trainee-pharmacist-salary.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "TODO\n",
    "- [ ] Write methodology  \n",
    "- [x] Remove irrelevant data columns in the preprocessing  \n",
    "- [x] Salary above grant and living wage  \n",
    "- [x] Number of visa available places over 3 years  \n",
    "- [x] Hours worked per week (expectation to work on the weekends and lates in hospitals)  \n",
    "- [ ] Primary care only pay distribution and hourly\n",
    "\n",
    "\n",
    "\n",
    "- https://survey.stackoverflow.co/2024/\n",
    "- https://www.gov.uk/national-minimum-wage-rates\n",
    "\n",
    "- Make online database using openai API to summarise the programme description into quick bullet points with filter function e.g. geographical"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "Attaching package: ‘dplyr’\n",
      "\n",
      "\n",
      "The following objects are masked from ‘package:stats’:\n",
      "\n",
      "    filter, lag\n",
      "\n",
      "\n",
      "The following objects are masked from ‘package:base’:\n",
      "\n",
      "    intersect, setdiff, setequal, union\n",
      "\n",
      "\n",
      "\n",
      "Attaching package: ‘maps’\n",
      "\n",
      "\n",
      "The following object is masked from ‘package:purrr’:\n",
      "\n",
      "    map\n",
      "\n",
      "\n",
      "Warning message in readRenviron(\"/.renviron\"):\n",
      "“file '/.renviron' cannot be opened for reading”\n"
     ]
    }
   ],
   "source": [
    "library(dplyr)\n",
    "library(ggplot2)\n",
    "library(tidyr)\n",
    "library(openai)\n",
    "library(purrr)\n",
    "library(maps)\n",
    "\n",
    "readRenviron(\"/.renviron\")\n",
    "OPENAI_API_KEY <- Sys.getenv(\"open_ai_api_key\")\n",
    "\n",
    "Sys.setenv(\n",
    "    OPENAI_API_KEY = OPENAI_API_KEY\n",
    ")\n",
    "\n",
    "# Load the data\n",
    "OD2526 <- read.csv(\"oriel-training-year-2526.csv\")\n",
    "OD2425 <- read.csv(\"oriel-training-year-2425.csv\")\n",
    "OD2324 <- read.csv(\"oriel-training-year-2324.csv\")\n",
    "OD2223 <- read.csv(\"oriel-training-year-2223.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
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       "<ol class=list-inline><li>'Programme.SystemID'</li><li>'Recruitment.Office'</li><li>'Region'</li><li>'Sub.Region'</li><li>'Sector'</li><li>'Post.Type'</li><li>'Programme.Preference'</li><li>'Abbreviation'</li><li>'Programme.Title'</li><li>'Programme.Description'</li><li>'Places.Available'</li><li>'Start.Date'</li><li>'Employer.Type'</li><li>'Employer.Name'</li><li>'Size.of.organisation..Primary.care.only.'</li><li>'Specialties..Hospital.only.'</li><li>'Skilled.worker.visa'</li><li>'Number.of.Licences'</li><li>'Salary....'</li><li>'Training.Provider'</li><li>'Employer.website'</li><li>'Hours.per.Week'</li><li>'ProgrammeNumber'</li><li>'ProgrammeName'</li><li>'ICB.Name'</li><li>'Pharmacy.Programme.Number'</li><li>'Number.of.Placements.Rotations'</li><li>'Practice.Placement.Rotation.Setting.1'</li><li>'Length.of.Placement.Rotation.1..weeks.'</li><li>'Practice.Placement.Rotation.Setting.2'</li><li>'Length.of.Placement.Rotation.2..weeks.'</li><li>'Practice.Placement.Rotation.Setting.3'</li><li>'Length.of.Placement.Rotation.3..weeks.'</li><li>'Practice.Placement.Rotation.Setting.4'</li><li>'Length.of.Placement.Rotation.4..weeks.'</li><li>'Placement.Rotation.1..SystemID'</li><li>'Placement.Rotation.2..SystemID'</li><li>'Placement.Rotation.3..SystemID'</li><li>'Placement.Rotation.4..SystemID'</li></ol>\n"
