+ktYKqqj1XVQ1X1tTFth1XVl6rqrqr6dFXN6Np3rqpLu/avVNUxY645tWv/alV9tqqe1VfNAAAAAExcnzOYPp7khCe1/XmSxa21eUk+meTdXfvbkqRrf1WSP6qqp1XV9CQfTvKK1trzk3w1yX/ssWYAAAAAJqi3NZhaa5+vqpEnNT8vyee74xuS/F2S9yeZm2RZd91DVfVwkvlJ7khSSZ5RVd9PMiPJ/X3VDAAAAPy8n/70p1m1alXWrVs37FKYQrvuumv233//7LTTTlvUf6oX+f5aktcluTbJyUkO6Nq/kmRBVV3Ztb0wyQGttVur6h1J7krywyT3JTlzimsGAACAp6xVq1Zljz32yMjISKpq2OUwBVpr+f73v59Vq1blwAMP3KJrpjpgekuSC6vq95Jcl+QnXfvHkhycZHmSbyf5YpL1VbVTknckOSLJPyX54yTvTfKB8QavqkVJFiXJtBn7ZGTdpf39JVNl8fXDrgAAAEiycumJwy4BhmLdunXCpaeYqsree++d7373u1t8zZQGTK21e5MclyRVdVCSE7v29UneuaFfVX0xo7OVDu/Of7NrvyrJ4k2Mf3GSi5Nkl1lzWh9/AwAAADzVCJeeeib637zPRb5/QVXt270/Lcl/TvLR7vNuVfWM7vhVSda31u5J8s9J5lbVPt0Qr0qyYiprBgAAAGDTepvBVFVXJDkmybOqalWS30+ye1VtWEPpmiQbnmHbN8nfVdXjGQ2VTkuS1trqqvovST5fVT/N6ONzp/dVMwAAALBpI5O8lMvmHj/9/ve/n2OPPTZJ8i//8i+ZNm1a9tlndB7Krbfemp133vmJvhdccEEWLVqU3XbbbZNjHnPMMfnQhz6U+fPnD1j9xIyMjGT58uV51rOeNaX33ZiHH344f/VXf5Xf+q3fGnisPneRO3Ujpz48Tt+VGd1hbrxxPppuphMAAADw1LL33nvnzjvvTJIsWbIku+++e971rneN2/eCCy7If/gP/2GzAROjHn744XzkIx+ZlIBpSh+RAwAAABjUsmXLcsQRR2TevHl5y1vekh//+Me58MILs3r16rziFa/IK17xiiTJO97xjsyfPz+HHHJIfv/3f3+Lx/9f/+t/5SUveUle8IIX5OSTT85jjz2WZHQG0rnnnpuXvOQlmT9/fm6//fYcf/zx+ZVf+ZV89KOjc2NuuummvOxlL8vrX//6zJ07N29/+9vz+OOP/8I9zj///Bx66KE59NBDc8EFFyRJ3v/+9+fDH/7/5+W8733vy4UXXpibbropL3/5y/OmN70pBx10UBYvXpzLL788Rx55ZObNm5dvfvObSZLvfve7ecMb3pAXvehFedGLXpQvfOELSUaDube85S055phj8pznPCcXXnhhkmTx4sX55je/mcMPPzzvfve7J/hf4edN9S5yU2be7JlZbpcHAAAA2KGsW7cup59+epYtW5aDDjoov/Ebv5E//dM/zdlnn53zzz8/N9544xOPoJ133nnZa6+98rOf/SzHHntsvvrVr+b5z3/+Jsf/3ve+lw984AP53Oc+l2c84xn5H//jf+T888/P7/3e7yVJDjjggHzpS1/KO9/5zpx++un5whe+kHXr1uWQQw7J29/+9iSjj+7dc889+eVf/uWccMIJueaaa/LGN77xiXvcdtttufTSS3PLLbektZYXv/jFefnLX54zzjgjv/Zrv5azzjorjz/+eK688srceuutueuuu/KVr3wlK1asyF577ZXnPOc5eetb35pbb701H/7wh/PHf/zHueCCC3LWWWflne98Z1760pfmgQceyPHHH58VK0aXsr733ntz4403Zu3atXne856Xd7zjHVm6dGm+9rWvPTFDbBA7bMAEAAAA7Hh+9rOf5cADD8xBBx2UJFm4cGH+5E/+JGefffYv9L3qqqty8cUXZ/369VmzZk3uueeezQZM//iP/5h77rknRx99dJLkJz/5SV7ykpc8cf51r3tdkmTevHl57LHHsscee2SPPfbIrrvumocffjhJcuSRR+Y5z3lOkuTUU0/NzTff/HMB080335zXv/71ecYznpEk+bVf+7X8wz/8Q/7Tf/pP2XvvvXPHHXfkwQcfzBFHHJG99947SfKiF70os2bNSpL8yq/8So477rgn6rjxxhuTJJ/73Odyzz33PHGfRx99NGvXrk2SnHjiidlll12yyy67ZN99982DDz64uX/qCREwAQAAANuNDaHM5nzrW9/Khz70oXz5y1/OnnvumdNPPz3r1q3b7HWttbzqVa/KFVdcMe75XXbZJUnytKc97YnjDZ/Xr1+fJKmqn7vmyZ9baxu9/1vf+tZ8/OMfz7/8y7/kLW95yy/c98n3Hnvfxx9/PF/60pfy9Kc/faN1J8m0adOeuGayWIMJAAAA2G6sW7cuK1euzP33358k+cu//Mu8/OUvT5LsscceT8zYefTRR/OMZzwjM2fOzIMPPpjPfOYzWzT+UUcdlS984QtPjP+jH/0o3/jGNyZU46233ppvfetbefzxx/OJT3wiL33pS3/u/Mte9rJ86lOfyo9+9KP88Ic/zCc/+cn823/7b5Mkr3/96/PZz342X/7yl3P88cdP6L7HHXdcLrrooic+b+7Rt7H/XoMygwkAAADYYiuHvN7xrrvumksvvTQnn3xy1q9fnxe96EVPrH20aNGivPrVr86sWbNy44035ogjjsghhxyS5zznOU888rY5++yzTz7+8Y/n1FNPzY9//OMkyQc+8IEnHsnbEi95yUuyePHi3HXXXU8s+D3WC17wgpx++uk58sgjk4zOWjriiCOSJDvvvHNe8YpX5JnPfGamTZu2xfdMkgsvvDBnnnlmnv/852f9+vV52cte9sTi4+PZe++9c/TRR+fQQw/Nq1/96vzhH/7hhO43Vm1qWtb2bP78+W358uXDLgMAAAC2aytWrMjBBx887DK2GzfddFM+9KEP5W//9m+36vrHH388L3jBC/LXf/3XmTNnziRXNzHj/bevqttaa/Of3NcjcgAAAADbgHvuuSfPfe5zc+yxxw49XJooj8gBAAAAT0kvfvGLn3gMboO//Mu/zLx587Z6zGOOOSbHHHPMVl07d+7c/NM//dNW33uYBEwAAADAU9Itt9wy7BJ2GB6RAwAAAGAgAiYAAAAABiJgAgAAAGAgO+4aTKvvSJbMHHYVk2vJI8OuAAAAAKbcv/zLv+Tss8/Ol7/85eyyyy4ZGRnJBRdckIMOOmjgsT/1qU/loIMOyty5cyeh0uTjH/94jjvuuDz72c9Okrz1rW/N7/zO70za+NuqHTdgAgAAACbfZE/m2MxkitZaXv/612fhwoW58sorkyR33nlnHnzwwUkLmF772teOGwCtX78+06dPLDr5+Mc/nkMPPfSJgOnP//zPB65xe9DbI3JV9bGqeqiqvjam7bCq+lJV3VVVn66qGV37zlV1adf+lao6pmvfo6ruHPP6XlVd0FfNAAAAwLblxhtvzE477ZS3v/3tT7QdfvjheelLX5p3v/vdOfTQQzNv3rx84hOfSJLcdNNNOeaYY/LGN74xv/qrv5o3v/nNaa0lSRYvXpy5c+fm+c9/ft71rnfli1/8Yq677rq8+93vzuGHH55vfvObOeaYY3Luuefm5S9/eT784Q/n9NNPz9/8zd88ce/dd9/9ieMPfvCDmTdvXg477LAsXrw4f/M3f5Ply5fnzW9+cw4//PD867/+a4455pgsX748SXLFFVdk3rx5OfTQQ/Oe97zn58Z83/vel8MOOyxHHXVUHnzwwV7/TfvQ5wymjye5KMlfjGn78yTvaq39fVW9Jcm7k7w/yduSpLU2r6r2TfKZqnpRa21tksM3XFxVtyW5pseaAQAAgG3I1772tbzwhS/8hfZrrrkmd955Z77yla/ke9/7Xl70ohflZS97WZLkjjvuyN13351nP/vZOfroo/OFL3whc+fOzSc/+cnce++9qao8/PDDeeYzn5nXve51ee1rX5s3vvGNT4z98MMP5+///u+TJKeffvq4dX3mM5/Jpz71qdxyyy3Zbbfd8oMf/CB77bVXLrroonzoQx/K/Pnzf67/6tWr8573vCe33XZb9txzzxx33HH51Kc+lZNOOik//OEPc9RRR+W8887L7/7u7+bP/uzP8p//83+epH/BqdHbDKbW2ueT/OBJzc9L8vnu+IYkb+iO5yZZ1l33UJKHk/zcf4mqmpNk3yT/0E/FAAAAwPbi5ptvzqmnnppp06Zlv/32y8tf/vJ8+ctfTpIceeSR2X///fO0pz0thx9+eFauXJkZM2Zk1113zVvf+tZcc8012W233TY69q//+q9v9v6f+9zn8pu/+ZtPjLPXXnttsv+Xv/zlHHPMMdlnn30yffr0vPnNb87nPz8akey888557WtfmyR54QtfmJUrV27JP8E2Zap3kftaktd1xycnOaA7/kqSBVU1vaoOTPLCMec2ODXJJ9qGeW0AAADADu+QQw7Jbbfd9gvtm4oHdtlllyeOp02b9sRaSrfeemve8IY35FOf+lROOOGEjV7/jGc844nj6dOn5/HHH3/inj/5yU+eOK6qLf47NlXvTjvt9MRYG+rd3kz1It9vSXJhVf1ekuuS/KRr/1iSg5MsT/LtJF9M8uR/zVOSnLapwatqUZJFSTJtxj4ZWXfp5FW+LVh8/bArAACAp6yVS08cdgnwlPTKV74y5557bv7sz/4sb3vb25KMzgbac88984lPfCILFy7MD37wg3z+85/PH/7hH+bee+8dd5zHHnssP/rRj/Ka17wmRx11VJ773OcmSfbYY4+sXbt2o/cfGRnJbbfdlje96U259tpr89Of/jRJctxxx+UP/uAP8u///b//uUfkNjbei1/84px11ln53ve+lz333DNXXHFFfvu3f3vQf55txpQGTK21e5MclyRVdVCSE7v29UneuaFfVX0xyX1jPh+WZHpr7Rcjy58f/+IkFyfJLrPmmOkEAAAA27mqyic/+cmcffbZWbp0aXbdddeMjIzkggsuyGOPPZbDDjssVZUPfvCD+aVf+qWNBkxr167NggULsm7durTW8j//5/9Mkpxyyil529velgsvvPDnFvPe4G1ve1sWLFiQI488Mscee+wTs5tOOOGE3HnnnZk/f3523nnnvOY1r8l/+2//Laeffnre/va35+lPf3q+9KUvPTHOrFmz8t//+3/PK17xirTW8prXvCYLFizo4V9sOKrPJ86qaiTJ37bWDu0+79tae6iqnpbRRcBvaq19rKp262r5YVW9Ksn7W2svGzPO0iQ/bq39/pbee5dZc9qshRdM4l8DAAA8lZnBxFPVihUrcvDBBw+7DIZgvP/2VXVba23+k/v2NoOpqq5IckySZ1XVqiS/n2T3qjqz63JNkg3PsO2b5O+q6vEk/5xffBTuTUle01etAAAAAGy93gKm1tqpGzn14XH6rszoDnMbG+s5k1QWAAAAAJNsqneRAwAAAGAHI2ACAAAANqnP9ZvZNk30v/mU7iI3lebNnpnlFuEDAACAgey66675/ve/n7333jtVNexymAKttXz/+9/PrrvuusXX7LABEwAAADC4/fffP6tWrcp3v/vdYZfCFNp1112z//77b3F/ARMAAACwUTvttFMOPPDAYZfBNs4aTAAAAAAMRMAEAAAAwEAETAAAAAAMpHbUrQaram2Srw+7DhjAs5J8b9hFwIB8j9kR+B6zvfMdZkfge8z2bkf6Dv9ya22fJzfuyIt8f721Nn/YRcDWqqrlvsNs73yP2RH4HrO98x1mR+B7zPbuqfAd9ogcAAAAAAMRMAEAAAAwkB05YLp42AXAgHyH2RH4HrMj8D1me+c7zI7A95jt3Q7/Hd5hF/kGAAAAYGrsyDOYAAAAAJgC23XAVFUnVNXXq+r+qlo8zvmqqgu781+tqhcMo07YlC34Hh9TVY9U1Z3d6/eGUSdsTFV9rKoeqqqvbeS832K2eVvwPfZbzDatqg6oqhurakVV3V1VZ43Tx+8x26wt/A77LWabVlW7VtWtVfWV7nv8X8bps8P+Fk8fdgFbq6qmJfmTJK9KsirJl6vqutbaPWO6vTrJnO714iR/2r3DNmELv8dJ8g+ttddOeYGwZT6e5KIkf7GR836L2R58PJv+Hid+i9m2rU9yTmvt9qraI8ltVXWD/2/MdmRLvsOJ32K2bT9O8srW2mNVtVOSm6vqM621fxzTZ4f9Ld6eZzAdmeT+1to/tdZ+kuTKJAue1GdBkr9oo/4xyTOratZUFwqbsCXfY9imtdY+n+QHm+jit5ht3hZ8j2Gb1lpb01q7vTtem2RFktlP6ub3mG3WFn6HYZvW/b4+1n3cqXs9eeHrHfa3eHsOmGYn+c6Yz6vyiz9AW9IHhmlLv6Mv6aZZfqaqDpma0mDS+C1mR+G3mO1CVY0kOSLJLU865feY7cImvsOJ32K2cVU1raruTPJQkhtaa0+Z3+Lt9hG5JDVO25OTwS3pA8O0Jd/R25P8cjfN8jVJPpXR6ZSwvfBbzI7AbzHbharaPcnVSc5urT365NPjXOL3mG3KZr7DfovZ5rXWfpbk8Kp6ZpJPVtWhrbWxazzusL/F2/MMplVJDhjzef8kq7eiDwzTZr+jrbVHN0yzbK39v0l2qqpnTV2JMDC/xWz3/BazPejW+7g6yeWttWvG6eL3mG3a5r7DfovZnrTWHk5yU5ITnnRqh/0t3p4Dpi8nmVNVB1bVzklOSXLdk/pcl+Q3ulXaj0rySGttzVQXCpuw2e9xVf1SVVV3fGRG/3f7/SmvFLae32K2e36L2dZ1389LkqxorZ2/kW5+j9lmbcl32G8x27qq2qebuZSqenqS/zvJvU/qtsP+Fm+3j8i11tZX1X9M8ndJpiX5WGvt7qp6e3f+o0n+3ySvSXJ/kh8l+c1h1Qvj2cLv8RuTvKOq1if51ySntNZ2iCmU7Biq6ookxyR5VlWtSvL7GV3Q0G8x240t+B77LWZbd3SS05Lc1a39kSTnJvm/Er/HbBe25Dvst5ht3awkl3W7hT8tyVWttb99quQU5X+PAAAAAAxie35EDgAAAIBtgIAJAAAAgIEImAAAAAAYiIAJAAAAgIEImAAAAAB2cFX1sap6qKq+tgV9/2dV3dm9vlFVD2/2GrvIAQAAAOzYquplSR5L8hettUMncN1vJzmitfaWTfUzgwkAAABgB9da+3ySH4xtq6pfqarPVtVtVfUPVfWr41x6apIrNjf+9EmqEwAAAIDty8VJ3t5au6+qXpzkI0leueFkVf1ykgOT/O/NDSRgAgAAAHiKqardk/ybJH9dVRuad3lSt1OS/E1r7WebG0/ABAAAAPDU87QkD7fWDt9En1OSnLmlgwEAAADwFNJaezTJt6rq5CSpUYdtOF9Vz0uyZ5Ivbcl4AiYAAACAHVxVXZHRsOh5VbWqqs5I8uYkZ1TVV5LcnWTBmEtOTXJla61t0fhb2A8AAAAAxmUGEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMBABEwAAAAADETABAAAAMJD/DweXk6X2LVeKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_emp.plot(use_index= True, y=[\"Total_employment\", \"Construction\"], kind=\"barh\") #Horizontal bars"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8db352d0",
   "metadata": {},
   "source": [
    "### TOP 5 Industries evolution through time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f0caccb1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Other retail trade (excluding cars and personal care) ',\n",
       " 'Construction',\n",
       " 'Food services and drinking places',\n",
       " 'Repair, personal and non-profit services',\n",
       " 'Business, building and other support services']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_emp = out.groupby(['LMO_Detailed_Industry']).agg({'Employment':np.mean}).sort_values(by='Employment',ascending=False)[:5] #Get avg top 5 employment\n",
    "top5 = total_emp.reset_index()['LMO_Detailed_Industry'].to_list() #get the industry names\n",
    "top5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9f63da13",
   "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>Employment</th>\n",
       "      <th>Other retail trade (excluding cars and personal care)</th>\n",
       "      <th>Construction</th>\n",
       "      <th>Food services and drinking places</th>\n",
       "      <th>Repair, personal and non-profit services</th>\n",
       "      <th>Business, building and other support services</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SYEAR</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>22337000</td>\n",
       "      <td>2450000</td>\n",
       "      <td>1489750</td>\n",
       "      <td>1327750</td>\n",
       "      <td>1086750</td>\n",
       "      <td>743750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>22347250</td>\n",
       "      <td>2498750</td>\n",
       "      <td>1424750</td>\n",
       "      <td>1358250</td>\n",
       "      <td>1107500</td>\n",
       "      <td>782250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>22697000</td>\n",
       "      <td>2467000</td>\n",
       "      <td>1363500</td>\n",
       "      <td>1375000</td>\n",
       "      <td>1266750</td>\n",
       "      <td>777500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000</th>\n",
       "      <td>23217250</td>\n",
       "      <td>2566750</td>\n",
       "      <td>1345750</td>\n",
       "      <td>1412250</td>\n",
       "      <td>1179000</td>\n",
       "      <td>836250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001</th>\n",
       "      <td>23041250</td>\n",
       "      <td>2523750</td>\n",
       "      <td>1347250</td>\n",
       "      <td>1439750</td>\n",
       "      <td>1183250</td>\n",
       "      <td>846250</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Employment  Other retail trade (excluding cars and personal care)   \\\n",
       "SYEAR                                                                       \n",
       "1997     22337000                                            2450000        \n",
       "1998     22347250                                            2498750        \n",
       "1999     22697000                                            2467000        \n",
       "2000     23217250                                            2566750        \n",
       "2001     23041250                                            2523750        \n",
       "\n",
       "       Construction  Food services and drinking places  \\\n",
       "SYEAR                                                    \n",
       "1997        1489750                            1327750   \n",
       "1998        1424750                            1358250   \n",
       "1999        1363500                            1375000   \n",
       "2000        1345750                            1412250   \n",
       "2001        1347250                            1439750   \n",
       "\n",
       "       Repair, personal and non-profit services  \\\n",
       "SYEAR                                             \n",
       "1997                                    1086750   \n",
       "1998                                    1107500   \n",
       "1999                                    1266750   \n",
       "2000                                    1179000   \n",
       "2001                                    1183250   \n",
       "\n",
       "       Business, building and other support services  \n",
       "SYEAR                                                 \n",
       "1997                                          743750  \n",
       "1998                                          782250  \n",
       "1999                                          777500  \n",
       "2000                                          836250  \n",
       "2001                                          846250  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_emp =  out.groupby('SYEAR').agg({'Employment':sum})\n",
    "for indust in top5:\n",
    "    total_emp[indust] = out[out.LMO_Detailed_Industry == indust].groupby('SYEAR').agg({'Employment':sum})\n",