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      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Programme.SystemID'\n",
       "\\item 'Recruitment.Office'\n",
       "\\item 'Region'\n",
       "\\item 'Sub.Region'\n",
       "\\item 'Sector'\n",
       "\\item 'Post.Type'\n",
       "\\item 'Programme.Preference'\n",
       "\\item 'Abbreviation'\n",
       "\\item 'Programme.Title'\n",
       "\\item 'Programme.Description'\n",
       "\\item 'Places.Available'\n",
       "\\item 'Start.Date'\n",
       "\\item 'Employer.Type'\n",
       "\\item 'Employer.Name'\n",
       "\\item 'Size.of.organisation..Primary.care.only.'\n",
       "\\item 'Specialties..Hospital.only.'\n",
       "\\item 'Skilled.worker.visa'\n",
       "\\item 'Number.of.Licences'\n",
       "\\item 'Salary....'\n",
       "\\item 'Training.Provider'\n",
       "\\item 'Employer.website'\n",
       "\\item 'Hours.per.Week'\n",
       "\\item 'ProgrammeNumber'\n",
       "\\item 'ProgrammeName'\n",
       "\\item 'ICB.Name'\n",
       "\\item 'Pharmacy.Programme.Number'\n",
       "\\item 'Number.of.Placements.Rotations'\n",
       "\\item 'Practice.Placement.Rotation.Setting.1'\n",
       "\\item 'Length.of.Placement.Rotation.1..weeks.'\n",
       "\\item 'Practice.Placement.Rotation.Setting.2'\n",
       "\\item 'Length.of.Placement.Rotation.2..weeks.'\n",
       "\\item 'Practice.Placement.Rotation.Setting.3'\n",
       "\\item 'Length.of.Placement.Rotation.3..weeks.'\n",
       "\\item 'Practice.Placement.Rotation.Setting.4'\n",
       "\\item 'Length.of.Placement.Rotation.4..weeks.'\n",
       "\\item 'Placement.Rotation.1..SystemID'\n",
       "\\item 'Placement.Rotation.2..SystemID'\n",
       "\\item 'Placement.Rotation.3..SystemID'\n",
       "\\item 'Placement.Rotation.4..SystemID'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Programme.SystemID'\n",
       "2. 'Recruitment.Office'\n",
       "3. 'Region'\n",
       "4. 'Sub.Region'\n",
       "5. 'Sector'\n",
       "6. 'Post.Type'\n",
       "7. 'Programme.Preference'\n",
       "8. 'Abbreviation'\n",
       "9. 'Programme.Title'\n",
       "10. 'Programme.Description'\n",
       "11. 'Places.Available'\n",
       "12. 'Start.Date'\n",
       "13. 'Employer.Type'\n",
       "14. 'Employer.Name'\n",
       "15. 'Size.of.organisation..Primary.care.only.'\n",
       "16. 'Specialties..Hospital.only.'\n",
       "17. 'Skilled.worker.visa'\n",
       "18. 'Number.of.Licences'\n",
       "19. 'Salary....'\n",
       "20. 'Training.Provider'\n",
       "21. 'Employer.website'\n",
       "22. 'Hours.per.Week'\n",
       "23. 'ProgrammeNumber'\n",
       "24. 'ProgrammeName'\n",
       "25. 'ICB.Name'\n",
       "26. 'Pharmacy.Programme.Number'\n",
       "27. 'Number.of.Placements.Rotations'\n",
       "28. 'Practice.Placement.Rotation.Setting.1'\n",
       "29. 'Length.of.Placement.Rotation.1..weeks.'\n",
       "30. 'Practice.Placement.Rotation.Setting.2'\n",
       "31. 'Length.of.Placement.Rotation.2..weeks.'\n",
       "32. 'Practice.Placement.Rotation.Setting.3'\n",
       "33. 'Length.of.Placement.Rotation.3..weeks.'\n",
       "34. 'Practice.Placement.Rotation.Setting.4'\n",
       "35. 'Length.of.Placement.Rotation.4..weeks.'\n",
       "36. 'Placement.Rotation.1..SystemID'\n",
       "37. 'Placement.Rotation.2..SystemID'\n",
       "38. 'Placement.Rotation.3..SystemID'\n",
       "39. 'Placement.Rotation.4..SystemID'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Programme.SystemID\"                      \n",
       " [2] \"Recruitment.Office\"                      \n",
       " [3] \"Region\"                                  \n",
       " [4] \"Sub.Region\"                              \n",
       " [5] \"Sector\"                                  \n",
       " [6] \"Post.Type\"                               \n",
       " [7] \"Programme.Preference\"                    \n",
       " [8] \"Abbreviation\"                            \n",
       " [9] \"Programme.Title\"                         \n",
       "[10] \"Programme.Description\"                   \n",
       "[11] \"Places.Available\"                        \n",
       "[12] \"Start.Date\"                              \n",
       "[13] \"Employer.Type\"                           \n",
       "[14] \"Employer.Name\"                           \n",
       "[15] \"Size.of.organisation..Primary.care.only.\"\n",
       "[16] \"Specialties..Hospital.only.\"             \n",
       "[17] \"Skilled.worker.visa\"                     \n",
       "[18] \"Number.of.Licences\"                      \n",
       "[19] \"Salary....\"                              \n",
       "[20] \"Training.Provider\"                       \n",
       "[21] \"Employer.website\"                        \n",
       "[22] \"Hours.per.Week\"                          \n",
       "[23] \"ProgrammeNumber\"                         \n",
       "[24] \"ProgrammeName\"                           \n",
       "[25] \"ICB.Name\"                                \n",
       "[26] \"Pharmacy.Programme.Number\"               \n",
       "[27] \"Number.of.Placements.Rotations\"          \n",
       "[28] \"Practice.Placement.Rotation.Setting.1\"   \n",
       "[29] \"Length.of.Placement.Rotation.1..weeks.\"  \n",
       "[30] \"Practice.Placement.Rotation.Setting.2\"   \n",
       "[31] \"Length.of.Placement.Rotation.2..weeks.\"  \n",
       "[32] \"Practice.Placement.Rotation.Setting.3\"   \n",
       "[33] \"Length.of.Placement.Rotation.3..weeks.\"  \n",
       "[34] \"Practice.Placement.Rotation.Setting.4\"   \n",
       "[35] \"Length.of.Placement.Rotation.4..weeks.\"  \n",
       "[36] \"Placement.Rotation.1..SystemID\"          \n",
       "[37] \"Placement.Rotation.2..SystemID\"          \n",
       "[38] \"Placement.Rotation.3..SystemID\"          \n",
       "[39] \"Placement.Rotation.4..SystemID\"          "
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       "<ol class=list-inline><li>'Programme.SystemID'</li><li>'Recruitment.Office'</li><li>'Region'</li><li>'Sub.Region'</li><li>'Sector'</li><li>'Post.Type'</li><li>'Programme.Preference'</li><li>'Abbreviation'</li><li>'Programme.Title'</li><li>'Programme.Description'</li><li>'Places.Available'</li><li>'Start.Date'</li><li>'Employer.Type'</li><li>'Employer.Name'</li><li>'Size.of.organisation..Primary.care.only.'</li><li>'Specialties..Hospital.only.'</li><li>'Skilled.worker.visa'</li><li>'Number.of.Licences'</li><li>'Salary....'</li><li>'Training.Provider'</li><li>'Employer.website'</li><li>'Hours.per.Week'</li><li>'ProgrammeNumber'</li><li>'ProgrammeName'</li><li>'ICS.Name'</li><li>'Pharmacy.Programme.Number'</li><li>'Number.of.Placements..3.months.or.more.'</li><li>'Practice.Placement.Setting.1'</li><li>'Length.of.Placement.1..3.months.or.more.'</li><li>'Practice.Placement.Setting.2'</li><li>'Length.of.Placement.2..3.months.or.more.'</li><li>'Practice.Placement.Setting.3'</li><li>'Length.of.Placement.3..3.months.or.more.'</li><li>'Practice.Placement.Setting.4'</li><li>'Length.of.Placement.4..3.months.or.more.'</li><li>'Placement.1..SystemID'</li><li>'Placement.2..SystemID'</li><li>'Placement.3..SystemID'</li><li>'Placement.4..SystemID'</li></ol>\n"