    "total_emp.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "e553d4f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='SYEAR'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_emp.plot(use_index= True, y=total_emp.columns[1:], kind=\"line\") #Horizontal bars"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "22f177ce",
   "metadata": {},
   "source": [
    "### Bottom 5 industries through time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "292a8de3",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='SYEAR'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_emp = out.groupby(['LMO_Detailed_Industry']).agg({'Employment':np.mean}).sort_values(by='Employment',ascending=True)[:5] #Get avg bottom industries\n",
    "bottom5 = total_emp.reset_index()['LMO_Detailed_Industry'].to_list() #get the industry names\n",
    "bottom5\n",
    "total_emp =  out.groupby('SYEAR').agg({'Employment':sum})\n",
    "for indust in bottom5:\n",
    "    total_emp[indust] = out[out.LMO_Detailed_Industry == indust].groupby('SYEAR').agg({'Employment':sum})\n",
    "total_emp.head()\n",
    "total_emp.plot(use_index= True, y=total_emp.columns[1:], kind=\"line\") #Horizontal bars"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9438b5c8",
   "metadata": {},
   "source": [
    "### THE FOOD AND RETAIL SERVICES"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "10d6d76b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='SYEAR'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_emp = out.groupby('SYEAR').agg({'Employment':sum})\n",
    "total_emp['Other retail'] = out[out.LMO_Detailed_Industry == 'Other retail trade (excluding cars and personal care) '].groupby('SYEAR').agg({'Employment':sum})\n",
    "total_emp['Food'] = out[out.LMO_Detailed_Industry == 'Food services and drinking places'].groupby('SYEAR').agg({'Employment':sum})\n",
    "total_emp['Services and Exchange'] = total_emp['Other retail'] + total_emp['Food']\n",
    "total_emp = total_emp.rename(columns={'Employment':'Total_employment'})\n",
    "total_emp.plot(use_index= True, y=total_emp.columns, kind=\"bar\") #Horizontal bars\n",
    "#total_emp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b1e2e730",
   "metadata": {},
   "source": [
    "### Let's switch the interest to the environment, how is foresting evolving employment-wise?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "cbd5dd54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Year long evolution')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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n4+WsUCJEMQUAAAAAyAqUUshq00dM10MXPKR5B82TJP193d911oKztLRpqcPJclcoEVJjoJFiCgAAAADgKEopZL1yX7lu+PQN+sXJv1CJp0RbAlt06UOX6v+W/J9S6ZTT8XJSOBFWg79BaZt2OgoAAAAAoEBRSuWhquIqGRmnYwwoY4zOnna2HrzgQR1ce7BSNqX/fu2/dfmjl6sl1OJ0vJwUSUYopgAAAAAAjqGUykPVxdWaNGySyn3lTkcZcJOHTdZ9592niw+7WJL0asOrOuPeM/SPjf9wOFluiiaj2ty1mRVnAAAAAIAhRymVpzwuj8ZUjNHYirHyurxOxxlQxZ5iXXfCdfr93N+rsqhSbZE2XfHYFfr1y79WPBV3Ol7OiaViavA3UEwBAAAAAIYUpVSeK/OVqb66XrUltXm3pe+Uyado4QULNWPUDEnSLctu0cUPXqxNXZscTpZ7YqmYNvs3K5lOOh0FAAAAAFAgKKUKgDFGtaW1qq+uV5m3zOk4A2pc5TjdcdYd+uqsr8rIaPm25Trj3jP0yAePOB0t58RTcTX4GyimAAAAAABDwnAsfLfZs2fbJUuWOB1jSITiIW0LbVMinXA6yoB6teFVfeeZ72hbaJsk6YyDz9C1J1w7pLO1Fm9YrFuW3aIGf4PGVY7T5TMu1wn1JwzZ6w8En9un8ZXj5Xa5nY4CAAAAAMhxxpil1trZu7qNlVIFqGdLX01JTV5t6Ttm3DF65MJHdFL9SZKkRz54RGctOEvvNr87JK+/eMNiXf/i9WoJtaiqqEotoRZd/+L1Wrxh8ZC8/kDpWTHFjCkAAAAAwGCilCpQxhgNLx2uCVUTVOwpdjrOgKkpqdEfPvsH/cfx/yGf26dNXZt00YMX6c9v/Vlpmx7U175l2S3yuXwq8ZbIGKMSb4l8Lp9uWXbLoL7uYOgZfj7Y3zMAAAAAQOGilCpwRZ4iTaiaoLrSOrlMfvznYIzRJYdfovvPu1+Th01WMp3UDa/coCsevaJ3a99gaPA37FTwFXuK1ehvHLTXHEwUUwAAAACAwZQfLQT227CSYZpYNVGl3lKnowyYqcOn6sHzH9QFh14gSXp588s6494zBm073bjKcYomo9tdiyajGls5dlBebzAs3rBY8xfO15zb5mj+wvl6es3TavQ3UkwBAAAAAAYcpRR6ed1ejascp1Hlo+Q2+THkusRboutPul6/O+13qiyqVHukXVc+fqV+9uLPFEvGBvS1Lp9xueLpuCKJiKy1iiQiiqfjunzG5QP6OoNldzOxnlrzlLYEtohDEQAAAAAAA4lSCjupLKpUfXW9KnwVTkcZMKceeKoeufARzRo9S5J0x7t36Nz7z9WHbR8O2GucUH+Crj3+WtWV1ckf86uurE7XHn9tzpy+t6eZWOFEWI2BRoopAAAAAMCAMfwls9vs2bPtkiVLnI6RdULxkJpDzUqmk05HGRCpdEp/XPpH3fTGTUrZlHxun777ie/q84d9Xsbkz0mE+2LObXNUVVS13ffBWit/zK9nL3tWklTmLdOYijEF/70CAAAAAPSPMWaptXb2rm5jpRT2qMxXpvrqetWU1Mgo94sIt8utr33sa7r7nLs1rnKc4qm4fvriT/WVx7+itnCb0/Ec1Z+ZWKFESE3BJlZMAQAAAAD2G6UUPpLLuDS8dLgmDZuUN1v6jhx1pB658BGdcfAZkqTFGxdr3j3ztHjj4AxBzwX9nYkVjAe1NbiVYgoAAAAAsF/YvpfB9r3+iyaj2hbattOqmv21eMNi3bLsFjX4GzSucpwun3H5kMxjevzDx3XdC9cpGA9Kki49/FJdc+w1KvIUDfprZ5ue34NGf6PGVo7d4+9BmbdMoytGy2XotgEAAAAAu7an7XuUUhmUUnsvEAuoNdyqRDqx38/Vc/Kbz+VTsadY0WRU8XR8yAaFN/gbdM0z1+itprckSQfVHqTfnPIbHVR70KC/di4r9hRrbMVYuV35cVojAAAAAGBgMVMKg6KiqEL11fUaXjp8v1fL7Onkt6EwrnKc7jjrDl191NVyG7c+bPtQ59x3jm5/53a2qe1BNBnVpq5NSqT2v5gEAAAAABQWSinsF2OMakpqNKl6kqqKqvb5eRr8DSr2FG93rdhTrEZ/4/5G7DePy6OrjrpKd519V+8Q9J//4+e64rErtC20bchy5JpEOqFNXZsGfDsnAAAAACC/UUphQLhdbo0sH6kJVRNU5N77WUz9OfltqMwYPUOPXPiIzpp6liTppU0vad498/TM2meGPEuuSNmUGvwNCsVDTkcBAAAAAOQISikMqGJPsSZWT1Rdad1ebenr78lvQ6XcV65ffuqXuvG0G1VVVKXOaKeuWnSVfvjcDylediNt09oS2KKuaJfTUQAAAAAAOYBSCoNiWMkw1VfXq9xX3q/7n1B/gq49/lrVldXJH/OrrqxuyIac78ncA+fqsYse0zHjjpEkPfDeAzpzwZl6e+vbjubKVlZWzaFmtYXbnI4CAAAAAMhynL6XkQ+n7y1avUg3vHKD1neu16TqSbrm2Gs0d8pcp2MpFA9pW2jbgJzS55S0Tev2d27Xf73yX0qkE3Ibt772sa/pq7O/Ko/L43S8rFRVVKWR5SOdjgEAAAAAcBCn7xWARasX6apFV6kp0KSa4ho1BZp01aKrtGj1IqejqcxXpvrqetWU1MjIOB1nn7iMS1848gt68PwHdVDNQUrZlH7/xu/1+Qc/r01dm5yOl5W6Yl1q9DdyeiEAAAAAYJcopfLEDa/cIJ/LpzJfmYwxKvOVyefy6YZXbnA6mqTuU/qGlw7XhKoJKvGUOB1nnx08/GA9cP4D+sIRX5Akvd38ts649wzd/979lC+7EEqEtNm/Wal0yukoAAAAAIAsQymVJ9Z3rlept3S7a6XeUm3o3OBMoN0o8hRpfNV4jSwbuVeD0LNJkadI3//k93XrGbdqRNkIhRNh/ei5H+lfnvgXtYZbnY6XdaLJqDb7NyuRyt3tmwAAAACAgTdorYAxZrwx5nljzCpjzEpjzNcz139sjGk0xryd+fhMn8d83xizxhjzgTHm1D7XZxljlmdu+50xxmSuFxljFmSuv26Mqe/zmMuMMaszH5cN1vvMFpOqJymcCG93LZwIq7663plAH6GquEr11fU7FWm55Njxx+qxix7T3AO753Y9v+F5zbtnnp5d/6zDybJPPBXXZv9mxZIxp6MAAAAAALLEYC5VSUr6lrV2mqSjJf2rMeaQzG3/ba09MvPxpCRlbrtQ0qGSTpP0v8YYd+b+f5B0paQpmY/TMtcvl9RhrT1Q0n9L+lXmuWokXSfp45KOknSdMWbYIL5Xx11z7DWKp+MKxUOy1ioUDymejuuaY69xOtpueVwejascl9OrpqqLq/Xfp/63/uvT/6UKX4XaI+362hNf0w+f+6GC8aDT8bJKMp3UZv/mncpTAAAAAEBhGrQmwFrbZK19K/N5QNIqSWP38JAzJN1rrY1Za9dLWiPpKGPMaEmV1tpXbffQntslndnnMbdlPn9A0smZVVSnSnrGWtture2Q9Iz+WWTlpblT5uqmuTdpdMVodUQ7NLpitG6ae1NWnL73UXpWTZV5y5yOsk+MMZp38Dw9dtFjOnrc0ZKkB957QGfce4aWbMntEx0HWtqm1ehvVCAWcDoKAAAAAMBhQ7I8JbOtboak1zOXrjLGvGuM+UufFUxjJW3u87CGzLWxmc93vL7dY6y1SUldkmr38Fw75rrSGLPEGLOkpaVl399glpg7Za6eu+w5rfv6Oj132XM5UUj18Lg8Gls5VqPKR8ndu0Aut4yuGK1bz7hVP/jkD+Rz+9Tgb9AlD12i37zyG8VTcafjZQ0rq6ZgkzoiHU5HAQAAAAA4aNBLKWNMuaQHJX3DWutX91a8yZKOlNQk6Tc9d93Fw+0eru/rY/55wdqbrbWzrbWz6+rq9vQ2MEQqiyo1sXqiyn3lTkfZJy7j0mVHXKaFFyzUIXWHyMrq5rdu1vn3n68P2z50Ol5WaQm3qCWU+2UwAAAAAGDfDGopZYzxqruQusta+5AkWWubrbUpa21a0p/UPfNJ6l7NNL7Pw8dJ2pK5Pm4X17d7jDHGI6lKUvsengs5wOPyaEzFGI0uH52zq6YOrDlQC85doK/O/qpcxqVVrat0zn3n6C/L/qJUOuV0vKzREe1QU6BJ3TtzAQAAAACFZDBP3zOSbpG0ylr7//pcH93nbmdJWpH5/FFJF2ZO1Juk7oHmb1hrmyQFjDFHZ55zvqRH+jym52S9cyU9l5k79bSkU4wxwzLbA0/JXEMOqSiqyOlZUz63T988+pu66+y7NKFqguKpuH718q902cOXaXPX5o9+ggIRiAfUGGhU2qadjgIAAAAAGEKDuVLqE5IulTTHGPN25uMzkn5tjFlujHlX0kmSvilJ1tqVku6T9J6kpyT9q7W2Z0nJv0j6s7qHn6+VtChz/RZJtcaYNZL+XdL3Ms/VLumnkt7MfFyfuYYc43a5NbZyrEaWjZTZ5a7M7Ddz9Ew9fMHDuuDQCyRJb255U6ffe7oWrFjACqGMcCKsTV2bmL0FAAAAAAXE8JfibrNnz7ZLlnBSWjaLp+LaGtyqaDLqdJR9tnjjYv3w2R+qJdw9S+n4icfrZyf9TCPLRzqcLDu4jEsjy0aqoqjC6SgAAAAAgAFgjFlqrZ29q9uG5PQ9YCD43D6NrxyvmpIap6PssxMmnqDHL35cn5vyOUnSixtf1Lx75umJD59wOFl2SNu0moJN2hbaxioyAAAAAMhzlFLIKcYYDS8drvGV4+V1eZ2Os0+qi6v1m1N/oxtPu1HVxdXqinXp3//27/rGU99Qe4RdppLUGe3UZv9mJdNJp6MAAAAAAAYJpRRyUom3RBOrJ6qyqNLpKPts7oFz9fhFj+uk+pMkSYvWLNK8e+bp+fXPO5wsO0STUW3s3KhwIux0FOyFRasXac5tczTpt5M057Y5WrR60Uc/CAAAAEBBYqZUBjOlclcwHlRzsFmp3rn4ucVaqwdXPaj//Md/KpQISZLOmXaOvn/c95mtlFFbUqva0lqnY+AjLFq9SFctuko+l0+l3lKFE2HF03HdNPcmzZ0y1+l4AAAAABzATCnktXJfueqr61VVVOV0lH1ijNG5h5yrRy96VEeNPUqS9OCqBzXvnnl6ZfMrDqfLDm2RNjX6G5VK52bxWChueOUG+Vw+lfnKZIxRma9MPpdPN7xyg9PRAAAAAGQhSinkBbfLrZHlIzWxaqJKvaVOx9kn4yrH6bYzb9MPP/lDFXuK1RRs0hcf+aKue+E6heIhp+M5LpQIaVPXppw+fTHfre9cv9P//kq9pdrQucGZQAAAAACyGqUU8kqRp0jjKsdpTMWYnByE7jIuzT9ivh6+4GHNGDVDknTvins17555er3hdYfTOS+RTmhz12Z1RbucjoJdmFQ9aacZYOFEWPXV9c4EAgAAAJDVKKWQl3q29NWV1sllcu8/80nDJumus+/Sd479jnxunxoDjZr/8Hz97MWfFfzgbyur5lCzmoPNYiZedrnm2GsUT8cViodkrVUoHlI8Hdc1x17jdDQAAAAAWSj3/rYO9JMxRsNKhmlS9SRVF1c7HWevuV1uXT7zcj18wcM6bMRhkqQ73r1DZ957ppZsYSh/V6xLm/2blUwnnY6CjLlT5uqmuTdpdMVodUQ7NLpiNEPOAQAAAOwWp+9lcPpe/oun4toW2paTK42S6aT+suwv+t3rv1MinZCR0ReO/IK+cfQ3VOwpdjqeo9zGrdEVo3N2lhgAAAAA5DNO3wMk+dw+jascp9Hlo+U2bqfj7BWPy6MrZ12phy54SIfWHSorq1vfvlVn3numljUtczqeo1I2pQZ/g9oj7U5HAQAAAADsBUopFJyKogrVV9ersqjS6Sh77aDag7Tg3AW6+qir5XF5tL5zvS568CL96qVfFfypdK3hVm0JbFHapp2OAgAAAADoB0opFCS3y61R5aM0tmKsPC6P03H2itft1VVHXaUHzntAU4dPlZXVX97+i86454yCnzUVjAe1qWuT4qm401EAAAAAAB+BUgoFrcxXpvrq+pwchD6tbpoeOO8BXX3U1fK6vNrQtUGXPHSJ/vMf/6lIIuJ0PMfEU3Ft6tqkQCzgdBQAAAAAwB5QSqHguYxLI8pGaHzlePncPqfj7JXeVVPnP9A7a+q2d27T6feerjcb33Q6nmPSNq2mYJNaQi1ORwEAAAAA7AalFJBR4i3RxKqJqimpkZFxOs5emTp8qhacu0DfOPob8rq82tS1SZcsvEQ/XfxTheIhp+M5piPaoQZ/g1LplNNRAAAAAAA7oJQC+jDGaHjpcE2omqBiT7HTcfaK1+3Vv8z+Fz10wUOaPmK6JOnO5Xfq9HtP12sNrzmczjnhRFgbuzYW/CB4AAAAAMg2lFLALhR5ijShaoJGlY+S27idjrNXek7o+9Yx35LX5VWDv0GXPXyZrnvhOgXjQafjOSKZTmpz12Z1RbucjgIAAAAAyKCUAvagsqhSk4ZN0rDiYTm1pc/j8ujKWVfq4Qsf1uEjD5ck3bviXn3u7s9p8cbFDqdzhpVVc6hZW4NbZa11Og4AAAAAFDxKKeAjuIxLdWV1mlg9UaXeUqfj7JUDaw7UPefco+8c+x0VuYvUFGzSlY9dqe888x11RDqcjucIf8yvTV2blEglnI4CAAAAAAWNUgroJ5/bp3GV4zSmYoy8Lq/TcfrN4/Lo8pmX69GLHtXHxnxMkvTIB4/os3d/Vk+tecrhdM6IpWLa1LVJ4UTY6SgAAAAAULAopYC9VO4rV311vWpLanNqS199db1uP+t2/fjEH6vUW6q2SJu+/tTXdfWTV6sl1OJ0vCGXsik1+BvUHml3OgoAAAAAFCRKKWAfGGNUW1qrScMmqcJX4XScfnMZly6afpGeuPgJfXLCJyVJf1v3N3327s/q4fcfLshZS63hVjX4G5RMJ52OAgAAAAAFhVIK2A8el0ejK0ZrXOU4+dw+p+P025iKMfrTvD/pV5/6laqKqtQV69J3//5dffmxL2tLYIvT8YZcOBHWhs4N8sf8TkcBAAAAgIJBKQUMgFJvqSZWTdTw0uFymdz4n5UxRmdOPVNPXPyETp18qiTpH5v+oc/e/Vnd+e6dSqVTDiccWmmb1tbgVjUFmgruvQMAAACAE3Ljb89ADjDGqKakRvXV9Tm1pa+urE6/m/s7/e6032l46XCFE2H99MWf6vMPfV5r2tc4HW/IBeIBbezaqFA85HQUAAAAAMhrlFLAAMvVLX2nHniqnrj4CZ0z7RxJ0rKty3TmvWfqpjduUjwVdzjd0Eqmk2oMNKo52Ky0TTsdBwAAAADyEqUUMEhycUtfdXG1/vPk/9Rfz/irxleOVyKd0O/f+L3OWnCWljUtczrekOuKdWlj50ZFEhGnowAAAABA3smNvykDOSpXt/QdM/4YPXbRY7p8xuVyGZfWtK/RRQ9epJ+9+DMF40Gn4w2pRDqhzf7Nagm1FOTphAAAAAAwWCilgCHQs6VvbMVYeV1ep+P0S4m3RN/5xHf0wHkPaNrwabKyuuPdO/S5uz+nxRsWOx1vyHVEO7Spa5NiyZjTUQAAAAAgL1BKAUOozFem+up61ZTUyMg4HadfDh1xqO4/7359+9hvq8hdpKZgk658/Ep96+lvqTXc6nS8IRVLxbSpa5M6Ih1ORwEAAACAnEcpBQwxY4yGlw7XhKoJKvYUOx2nX7xur74888t69KJHddTYoyRJj69+XJ+56zN64L0HCmpbm5VVS7hFDf4GJdNJp+MAAAAAQM6ilAIcUuQp0oSqCRpZNjJnBqHXV9fr9jNv18/m/ExVRVXqinXph8/9UPMfnq/1HeudjjekwomwNnZuVCAWcDoKAAAAAOSk3PibMJDHqoqrcmoQujFG5x1ynp78/JP63JTPSZLeaHxDp997uv7nzf9RPBV3OOHQSdmUmoJN2hrcqrRNOx0HAAAAAHIKpRSQBXJxEPrw0uH6zam/0Z/m/UljK8Yqnorrd6//TmctOEtLm5Y6HW9I+WN+bezcqEgi4nQUAAAAAMgZlFJAFsnFQejHTzxej1/8uL4040tyG7fWtK/RxQ9erGufv1b+mN/peEMmkU5os3+zWsOtBTVjCwAAAAD2Vb9KKWPMr/pzDcD+y8VB6KXeUn33E9/VA+c/oEPrDpUkLVi5QJ+56zNatGZRQZU07ZF2bfZvViKVcDoKAAAAAGS1/q6U+vQurs0dyCAAtpeLg9APqTtE9513n75/3PdV6i1VS7hF33jqG/rK419Rg7/B6XhDJpqMamMXQ9ABAAAAYE/2+DddY8y/GGOWSzrYGPNun4/1kt4dmohAYasqrtKk6kk5Mwjd4/LoC0d+QY9f9LhOqj9JkrR442J99u7P6ualNxfMCqK0TTMEHQAAAAD2wOxpW40xpkrSMEm/kPS9PjcFrLXtg5xtSM2ePdsuWbLE6RjAHoUTYTUHm5VI50axY63V39b+TT/7x8+0LbRNknRQzUH6yUk/0czRMx1ON3R8bp9Gl49WkafI6SgAAAAAMKSMMUuttbN3eVt/Z70YY9ySRkry9Fyz1m4akIRZgFIKucJaq7ZImzoiHbLKjVlNwXhQN752o+5aflfvqqELDr1A3zrmW6oqrnI43dAwMqorq1N1cbXTUQAAAABgyOx3KWWMuUrSjyU1S+rZh2KttYcPVEinUUoh18RTcW0NblU0GXU6Sr+t2LZC1z5/rVa2rJQk1ZbU6nvHfU/zDponY3LjtMH9VeYt06jyUXK73E5HAQAAAIBBNxCl1BpJH7fWtg10uGxBKYVc1R5pV1u4LWdWTaXSKd21/C7d+NqNCiVCkqRjxx+r6064TvXV9c6GGyIel0ejykep1Fu6022LVi/SDa/coPWd6zWpepKuOfYazZ3CuRIAAAAActOeSqn+Hum1WVLXwEUCMFBqSmo0oWqCity5Ma/I7XJr/hHztejzi3Tq5FMlSa9sfkXz7pmnm964SbFkzOGEgy+ZTqrB36DWcKv6/sPAotWLdNWiq9QUaFJNcY2aAk26atFVWrR6kYNpAQAAAGBw9Hel1C2SDpb0hKTevzFaa//f4EUbWqyUQq6z1qo90q72SHvOrJqSpBc2vKDrF1+vxkCjJGli1URde8K1Om7CcQ4nGxo+t091pXUq85Vpzm1z1BRoUpmvrPf2UDyk0RWj9dxlzzmYEgAAAAD2zUCslNok6RlJPkkVfT4AZAljjGpLazW+arx8bp/TcfrtxPoT9fjFj+vKmVfK4/JoY9dGXf7o5fr6U19Xc7DZ6XiDLp6KqzHQqAZ/g9Z1rNtpS1+pt1QbOjc4Ew4AAAAABlG/T9+TJGNMmbU2NIh5HMNKKeQTa61aw63qiHY4HWWvrGlfo5+88BO9seUNSd2FzL8d9W+69IhL5XF5PuLRuW/+wvlqC7epsqiyd/A7K6UAAAAA5LL9XilljDnGGPOepFWZr48wxvzvAGYEMICMMaorq9P4yvHyurxOx+m3A2sO1O1n3a5ffepXqi2pVTgR1i9f/qXOXnC2ljYtdTreoLt8xuWKpqLqjHYqkUooGAsqno7rmmOvcToaAAAAAAy4/m7fu1HSqZLaJMla+46k4wcpE4ABUuIt0cTqiaournY6Sr8ZY3Tm1DO16POLdPFhF8vI6IO2D3TxgxfrB8/+QO2RdqcjDpoT6k/Qtcdfq7qyOrVH2jWsZJj+69P/xel7AAAAAPJSfwedv26t/bgxZpm1dkbm2jvW2iMGPeEQYfse8l0kEVFzqFnxVNzpKHvl3eZ39eMXfqyVLSslSdVF1frWsd/SuYecK5fpb6+e28q8ZRpRNkJed+6segMAAAAAaWAGnW82xhwryRpjfMaYbyuzlQ9Abijxlmhi1UQNLx0uI+N0nH47fOThuv+8+3XtCdeqwlehzlin/uP5/9AFD1yg5c3LnY43JEKJkDZ0blBbuE17MwcQAAAAALJZf1dKDZf0W0mfkmQk/U3S1621bYMbb+iwUgqFJJ6Ka1tom8KJsNNR9kpruFW/fvnXeuSDRyRJRkbnH3q+vnn0NzWsZJjD6YaGz+3TiLIRO53SBwAAAADZaE8rpfbq9L18RimFQuSP+dUSalHKppyOsleWbFminyz+iT5s+1CSVF1crW8f822dc8g5BbOlr8JXobqyuoI4lRAAAABA7trvUsoYM0nS1ZLqJfX+Dchae/oAZXQcpRQKVSqdUku4Rf6Y3+koeyWZTuqu5Xfpd6//TsF4UFL3Vr9rj79Wh408zOF0Q8NlXKotqS2YVWIAAAAAcs9AlFLvSLpF0nJJ6Z7r1trFAxXSaZRSKHThRFjNwWYl0gmno+yVllCLbnjlhu229F0w/QJ98+hv5tSpg/ujyF2kkeUjVewpdjoKAAAAAGxnIEqp1621Hx/wZFmEUgqQrLXqiHaoPdKutE1/9AOyyJuNb+r6F6/fbkvft44prFP6qoqqNLx0uNwut9NRAAAAAEDSwJRSF0uaou4B57Ge69batwYqpNMopYB/SqaTagu3qSvW5XSUvdKzpe+3r/1WoURIkjR9xHRde/y1OmLUEQ6nGxpu41ZdWZ0qiyqdjgIAAAAAA1JK/ULSpZLW6p/b96y1ds6ApXQYpRSws1gypm2hbYokI05H2SvbQtt0wys36NEPHu29dvbUs/WtY7+l4aXDHUw2dEo8JRpZPlI+t8/pKAAAAAAK2ECUUu9LOtxaGx/ocNmCUgrYvWA8qJZQS87Nm1ratFQ/XfxTrWpdJUkq95Xr6qOu1ucP+7y8bq/D6QafkdGwkmGqLamVMcbpOAAAAAAK0J5Kqf4OWnlHUvWAJQKQU8p95aqvrtfw0uE5NZ9p1uhZevD8B/XjE3+s6qJqBeNB/eKlX+jMBWfq1c2vOh1v0FlZtUfataFzg0LxkNNxAAAAAGA7/V0p9YKkwyW9qe1nSp0+aMmGGCulgP5JpVNqDbfm3LypjkiHfvv6b7Vg5YLeIe6nTj5V3zvuexpTMcbhdEOj3FeuEWUj5HF5nI4CAAAAoEAMxPa9E3Z13Vq7eD+zZQ1KKWDvRBIRNYeaFU/l1q7eVS2r9NMXf6qlTUslScWeYn155pd1xcwrVOwpdjjd4HMZl2pLalVdXM2WPgAAAACDbiBKqask3WWt7RjocNmCUgrYe9ZatUXa1BHpkNVH/39JtrDW6rEPH9OvX/61WsItkqSxFWP1nU98R6dOPrUgyhqf26fhpcNV7it3OgoAAACAPDYQM6VGSXrTGHOfMeY0Uwh/YwPwkYwxGl46XBOqJqjIXeR0nH4zxuj0g0/XU5c8pStmXiGvy6vGQKO+/tTXNf/h+Xq/9X2nIw66eCquLYEt2ti5kXlTAAAAABzRr5VSkpQpok6R9EVJsyXdJ+kWa+3awYs3dFgpBewfa606oh1qC7fl1KopSdrQuUG/fOmXen7D85K6t7idf+j5+vrHv66akhqH0w2NYk+xhpcOV6m31OkoAAAAAPLIQKyUku1ur7ZmPpKShkl6wBjz6wFJCSCnGWNUU1KjidUTVeIpcTrOXqmvrtf/fe7/9Od5f9bkYZOVtmndu+JenXrnqbr9nduVSCWcjjjoosmoGvwN2ty1WeFE2Ok4AAAAAApAf2dK/ZukyyS1SvqzpIettQljjEvSamvt5MGNOfhYKQUMrM5op1rDrb0n3eWKRCqhu1fcrd+//nsF4gFJ0uRhk/WDT/5Ax004zuF0Q6fUW6raklqVeHOrYAQAAACQXQZi0Pn16t6qt3EXt02z1q7a/5jOopQCBl4ynVRzsFmhRO7NLGqPtOvG127UfSvv692OOGfSHH33E99VfXW9s+GGUJm3TMNLh6vIkzszwwAAAABkj/0upTJPcoSkT2a+/Ie19p0BypcVKKWAwROMB7UttE3JdNLpKHttVcsq/fwfP9ebW96UJHldXl1y+CX62se+psqiSofTDQ0jo+riatWW1spl+r3rGwAAAAD2f6ZUZvveXZJGZD7uNMZcPXARAeSzcl+56qvrNax4mIxy6/DOaXXTdMdZd+jG027U2IqxSqQTuvXtW3XKHafo7uV352TRtresuofYb+jcIH/M73QcAAAAAHmiv9v33pV0jLU2lPm6TNKr1trDBznfkGGlFDA0YsmYtoW2KZKMOB1lr8WSMf317b/q/5b+X+8w8Ck1U/S9475XUPOmSjwlGlE2gi19AAAAAD7SQJy+ZySl+nydylwDgL1S5CnS+KrxGlk2Um7jdjrOXinyFOkrs7+ipy95WudMO0dGRqvbV+vyRy/XVx77itZ2rHU64pCIJCPa2LVR20Lbcm6QPQAAAIDs0d+VUv+u7tP3FmYunSnpr9baGwct2RBjpRQw9FLplFrDreqKdTkdZZ+81/KefvGPX+iNLW9Ikjwujy6afpGuOuoqVRdXOxtuiLiNW3VldQUzXwsAAADA3hmoQeczJR2n7hVSL1prlw1cROdRSgHOiSQi2hbaplgq5nSUvWat1TPrntGvX/61Nvs3S5Kqiqr0r0f9qy6afpF8bp/DCYdGiadEdWV1KvYUOx0FAAAAQBbZ51LKGFOzpye21rbvZ7asQSkFOK8z2qm2cJtSNvXRd84y8VRct79zu/73zf9VKBGSJNVX1euaT1yjkyedLGMKY8dzha9CtaW1BVPGAQAAANiz/Sml1kuy2vX8KGutPWBgIjqPUgrIDql0Sm2RNnVFu2TVv5Wc2aQt3Kbfvv5b3f/e/b3zlj425mP67ie+q8NGHuZwuqFhZFRZVKna0lp5XB6n4wAAAABw0IBs38t3lFJAdomn4toW2tZ7yl2uWd22Wr9+5dd6ceOLvddOP/h0/fvR/67RFaMdTDZ0jIyGlQxTTUmNXKa/52oAAAAAyCcDNVPqbHXPlLKS/mGtfXjAEmYBSikgOwXjQbWEWpRIJ5yOsk9e3vSyfvnyL/Vh24eSpCJ3kb545Bf15VlfVrmv3OF0Q8Nt3KopqVF1cXXBbGMEAAAA0G2/SyljzP9KOlDSPZlLF0haa6391wFL6TBKKSB7WWvVEe1Qe6S9d0tcLkmlU3ro/Yf029d+q5ZwiySptqRW//bxf9O5h5xbMFvcPC6PhpcO56Q+AAAAoIAMRCm1UtJ0m7mzMcYlabm19tABTeogSikg+yXTSbWGW+WP+Z2Osk9C8ZBuWXaLbll2i6LJqCTpwJoD9e1jvq0T608smFVEPrdPNSU1lFMAAABAAdhTKdXfIR8fSJrQ5+vxkt7d32AAsDc8Lo9GlY/SxKqJKvWWOh1nr5X5yvRvH/83/e2Sv+nsqWfLyGhN+xp99Ymvav7D87W8ebnTEYdEPBXX1uBWre9Y3z3QntmGAAAAQEHq70qpxZI+JumNzKWPSXpVUliSrLWnD1bAocJKKSD3hBNhtYRaFEvFnI6yT1a1rNINr9yglze/3Hvtc1M+p28c8w2NrxzvYLKh5XF5VFNSo6qiqoJZLQYAAAAUioHYvnfCnm631i7ex2xZg1IKyF3+mF+t4VYl00mno+yTlza9pF+//Gt90PaBJMnr8uqSwy/RV2d/VdXF1c6GG0Iel0fDiocxEB0AAADIIwNy+l7miSol9U7ktda273+87EApBeS2fBiG/ugHj+rG12/U1uBWSVJlUaW+OuuruuTwS1TkKXI44dBxG7eGlXSXUy7T313mAAAAALLRQKyUulLSTyVFJKUlGUnWWnvAQAZ1EqUUkB9S6ZTaI+3qjHbKKvdmFUWTUd3+zu3649I/KhgPSpLGVIzRN47+huYdNK+gShq3cau6uFrDSoYV1PsGAAAA8slAlFKrJR1jrW0d6HDZglIKyC+JVEJtkbacPamvPdKuPyz5g+5Zfo8S6YQkaerwqfrWMd/SJyd8sqC2t7mMq7ucKh4mt8vtdBwAAAAAe2EgSqmnJJ1trQ0PdLhsQSkF5KdYMqa2SFvvqqNcs6lrk37z6m/01Jqneq99fOzH9e1jv63DRx7uYLKhRzkFAAAA5J6BKKVmSLpV0uuSeo+5stb+20CFdBqlFJDfosmo2sJtCiVCTkfZJ+82v6v/euW/9Hrj673XTp18qr559Dc1adgkB5MNPZdxqaqoSjUlNZRTAAAAQJbbUynV3yEdf5T0nKTXJC3t87GnFx1vjHneGLPKGLPSGPP1zPUaY8wzxpjVmV+H9XnM940xa4wxHxhjTu1zfZYxZnnmtt+ZzL4VY0yRMWZB5vrrxpj6Po+5LPMaq40xl/XzfQLIU8WeYo2tHKvxleNV4ilxOs5eO3zk4brtzNv053l/1rTh0yRJT699Wp+9+7O67oXrtC20zeGEQydt0+qIdmhdxzq1hFpy9tRFAAAAoND1d6XUK9baY/fqiY0ZLWm0tfYtY0yFukusMyV9QVK7tfaXxpjvSRpmrf2uMeYQSfdIOkrSGEl/l3SQtTZljHlD0tfVXYo9Kel31tpFxpivSTrcWvtVY8yFks6y1l5gjKmRtETSbEk289qzrLUdu8vLSimgsITiIbVF2hRNRp2OstfSNq0nPnxCN75+oxr8DZKkEk+JLjvyMl0x4wpVFFU4nHBoGRlVFlWquri6oE4pBAAAAHLBQKyUet4Yc6UxZnRmpVNNpvjZLWttk7X2rcznAUmrJI2VdIak2zJ3u03dRZUy1++11sasteslrZF0VKbcqrTWvmq7G7Tbd3hMz3M9IOnkzCqqUyU9Y61tzxRRz0g6rZ/vFUABKPOVaULVBI2pGCOf2+d0nL3iMi7NO3ieFn1+kX70yR+ppqRGkWRE/7fk//SpOz6lW5fdqlgy9tFPlCesrLpiXdrYtVEN/oacnR8GAAAAFJr+llIXS/q+pFf0z617/V5WlNlWN0PdM6lGWmubpO7iStKIzN3GStrc52ENmWtjM5/veH27x1hrk5K6JNXu4bl2zHWlMWaJMWZJS0tLf98OgDxS7ivXxKqJGlE2Qm6TW/OJfG6fLj3iUj1z6TO66mNXqdRbqs5op3758i91yp2n6P6V9xfc1rZwIqwtgS1a37FeHZEOpW3a6UgAAAAAdqNfpZS1dtIuPg7oz2ONMeWSHpT0DWvtns5m39X55nYP1/f1Mf+8YO3N1trZ1trZdXV1e4gGIJ8ZY1RdXK366npVF1fL7PL/QrJXua9cV3/8aj1z6TO69PBL5XV5tTW4VT96/kf67N2f1ZOrnyy4ciaRTqgl3KJ1Heu0LbRNiVTC6UgAAAAAdrDHUsoY850+n5+3w23/+VFPbozxqruQusta+1DmcnNmS17P3Kme6bwNksb3efg4SVsy18ft4vp2jzHGeCRVSWrfw3MBwG65XW6NKBuhidUTVeYtczrOXhteOlw/Ov5HeuqSp3TW1LNkZLShc4O++fQ3dc595+jFjS+qP3ME80naptUZ7dT6zvVq9DcqnAg7HQkAAABAxketlLqwz+ff3+G2Pc5oysx2ukXSKmvt/+tz06OSek7Du0zSI32uX5g5UW+SpCmS3shs8QsYY47OPOf8HR7T81znSnouM3fqaUmnGGOGZU73OyVzDQA+ks/t09jKsRpbMTbn5k1J0rjKcfrlp36pxy56TJ864FOSpPda3tOXH/uyLl14qd5qesvhhM4IJUJq8DdoQ+cGdUY7C271GIbGotWLNOe2OZr020mac9scLVq9yOlIAAAAWWuPp+8ZY5ZZa2fs+Pmuvt7FY4+T9A9JyyX1/OT/A3XPlbpP0gRJmySdZ61tzzzmh5K+JCmp7u1+izLXZ0v6q6QSSYskXW2ttcaYYkl3qHteVbukC6216zKP+VLm9STp59baW/f0jeD0PQC7Ym33EO22cJtSNuV0nH3yztZ39P9e+396reG13msn1Z+kbxz9DU0dPtXBZM5yGZeqiqpUXVwtr9vrdBzkgUWrF+mqRVfJ5/Kp1FuqcCKseDqum+bepLlT5jodDwAAwBF7On3vo0qpt6y1M3f8fFdf5zpKKQB7krZptYXb1BntlN15RF1OeGXzK/p/r/4/Ld+2vPfaZ6Z8RlcddZUmD5vsYDLnlXnLVF1crTJf7m3bRPaYc9scNQWatvvvKBQPaXTFaD132XMOJgMAAHDO/pRSKUkhdQ8OL5HUM4zDSCq21ubNPy1TSgHoj2Q6qbZwm/wxf06WU9ZaPbPuGd342o1a27FWUveKoTMPPlNfO+prGl85/iOeIb/53D5VF1ersqhSLtPfA2qBbpN+O0k1xTXqnjbQzVqrjmiH1n19nYPJAAAAnLOnUmqPP3Fba93W2kprbYW11pP5vOfrvCmkAOSHoZjl4nF5NLJ8pOqr61Xhqxjw5x9sxhidMvkUPXbRY/r1p3+t8ZXjlbZpPfT+QzrtztN03QvXqTnY7HRMx8RTcW0LbdP6jvVqj7QX3GB47J9J1ZN2GqYfToRVX13vTCAAAIAst8eVUoWElVJAbnNqlkssGVNruFWhRGjQXmMwJVIJLXx/of7nzf/R1uBWSd2rhS6efrGunHWlaktrHU7oLLdxq7a0VlVFVdutfgF2hZlSAAAAO9vn7XuFhFIKyG1Oz3KJJqNqDbfutEoiV8SSMS1YuUB/XPpHtYZbJUml3lLNP3y+vjTjS6oqrnI4obM8Lo9qS2pVWVRJOYU9WrR6kW545QZt6Nyg+up6XXPsNRRSAACgoFFK9QOlFJDbsmWWSzgRVmu4VdFkdMhecyCFE2Hd+e6d+vNbf1ZXrEuSVO4r1xeP/KIuO+IyVRTl3pbFgeRz+1RbUlvw3wcAAACgv/Z5phQA5IpsmeVS6i3VhKoJGlU+Sh6XZ0hfeyCUekt15awr9ez8Z3X1UVerzFumYDyo37/xe825fY7+983/VTAedDqmY+KpuJqCTdrYubGgvw8AAADAQKCUApAXrjn2GsXTcYXiIVlrFYqHFE/Hdc2x1ziSp7KoUvXV9RpWPExGubfdq6KoQlcddZWeu+w5fXXWV1XqLZU/5tdvX/+tTr7tZN289GaF4rk5R2sgxFIxbQls0aauTQrEAgxEBwAAAPYB2/cy2L4H5L5sneUST8XVEmrJ2WHoktQeaddflv1Fd757pyLJiCRpWPEwXTHzCl182MUq9ZY6nNBZHpdH1cXVqiqqktvldjoOAAAAkDWYKdUPlFIABlsoHtK20DYl0gmno+yztnCb/vzWn3XX8rsUS8UkSbUltbpy1pW6cPqFKvYUO5zQWUZGFUUVGlY8TEWeIqfjAAAAAI6jlOoHSikAQ6Fn+Hp7pF1pm3Y6zj7bFtqmP731J9274l7FU3FJUl1pna6YeYUuOPQClXhLHE7ovBJPiYaVDFO5r9zpKAAAAIBjKKX6gVIKwFBKppNqCbUoEA84HWW/NAebdfPSm7Vg5YLeFWDDS4frihlX6MLpF1JOSfK6vKourlZlUSVb+wAAAFBwKKX6gVIKgBOiyahaw607nRyYa5oCTbr5rZt1/8r7e8up2pJaXT7jcl102EUFP3NK+ufWvuri6oLf5ggAAIDCQSnVD5RSAJwUToTVGm5VNBl1Osp+2Rrcqj8t/ZPue+++3m19NSU1+tKML+ni6RerzFfmcMLsUOwpVnVxtSp8FTIm905nBAAAAPqLUqofKKUAZINALKC2SFtvoZOrmoPN+tNbf9J9K+/rHYg+rHhYdzl12MXMWcpwG7cqiypVXVwtr9vrdBwAAABgwFFK9QOlFIBsYa2VP+ZXW6RNyXTS6Tj7ZVtom/781p9174p7e8up6uJqfeHIL+iSwy5RRVGFwwmzR5m3TNXF1awmAwAAQF6hlOoHSikA2cZaq85op9oj7UrZlNNx9ktLqEW3LLtF96y4p3eLYoWvQpcecanmHz5fw0qGOZwwe3hcHlX4KlRRVMHsKQAAAOQ8Sql+oJQCkK3SNq2OSIc6oh1K27TTcfZLa7hVt759q+5efnfvcPdSb6kumn6RvnjkF1VXVudwwuzidXlVUVShyqJK+dw+p+MAAAAAe41Sqh8opQBku1Q6pY5ohzqjnTlfTnVEOnT7u7frjnfuUCAekCQVuYt0/qHn64qZV2hU+SiHE2afIneRKooqVOGrYP4UAAAAcgalVD9QSgHIFflUTgViAd21/C7d+vat6ox2SupeHXT2tLP15Vlf1vjK8c4GzFLFnmJVFVWpsqiS0/sAAACQ1Sil+oFSCkCuyadyKhQPacHKBbpl2S1qDbdK6j6Zbt5B83TlrCs1uWaywwmzk9u4NaxkmKqLq+UyLqfjAAAAADuhlOoHSikAuSqfyqloMqoH3ntAf3rrT9oa3CpJMjL69AGf1pWzrtRhIw9zOGF2chmXqoqqNKxkmDwuj9NxAAAAgF6UUv1AKQUg16XSKbVH2tUZ7ZRVbv9/ezwV1yPvP6I/vfUnbeza2Hv9E+M/oa/M+oqOGnsU29Z2wciosqhSw0qGMRgdAAAAWYFSqh8opQDki2Q6qdZwq/wxv9NR9lsqndLTa5/WH5f+Ue+3vt97/ciRR+ors7+ik+pPopzajXJfuWpKalTsKXY6CgAAAAoYpVQ/UEoByDexZEyt4VaFEiGno+w3a61e3Pii/rDkD1q2dVnv9YNqD9JXZn1Fpx14GtvWdqPUW6rKokqV+8qZOwUAAIAhRynVD5RSAPJVOBFWS6hFsVTM6Sj7zVqrJVuW6P+W/p9e2vRS7/XxleP1pRlf0tnTzmZl0G4YGZX7ylVRVKEybxkrzAAAADAkKKX6gVIKQL4LxAJqDbcqkU44HWVArNi2QjcvvVl/W/u33hlatSW1uvSIS3Xx9ItVVVzlcMLs5TZulfvKVVlUqRJvidNxAAAAkMcopfqBUgpAIbDWqjPaqfZIu1I25XScAbGuY51uWXaLHnn/kd7CrdRbqgsOvUBfOPILGlU+yuGE2c3j8qiyqFIVvgoVeYqcjgMAAIA8QynVD5RSAApJ2qZ7T+pL27TTcQZEc7BZt71zm+5dcW/vHC2vy6t5B83TFTOv0OSayQ4nzH5F7iJVFlWqsqhSbpfb6TgAAADIA5RS/UApBaAQpdKp3nKqZwtcrvPH/Lp3xb267Z3b1Bpu7b0+Z9IcfXnmlzVz9MzdPnbxhsW6ZdktavA3aFzlOF0+43KdUH/CUMTOKkZGpd5SVRVXMX8KAAAA+4VSqh8opQAUsmQ6qbZwm7piXU5HGTCxZEwPv/+wbll2izZ2bey9PmPUDF0x8wqdVH/SdquBFm9YrOtfvF4+l0/FnmJFk1HF03Fde/y1BVlM9XAbtyqKKlRZVMkQeQAAAOw1Sql+oJQCACmeiqst3KZAPOB0lAGTSqf0zLpn9Ke3/qQV21b0Xq+vqtcXZ3xRZ049U8WeYs1fOF8toZbtBn9HEhHVldXp9rNudyJ61vG5fb3b+zwuj9NxAAAAkAMopfqBUgoA/imWjKk13No7mykfWGv1RuMb+suyv+iFjS/0Xh9WPEyXHH6J7l95v2pKarbbqmatlT/m17OXPetA4uxW5C5Sua9c5b5yBqQDAABgtyil+oFSCgB2FklE1BZpUzgRdjrKgFrdtlq3vn2rHv3g0d4T+1zGpXJvuUaUj1CRu7tkYaVU/3hcnt6CqsRTwgwqAAAA9KKU6gdKKQDYvXwtp7aFtunOd+/UPSvukT/m771e4atQha9Cxhhdd8J1BT1Tam+5jEtl3jKV+8pV5iuTy7icjgQAAAAH7amU4idFAMBHKvGWaFzlOE2omqAyb5nTcQbMiLIR+vdj/l0vXPaCfvDJH6i2pFaSFIgHtCW4RT63T6FESMl00uGkuSNt0wrEA2oKNmlt+1o1+BvUEelQIpVwOhoAAACyDCulMlgpBQD9F01G1RZuy6uZU1L3KYRPr3laf3n7L9sNRR9TMUaXHn6pzjvkPFUUVTiYMLf53L7ebX6c5AcAAFAY2L7XD5RSALD38rWcstZqadNS/fXtv+rv6/4uq+4/K0u9pTr3kHM1//D5Gl813uGUuc1t3L1b/Mq8ZcyhAgAAyFOUUv1AKQUA+y4fT+vrsalrk25/53Y9uOrB3plaLuPSpyZ9Sl+Y8QXNHDWTQmU/GRmV+cp6V1ExhwoAACB/UEr1A6UUAOy/UDyklnCL4qm401EGnD/m130r79Md796hrcGtvdenj5iu+UfM19wD58rn9jmYMD8YGZV6S3sLKrfL7XQkAAAA7AdKqX6glAKAgWGtVWe0U22RNqVt2uk4Ay6RSujptU/r1rdv3W7uVF1pnS467CJdeOiFqi2tdTBhfinxlKjcV66Kogp5XB6n4wAAAGAvUUr1A6UUAAysVDql1nCrumJdTkcZFNZavbX1Ld3+zu16Zu0zStmUJMnr8mreQfM0/4j5mlY3zeGU+aXYU9y7gopVaQAAALmBUqofKKUAYHDEkjG1hFt65zHloy2BLbpr+V26f+X925VwHxvzMc0/Yr5OnnQy29AGGCf5AQAA5AZKqX6glAKAwRWMB9USalEinXA6yqAJJ8J69INHdce7d2hN+5re62Mrxuriwy7WuYecq+riaucC5imPy6Myb/eg9FJvKYPnAQAAsgilVD9QSgHA4Mv3eVM9rLV6ZfMruv2d2/XCxhd6rxe5izTv4Hm69PBLNXX4VOcC5jGXcW1XULFCDQAAwFmUUv1AKQUAQyeVTqk90q7OaKes8vvPoQ2dG3Tnu3fqoVUPKZQI9V6fNXqWLjn8En36gE/L6/Y6mDC/lXhKVOYrYw4VAACAQyil+oFSCgCGXiKVUGu4VYF4wOkogy4YD+qR9x/Rncvv1LqOdb3XR5SN0IXTL9T5h5yvurK6/X6dxRsW65Zlt6jB36BxleN0+YzLdUL9Cfv9vPnA6/KqzFemMm8Z2/wAAACGCKVUP1BKAYBzosmoWsOteT0MvYe1Vq81vKY73r1Dz294vncbo9fl1akHnqpLDrtER446cp8Kk8UbFuv6F6+Xz+VTsadY0WRU8XRc1x5/LcXUDoyMSr2lvdv8WK0GAAAwOCil+oFSCgCcF4qH1BJuUTwVdzrKkGjwN+jeFffq/pX3qzPW2Xv9kLpDdNH0i/S5gz6nUm9pv59v/sL5agm1qMRb0nstkoiorqxOt591+0BGzzs+t09l3jKV+cpU4ilhFRUAAMAAoZTqB0opAMgeXdEutUXalEwnnY4yJKLJqJ748AndufxOvdfyXu/1Cl+Fzpx6pi467CJNHjb5I59nzm1zVFVUtV2hYq2VP+bXs5c9OyjZ85HLuFTqLe0tqTwuj9ORAAAAchalVD9QSgFAduk5qa890q6UTTkdZ0hYa/VO8zu6e/ndWrRm0XYrxj4+9uO6+LCLdfKkk3e71YyVUoOjyF2kMl/3HCpWUQEAAOwdSql+oJQCgOyUtml1RjvVEekomHJKktoj7Xpo1UO6Z8U9avA39F6vK63T+Yeer/MPPV+jykdt9xhmSg0+l3H1nuhX5i1jFhUAAMBHoJTqB0opAMhuhVpOpW1aL216SXcvv1uLNy7uHYzuNm6dNOkkXXDoBTpuwnFyGZekf56+1+hv1NjKsZy+N8g40Q8AAGDPKKX6gVIKAHJDoZZTktTob9R9K+/T/e/dr7ZIW+/1sRVjdf6h5+ucaeeorqzOwYSFzcioxFvSO4vK5/Y5HQkAAMBxlFL9QCkFALmlkMupeCquv6/7u+5dca9eb3y997rH5dHJk07WBYdeoGPGH9O7egrOYBUVAAAApVS/UEoBQG5K27TaI+3qjHb2bm0rJOs61um+lfdp4aqF6ox19l6fUDVB5x1yns6Zdo5qS2udCwhJ3auoSr2lKvWWqtxXziwqAABQMCil+oFSCgByWyqdUlukTV3RLlkV3p9tsWRMT699WgtWLtCSLf/888zr8urkA07WeYecp2PHH8vqqSzRs4qqxFOiUm+p3C6305EAAAAGBaVUP1BKAUB+SKQSag23KhAPOB3FMWva12jBygV6+P2H5Y/5e6+PrRircw45R+dMO2enk/vgrCJ3kUq83QVViaeEkgoAAOQNSql+oJQCgPwSS8bUGm5VKBFyOopjosmonlrzlO5/7/7tVk+5jEvHTzhe5x16nk6YeAJbybJQkbuod7tfibeEFW4AACBnUUr1A6UUAOSnSCKilnCLosmo01Ecta5jnR547wEtfH+h2iPtvdfrSut01tSzdN6h52lC1QQHE2JPij3F/yypPCUMTQcAADmDUqofKKUAIL8F40G1hdsUS8WcjuKoeCqu59c/r/veu08vb3p5u/lbR409SudMO0enTj5VJd4SB1NiT4xM71a/Um+pitxFlFQAAOSZtE3nzUppSql+oJQCgMIQiAXUFmlTPBV3OorjGv2NemjVQ3pw1YNqCjb1Xi/3leuzUz6rc6ado8NHHk7hkeVcxtU7ML3UW6oiT5HTkQAAwD6Kp+JqC7cpbdMaWznW6TgDglKqHyilAKCw+GN+tYXblEgnnI7iuFQ6pZc2v6SHVj2kZ9c9u9335MCaA3X21LN1xtQzNLx0uIMp0V9u495uaDolFQAA2a+njOo5rKfUW6pxleMcTjUwKKX6gVIKAAqPtVb+mF/tkXbKqYz2SLse//BxPbjqQb3f+n7vdY/LoxMmnqBzDjlHx084nuHoOcRt3L0D00u9pfK5fU5HAgAAGbFkTO2R9p1OjqaUKjCUUgBQuKy16op1qT3SrmQ66XScrPFey3t68L0H9diHj6kr1tV7vbakVvMOmqezpp2lqcOnOpgQ+8Lj8qjEU6JiT7FKvCXMpAIAwAGxZExtkTYF48Fd3k4pVWAopQAA1lp1RjvVHmlXyqacjpM1YsmYnl3/rB5870G9vHn74ehTh0/VWVPP0ucO+hzb+3KUy7i6C6o+RVW+DFYFACDbfFQZ1YNSqsBQSgEAeqRtWp3RTnVEOiindtAUaNIjHzyihe8v1IbODb3X3cat4ycerzOnnqk5k+awRSzHFbmLVOItUYmnRCXeEnlcHqcjAQCQ03acGfVRKKUKDKUUAGBHaZtWe6RdndFOpW3a6ThZxVqrd5rf0cL3F+rJ1U/KH/P33lZVVKXPTPmMzpp61l6f3rd4w2LdsuwWNfgbNK5ynC6fcblOqD9hMN4C9oLP7esdnF7qLZXb5XY6EgAAOSGZTqo13Lrdz0r9QSlVYCilAAC7k0qn1BZpU1e0a7uta+gWS8b03IbntHDVQr206aXtVpfVV9fr9INP1+kHn67xleP3+DyLNyzW9S9eL5/Lp2JPsaLJqOLpuK49/lqKqSzTU1L1FFWUVAAAbG9/f36klCowlFIAgI+STCfVFm7bbug3ttcSatFjHz6mhe8v1IdtH25328zRM3XGwWfotANPU3Vx9U6Pnb9wvlpCLSrxlvReiyQiqiur0+1n3T7Y0bEf2O4HAEC3gVppTylVYCilAAD9tbczAQqRtVYftH2gRz54RI998Jhawi29t3ldXp1Yf6JOP/h0nVh/Yu/8qTm3zVFVUdV22/2stfLH/Hr2smeH/D1g33ld3u1KKmaMAUDuWLR6kW545Qat71yvSdWTdM2x12julLlOx8p61lp1RDsGbCYppVSBoZQCAOytWDKm9kg75dRHSKVTer3xdT3y/iP627q/KZwI995WWVSpuQfO1byD5ul3r/9OreFWVkrlIY/L01tQFXuKVewpdjoSAGAXFq1epKsWXSWfq3ubdjgRVjwd101zb6KY2o20Tasr2qWOaIeS6eSAPS+lVIGhlAIA7KtEKqH2SLv8MT8zpz5COBHWs+ue1aMfPqqXN7283b8kDisepkQ6oSpflSqLKhVLxZgpladcxtVbTvWUVS7jcjoWABS8ObfNUVOgSWW+st5roXhIoytG67nLnnMwWfZJpVPqiHaoK9o1KKc1F0opxYZ/AAD2k9ft1cjykaotrVVHpENdsS5O69uNUm+p5h08T/MOnqfWcKueWP2EHv3gUa3YtkId0Q5JUjAeVHO4WSPLRuqrs75KIZWH0jatcCK83ao5n9vXW1CVeErkdXsdTAgAhWl953rVFNdsd63UW6oNnRucCZSFkumk2iPtHIAzQFgplcFKKQDAQEmlU+qMdqoz2jko/3KWjzZ0btDjHz6uxz98XOs7129322EjDtPnDvqcPjPlMxpRNsKhhBhqbuPuXknVZ8sfq6kAYHCxUmr34ql499iGWGBIyqhCWSlFKZVBKQUAGGiDNWMgn1lrtap1lR778DE98eETag41995mZHTU2KP0mSmf0SmTT1FNSc0engn5qMhdtF1RxQB1ABhYzJTaWTQZVXukXcF4cEhfl1KqwFBKAQAGS88Jcp3RTsVSMafj5Iy0TWvJliV6/MPH9fSap9UZ6+y9zW3cOmbcMZo7Za4+fcCnVVVc5VxQOKZnNVXfD7fL7XQsAMhpPafvbejcoPrq+oI8fc9aq2A8qM5opyLJiCMZKKUKDKUUAGAohBNhtUfat5ulg48WT8X18qaX9eSaJ/X3dX/f7vvndXl13ITjNHfKXJ086WSV+8odTAqn9Zz0V+QpYtsfAGCvpNIpdcW61BntdHyVO6VUgaGUAgAMpXgqro5IByf27YNoMqoXN76oJ1c/qRc2vLDdv2D63D6dMPEEfWbKZ3TCxBO2m4mBwuVz+1TsKVaRu0hFniIVuYtYUQUA6BVNRtUZ7RyyeVH9QSlVYCilAABOYCj6/gknwnphwwt6cvWTWrxxseKpeO9tRe4iHT/xeJ06+VSdNOkkVlBhOx6XZ6eiihP/AKBwWGsViAfUGe1UNBl1Os5OKKUKDKUUAMBJPXOnOqId2xUr6L9gPKhn1z+rRasX6aVNLymRTvTe5nP7dNyE43TagadpTv0cVRRVOJgU2cplXNuVVD2/GmOcjgYAGCDJdFJd0a6s/wdBSqkCQykFAMgW4URYHZEOhRIhp6PkrEAsoOc2PKen1jyllza9tF3R53V59Ynxn+guqCbNYUg6PpLP7estqXo+Z1UVAOSWcCKsrmiXgvFg1mzR2xNKqQJDKQUAyDbMnRoYwXhQL2x4QU+teUovbnxxuxMQPS6Pjh53tD59wKd18qSTVVdW52BS5JKeVVXFnuLeoeo+t8/pWACAPtI2LX/Mr65oV86dgEwpVWAopQAA2SqbToLJdaF4SIs3LtZTa57S4o2Lt5shYWQ0c/RMnTL5FH3qgE/lzQ+CGDp9t//1zKvyuX1s/wOAIRZPxdUZ7ZQ/5lfapp2Os08opQoMpRQAINtZaxWMB9UR7cjKgZy5JpwI66VNL+lva/+m5zc8r2A8uN3th9Qdok8f8GmdMvkUTR42mWIB+8TI7DSjqshTJJdxOR0NAPJOMB5UZ7RT4UTY6Sj7jVKqwFBKAQBySTQZVUekI2fmImS7eCqu1xpe0zNrn9Hf1/9d7ZH27W6vr67Xpw74lE6edLKOHHUkhQL2m9fl3amsYk4VAOy9RCqhrliX/DF/Xq0op5QqMJRSAIBc1HOCTFesK69+EHNSKp3Ssq3L9Le1f9Mz657RlsCW7W4fXjpcJ9WfpJMnnaxjxh+jYk+xQ0mRb1zGJZ/bt9OH1+VlpR4A9NGzerwr1pUXq6J2hVKqwFBKAQByWc8PZ53RTkWSEafj5A1rrVa2rNQz657Rc+ue04ftH253e4mnRMdNOE4nTzpZJ9afqGElwxxKinxmZOR1e3dZVrldbqfjAcCQiafi6op2r4pK2ZTTcQYVpdT+v+hfJH1O0jZr7fTMtR9L+rKklszdfmCtfTJz2/clXS4pJenfrLVPZ67PkvRXSSWSnpT0dWutNcYUSbpd0ixJbZIusNZuyDzmMkk/yrzGz6y1t31UXkopAEC+iCVj6oh2KBALsLVvgG3q2qTn1j+nZ9c9qyVNS7YbnuoyLs0aPUtzJs3RSfUnadKwSQ4mRaFwG/f2RVWmvGJ1FYB8Ya1VIB5QV7SroP7hjVJq/1/0eElBSbfvUEoFrbX/tcN9D5F0j6SjJI2R9HdJB1lrU8aYNyR9XdJr6i6lfmetXWSM+Zqkw621XzXGXCjpLGvtBcaYGklLJM2WZCUtlTTLWtuxp7yUUgCAfMOpfYOrI9KhxRsX6+/r/q6XNr200w/K9VX1OmnSSTqx/kTNGj2LeUEYUjuuruo5CZDTAAHkilgy1jsrKldP0NsflFID88L1kh7vRyn1fUmy1v4i8/XTkn4saYOk5621UzPXL5J0orX2Kz33sda+aozxSNoqqU7ShT33yTzmj5JesNbes6eslFIAgHxlrZU/5ldHtEPxVNzpOHkpmozq1c2v6tn1z+qFDS+oJdyy3e0Vvgp9cuIndWL9iTp+wvFs84Oj+q6soqwCkE16fmbpinUV/EnDhVJKeYY6jKSrjDHz1b2a6VuZFUxj1b0SqkdD5loi8/mO15X5dbMkWWuTxpguSbV9r+/iMdsxxlwp6UpJmjBhwv69KwAAspQxRlXFVaoqrlIoHlJ7pL2glr8PhWJPsU6adJJOmnSS0jat91re0/Prn9fzG57XypaVCsQDenL1k3py9ZNyGZdmjJqhE+tP1AkTT9BBtQdRBmBIxVPxXRbUHpdnp5lVPVsCAWAwFfqqqEI21KXUHyT9VN3b6n4q6TeSviRpVz+J2T1c1z4+ZvuL1t4s6Wape6XUnoIDAJAPynxlKvOVKZqMqj3SrmA86HSkvOMyLk0fMV3TR0zX1R+/Ws3BZi3euFjPrX9Orza8qmgyqqVNS7W0aal+8+pvNKp8lE6YeIKOn3i8jhl3jMp8ZU6/BRSoZDqpZDq500lWO24F7FtWeVxO/Bs3gHyQtmkFYgFWRRW4If1TxFrb3PO5MeZPkh7PfNkgaXyfu46TtCVzfdwurvd9TENm+16VpPbM9RN3eMwLA/UeAADIB8WeYo2pGKN4Kq6OSIf8MT9D0QfJyPKROv/Q83X+oecrmozq9YbX9dyG57R4w2I1BZu0NbhVC1Yu0IKVC+R1eTV7zOzukqr+eB1QfQCrqOA4K7vb1VVGpreg6ltW+dw+CisAO+k5LTgQDygUD/GzB4Z8ptRoa21T5vNvSvq4tfZCY8yhku7WPwedPytpSmbQ+ZuSrpb0uroHnf/eWvukMeZfJR3WZ9D52dba8zODzpdKmpmJ8Za6B5237ykrM6UAAIWsZyh6V7RLiXTC6TgFwVqrNe1rtHjjYi3euFhvNb2100D6cZXjdPzE4/XJCZ/Ux8d+nFVUyCku49rl7Cq2AwKFxVqrUCKkQCygUCLE9rx+KpSZUoN5+t496l6xNFxSs6TrMl8fqe7tdBskfaVPSfVDdW/lS0r6hrV2Ueb6bEl/lVQiaZGkq6211hhTLOkOSTPUvULqQmvtusxjviTpB5koP7fW3vpReSmlAADoFoqH1BXrYmvfEAvGg3pl8yvdJdWGxTsNS/e6vJoxeoY+OeGTOm7CcZo6fKpcxuVQWmDf9S2r+hZWlFVA/rDWKpwIKxAPKBgPUkTtA0qpAkMpBQDA9pLppLqiXeqKde20ggeDy1qr91vf14sbX9SLm17UsqZlStnUdvepLanVJyZ8QsdNOE7HjT9OtaW1DqUFBkbPVsBdfbCNFchuaZtWNBlVLBlTLBVTKB7a6c8t7B1KqQJDKQUAwO4F40F1RbsUSoScjlKQgvGgXmt4TS9ufFEvbXpJjYHGne5zSN0hOnb8sfrE+E9o5uiZKvYUO5AUGBw986r6bgFkbhXgjFQ61V1ApWK9RRRb/wcepVSBoZQCAOCjJVKJ3iObWT3lDGutNnRu0EubXtJLm17S642vK5KMbHefIneRZo2ZpWPGHaNPjP+EptVNY6sf8lLfrYA7FlesroJTFq1epBteuUHrO9drUvUkXXPsNZo7Za7TsfZZLBlTOBFWOBFWLBXL+j//F29YrFuW3aIGf4PGVY7T5TMu1wn1Jzgda69RShUYSikAAPqvZ2gpq6ecF0/FtbRpqV7e9LJe2fyK3mt5b6fTjKqLq3XMuGN07Phjdez4Y/Pmh1xgTzwuz3ZlVc/qKq/LS2GFQbNo9SJdtegq+Vw+lXpLFU6EFU/HddPcm3KmmIqn4r0lVCQRyalteIs3LNb1L14vn8unYk+xosmo4um4rj3+2pwrpiilCgylFAAA+4bVU9mlPdKu1xtf1yubXtHLm1/e5Va/8ZXjdfS4o3X0uKP18bEfV11ZnQNJAefsuKqqyNM9bJ0Vhdhfc26bo6ZA03anpYbiIY2uGK3nLnvOwWS7l0gluguoZEThRDin/yyfv3C+WkItKvGW9F6LJCKqK6vT7Wfd7mCyvVcopRSbsAEAwH7xur0aXjpctSW1CiVC6ox2KpwIOx2rYNWU1GjugXM198Duf5Hf1LVJr2x+Ra9sfkWvNbymrliXNvs3a/N7m3X/e/dLkiYPm9xbUn1szMc0rGSYk28BGHSJdEKJdGKnlZ49q6t6TgSkrMLeWt+5XjXFNdtdK/WWakPnBmcC7cBaq1gqpkgiomgyqkgyktMl1I4a/A2qKqra7lqxp1iN/p3/gQbZgVIKAAAMCGOMyn3lKveVs3oqi0yomqAJVRN04fQLlUqntLJlpV5vfF2vNbympVuWKpKMaG3HWq3tWKu7lt8lI6Opw6f2rqKaNWaWKosqnX4bwJBIppNKppM7Fes7bgXsO3Ad6GtS9aSdVkqFE2HVV9c7kqdnKHkkGektonbc4p1PxlWO22mlVDQZ1djKsQ6mwp6wfS+D7XsAAAyOUDwkf8yvYDyY1z8I56J4Kq7l25brtYbX9FrDa1rWtGynE5SMjKbVTdPHxnxMR409SrPHzFZ1cbUzgYEsY2R2mlfldrnlcXnkcXnkNm7mVxUYp2dKxVPx7hIqEVEkGVE8FR/018wmzJTKTsyU6gdKKQAABlcqnVIgHpA/5lc0GXU6DnYhmoxqWdMyvdb4ml7b/JpWtKzYaaWbkdFBtQfpqLFH6WNjPqaPjf2YakpqdvOMAFzG1VtQeVye3tLK6/LK6/b2Fljolg8n1/W8hw2dG1RfXT+o76FvARVNRlmdrH+evtfob9TYyrGcvpcFKKX6gVIKAIChE0vG5I/55Y/5c+pUn0ITiof09ta39UbjG3pjyxta3rx8p5VUknRgzYGaNXqWZo2ZpdmjZ2tMxRhWhwB7wcj0FlR9y6q+nxcCp1cZZbNUOtW7vbRnO140GVXapp2OhkFS7ClWua88L/7hh1KqHyilAAAYetZahRNhBeIBheIhCqosF0lE9Hbz23qz8U292fim3m5+e5dbQ0aVj9Ls0bM1c8xMzR49W1NqpzAoGtgPPaVVT0m146/58r+vXDy5biCkbbq3cEqkEv/8PP3Pzymf8l80GdWKbSu0dMtSvdX0lpZtXaajxx2tpy55yulo+41Sqh8opQAAcF4kEVEwHlQwHtzlihxkl1gypneb39WbW97U0qalWta0bKfTzCSpsqhSM0fN1KwxszRz9ExNHzFdxZ5iBxID+alna+CePtwut9MxP9Kk305STXHNdistrbXqiHZo3dfXOZhs3/Vd4dS3ZOr7QeFUmNoj7Xqr6a3ePz9XbFux088+Fb4KdXy3Iyf+97snlFL9QCkFAEB2iafivQUVM6hyQzKd1IdtH2rJliVa2rRUS7csVUu4Zaf7eVweTRs+TTNGz9CMUd0foytGO5AYKBxGZrsh7H3nXPWddeXkcPZsXimVtmmlbVqpdOqfn9uUUunUHn8FpO7/fta2r9XbW9/Wsq3LtLRpqTZ0btjlfQ8YdoDGlI9RU7BJ0WRUU2qm6Duf+E5Ob2GllOoHSikAALJXMp3sPcUvkow4HQf9ZK3VZv9mLd2yVEualmjplqVa37l+l/cdVT6qu6DKFFVTh0+Vz+0b4sQAJG03lH3HAe1u497nAsta21vo7Orj6bVP6zvPfEdel1clnpLu0+PScf3spJ/phPoTlLbp7Z5jxxNdjXbO0pPPyMgYs8dfXca1XZ6U/WcBBewNf8yvt7e+rXe2vtP9a/M7CsQDO93P6/Jq+ojpmjm6ezXxjFEztLx5ua5/8XoVuYpUVVyVF7PVKKX6gVIKAIDcEE/F1RXtYkh6juqIdOid5ne0rGmZ3tr6lpY3L99l0ehz+3Ro3aE6fOThOmLkETpi1BEaWzGWAepAltnTPKsd/665Y4m0K/lychoKRyqd0tqOtXpn6ztatnWZ3t76ttZ2rN3lfYcVD9ORo47UzNEzNXP0TB024jAVeYq2u8/8hfPVEmpRma+s9x9nsmXF4L6ilOoHSikAAHKLtVahREhd0a5dzjFCbkimk/qg9QMt27pMy5qWadnWZWoMNO7yvrUltd0l1agjdMTII3TYiMNUUVQxxIkBAIXKWqumYJPebX5X7za/q+XNy7WiZYXCifBO93UZlw6uPVhHjjpSR446UjNGzdCEqgkf+Y8rc26bo6qiKrld7t5SKtdnq1FK9QOlFAAAuSuZTsof86sr2sWA9DzQHGzWu83v6p3md/RO8ztasW3XP/AbGR0w7AAdNuIwTR8xXdNHTNe0umkMUQcADIiuaJdWbFuhd7e921tEtYZbd3nfnlVQM0bN0JGjjtT0EdO3m4/WX6yUKlCUUgAA5IdwIix/zK9ALNCvrSLIfql0SqvbV/cWVe9ufVer21fv8vfXbdyaUjtF00dM7y2rDqo9iPlUAIA98sf8WtmyUiu3rdSKbSu0YtsKbfZv3uV9iz3FvVvMDx95uA4beZjGVYwbkC3mizcsZqZUIaKUAgAgv6RtWsF4UP6Yf5erbJDbgvGgVmxboeXblnf/2rx8t9v+vC6vDh5+sA6tO1SH1h2qaXXTdHDtwTvN8QAAFIZALKD3Wt7Tim0rtLKlu4Ta2LVxl/d1GZem1EzpLaAOH3m4Dqw5UB6XZ9DyLd6wWLe+fau2Breqvrpe1xx7Tc4WUhKlVL9QSgEAkL8SqYT8Mb/8MT/b+/JYe6S991+3e8qqbaFtu7yvx+XR5GGTdWjdoTqk7hAdMuIQTa2duk9bLQAA2WtbaJtWtazSe63vaVXLKq1qXaVNXZt2eV8jo0nDJmn6iOk6tO7Q7m3hw6c58mdDqbdU4yrHDfnrDgZKqX6glAIAoDBEEpHu7X3xAMd8F4DmYLNWtHQXVataVmlly8rdFlVGRvXV9ZpWN01Ta6dq6vDujxFlIzj1DwCyXNqmtalrk95r+Wf5tKp11W5nQPX8f37PTMLpI6Zr6vCpKveVD3HyXaOUKjCUUgAAFBZrrYLxoILxoEKJEAVVAWkNt+q9lvd6P1a2rFSDv2G3968uru4uqPoUVZNrJjOnCgAc4o/59WHbh/qg9QO93/q+Pmj7QKvbV+92u77H5dGBNQfqkOGHaGrdVB0y/BBNq5uWNQXUrlBKFRhKKQAACpe1VqFEqLekKuSCavGGxbpl2S1q8DdoXOU4XT7jcp1Qf4LTsQZdV7RLq1pX6b2W9/R+6/t6v/V9re1Yq2Q6ucv7e1weHVB9gA6qPUhTaqf0/jq2YqxcxjXE6QEgPyVSCW3s2thbQH3Q1v2xJbBlt48p9ZZq6vCpmjZ8mqbVTdMhww/RlNopOfcPCZRSBYZSCgAASN0FVTgRViAeUCgeUsqmnI40ZHpO/PG5fCr2FCuajCqejuva468tiGJqR/FUXGvb1/aWVO+3df/aGe3c7WNKvaWaUvPPkuqgmu5fa0tq2QIIALuRSqe02b9Za9rX6MO2D7WmfY1Wt63W+s71e5wFOa5ynA6uPVgHDz9YU2un6qDagzSxemJe/OMApVSBoZQCAAA7stYqkowoEAsonAjn/ZD0+QvnqyXUohJvSe+1yP9v7+6D5Mjv+o5/vvO8M/ssrXSrXZ20d1ZhzgSsWDbmAhxRwtlbocom2PgqBExQxZUEUbggSmxc2HD8EShVhdilmIrhwGdiYxwDBaFqA46xfSbnwtz5bN8Z26WTd3V6WEkraR9ndp56fvmje1oz+yxptmd29/2q6uru30z3/PpOrdF+9vv7dWVZQ7khfezHP9bGnnUO55xu5G80DRc5f+u8Xr798oZ/PvrT/Xp48GG9avBVenjwYT084G8fzB0krAKwZ1RrVV2av6QLsxf0ndnv+OHT7fO6cPuCSl5p3eOyyWwYPn3Xvu/Sq/f7AVQnD7+7X3sllNq+ZxgCAADscGambDKrbDIryR9GUKgUVKgUtFxdXndo1051eeGy+tJ9TW2ZREZXFq60qUedx8x0sPugDnYfbKoeq9aq4RCT87fOh+uL8xfl5DRXmtPz08/r+ennm86XS+aagqqxgTGN9Y/pcO9hJePJqC8PAFqiUClocnZS35n9ThhAXZi9oItzFzcM8DOJTBjaH9t3TMcG/WW4Z3hXVD9hNUIpAACALUrGk+qL96kv4wc3Za8chlSFSmHHz0U12ju6qlKqWC1qpHekjb3aGRKxhB4e8IOl8VeNh+3LlWVNzk3q5dsv68LtC3p51l+/Mv+KPOcpX8nra9e/pq9d/9qq8432jmqsf0xjA2N6qP8hfz3wkAYyA1RXAWg7r+bp6tJVTc1OaWpuSpNzk5qa87evLG78y4x0PK2xgTE9PPBwU/g02juqeCwe0RWgExBKAQAA3KNUPKVUPKX+TL8kP8BZLC1qobSwI+eiOnX8lJ585kmpoqY5pU4dP9Xuru1YXckuPTL0iB4ZeqSpveyVNTU3FYZVF2Yv6MLtC5qan1LZK6taq4Y/3H1u6nNNx/al+3Sk/4ge7HtQR/uO6kj/ER3pO6Ij/UfCP4sA0Ao1V9NMfkavzL+ii/MXw7+XJucmN616kvy/rx4aeEgPDz6sh/ofCqtCD/UcInyCJOaUCjGnFAAAaJX6ZOnzpXnly3k57Zx/b9Wfvndl4YpGekf2zNP3OkW98mBydlKTc5NN6+v565sevzKwOtx32F96D2soO0SFFYBVqrWqri5eDYOnS/OXwvWlhUsqVosbHt9Y2Xm03w/K6wEUD3m4d3tlTilCqQChFAAA2A5ezdNCaUELpYUNJ3EFNpMv5+9UKMxf1MW5i3pl/hVNzU1ptji76fHpeFqjvaM63OsHVaO9o+H+aO+ocqlcBFcBIGrOOd0s3NTlhcv+sng53L6ycEXTS9NbmiPxQO5AGDzV10f7j2q0d5Q58LYBodQeQygFAAC2W6la0nxpXoulxR05vA+da6G0cCekmp/SK3NBxcPCJd0s3NzSOfrT/TrUe0iHevxlpGck3D7Uc4i5rIAOVa1VNZOf0dWlq5penNbVxau6unhVVxavhMHTVn4pEre4RnpH9GDvg3qw/8Gm9eG+w8okMhFcDeoIpfYYQikAABCV+vC+pfKS8pX8rnuKHzpLoVLQlYUrurTgD8W5NH8prJLYytCcumwyq+HuYQ13D+tg90ENdw/rge4HwmW4Z3hXP54daIeaq2l2eVbX89d1bemaruevNwVP00vTur50fcu/6OjP9IdVkuHSM6oj/Uc03D1MxVMH2SuhFBOdAwAARMzMlEvlwuFSpWpJ+UpeS+WlLQcEwFZlk1n/6Vb7jq16zTmnmcKMrixcCSsr6j/s1vcLlYIkP9y6MOtPyr6eXDLnB1TdwzqQO7Dmsj+7nx98AflP55wpzOhG/oZmCjO6vnRd15eu61r+mr9euqYb+RubTibeaCAzoEM9hzTcM6xDPYeagqeR3hGCY3QcQikAAIA2SyfSSifSGuwalFfzwgqqQqWgmqu1u3vYxcwsDIuODx9f9bpzTvOl+aaQ6tqS/wNzvULjev56WO2Xr+Q3Da4kabBrsCmk2t+1X/uy+7Q/G6yD/f5Mv2IW25ZrB7ZDxatotjir28u3datwSzOFGd0s3NRMfkYzhRnN5Gd0o3BDNws3tVReuqtzp+IpHcwd1HDPsEZ6RvzgqdsPoOrbXcmubboyYHsQSgEAAHSQeCyuvkyf+jJ9cs5pubqsfNkPqJgoHVEzM/Vn+tWf6dcjQ4+s+R6v5unW8i1dW7qma0vXNL00rWtL1/wfvvM3wiVfyYfH3F6+rdvLt/Wtm9/a8PMTsYQGMgNhWDWQGdBg16AGugY0mAnWXYMayAxooGuAEAstV/bKml2e1WzRX+aKc5pdng3/DN9avqXbBX99a/mW5opz9/Q5velePZB7QAe6D+iB7gd0MHcwXB/sPqiDuYPqz/Qzrxt2HUIpAACADmVmyiazyiazkvwf/usVVIVKgbmo0BHisXhY9fS9B7933fctlZfCapHGsGqmMKNbhVu6Vbilm8s3Nbs8Kyd/3ttqrepXlxRmttSXmMXUl/ZD3cZ1f6ZfveneVfu96V71pHrUnepWNpnlB/5dyjmnpfJS+KCJ+dK8FkoL/rq4oIWy/4TUheKCHzrVw6fibDh89V7ELa7BrkEN5Ya0P7tfQ9khDeWGdCB7QEO5oXB/f3Y/k4hjzyKUAgAA2CHisXj4g7Tk/wa/XkW1XF1mqB86WneqW92pbo0NjG34vmqtqtnlWd1avqWZ/IxuLd/SzcJN3V6+HVas3F6+Ha4bh0DVXC2saLlbcYuHfQzDqnR3U2iVS+X8dTIX7ueSuXA/m8wqk8gok8gwb9Z9cM6pUqsoX85rubocBvH1Zbnit9Xn4suX/fVSZUmLpcU7bZUlv7281JK/H03mh5pd/WEF32DXoPZl92lf1z5/u2uf9mX9bSr3gM0RSgEAAOxQqXhKqa6UBroG5JzTYnlRC6WF+/rNPtBuiVjCryLJDenV+1+96fvLXllzxbkwqJpdntV8aV7zxfnV6+K85kpzWigtrHqogOc8/32leV1ZvNKS66gHVJlERl2JrnA7nUgrHU/79/AmSzKWVDwWVyKWUCKWUNziSsQTSliwH4srGUsqZjGZ2Z21GvZ1p91kcnJyzoUVaSu3JT/g85wnr+ap5mqq1qr+2lVVqzWvK15FlVpFFa+islcOt1fuF72iStWSStVSuF2sFlXySuF2fdnq0+TuVU+qJ6ye6033qi/dp550j/ozfuDUn+kPh4TW9/vSfYrH4tvaL2CvIZQCAADYBcwsrKKqeJVweApD/LDbpeKpcPjg3ShWi1osLWqx7FfW1LcXy4taKi2FIe9Secmvyinnla/kwyG0m831Vq1VwyodtE42mVVXostfJ7vCSrbNlsbgqSf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      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_emp = out.groupby('SYEAR').agg({'Employment':sum})\n",
    "total_emp['foresting'] = out[out.LMO_Detailed_Industry == 'Forestry and logging'].groupby('SYEAR').agg({'Employment':sum})\n",
    "total_emp = total_emp.rename(columns={'Employment':'Total_employment'})\n",
    "\n",
    "ax = sns.regplot(x=total_emp.index, y=\"foresting\",order=2, data=total_emp,color='g') #Create a regression plot Order 2 with default Confidence interval\n",
    "ax.set_title('Foresting Employment')\n",
    "ax.set_ylabel('Employment')\n",
    "ax.set_xlabel('Year long evolution')\n",
    "\n",
    "#total_emp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8593c133",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}