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      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Programme.SystemID'\n",
       "\\item 'Recruitment.Office'\n",
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       "\\item 'Sub.Region'\n",
       "\\item 'Sector'\n",
       "\\item 'Post.Type'\n",
       "\\item 'Programme.Preference'\n",
       "\\item 'Abbreviation'\n",
       "\\item 'Programme.Title'\n",
       "\\item 'Programme.Description'\n",
       "\\item 'Places.Available'\n",
       "\\item 'Start.Date'\n",
       "\\item 'Employer.Type'\n",
       "\\item 'Employer.Name'\n",
       "\\item 'Size.of.organisation..Primary.care.only.'\n",
       "\\item 'Specialties..Hospital.only.'\n",
       "\\item 'Skilled.worker.visa'\n",
       "\\item 'Number.of.Licences'\n",
       "\\item 'Salary....'\n",
       "\\item 'Training.Provider'\n",
       "\\item 'Employer.website'\n",
       "\\item 'Hours.per.Week'\n",
       "\\item 'ProgrammeNumber'\n",
       "\\item 'ProgrammeName'\n",
       "\\item 'ICS.Name'\n",
       "\\item 'Pharmacy.Programme.Number'\n",
       "\\item 'Number.of.Placements..3.months.or.more.'\n",
       "\\item 'Practice.Placement.Setting.1'\n",
       "\\item 'Length.of.Placement.1..3.months.or.more.'\n",
       "\\item 'Practice.Placement.Setting.2'\n",
       "\\item 'Length.of.Placement.2..3.months.or.more.'\n",
       "\\item 'Practice.Placement.Setting.3'\n",
       "\\item 'Length.of.Placement.3..3.months.or.more.'\n",
       "\\item 'Practice.Placement.Setting.4'\n",
       "\\item 'Length.of.Placement.4..3.months.or.more.'\n",
       "\\item 'Placement.1..SystemID'\n",
       "\\item 'Placement.2..SystemID'\n",
       "\\item 'Placement.3..SystemID'\n",
       "\\item 'Placement.4..SystemID'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Programme.SystemID'\n",
       "2. 'Recruitment.Office'\n",
       "3. 'Region'\n",
       "4. 'Sub.Region'\n",
       "5. 'Sector'\n",
       "6. 'Post.Type'\n",
       "7. 'Programme.Preference'\n",
       "8. 'Abbreviation'\n",
       "9. 'Programme.Title'\n",
       "10. 'Programme.Description'\n",
       "11. 'Places.Available'\n",
       "12. 'Start.Date'\n",
       "13. 'Employer.Type'\n",
       "14. 'Employer.Name'\n",
       "15. 'Size.of.organisation..Primary.care.only.'\n",
       "16. 'Specialties..Hospital.only.'\n",
       "17. 'Skilled.worker.visa'\n",
       "18. 'Number.of.Licences'\n",
       "19. 'Salary....'\n",
       "20. 'Training.Provider'\n",
       "21. 'Employer.website'\n",
       "22. 'Hours.per.Week'\n",
       "23. 'ProgrammeNumber'\n",
       "24. 'ProgrammeName'\n",
       "25. 'ICS.Name'\n",
       "26. 'Pharmacy.Programme.Number'\n",
       "27. 'Number.of.Placements..3.months.or.more.'\n",
       "28. 'Practice.Placement.Setting.1'\n",
       "29. 'Length.of.Placement.1..3.months.or.more.'\n",
       "30. 'Practice.Placement.Setting.2'\n",
       "31. 'Length.of.Placement.2..3.months.or.more.'\n",
       "32. 'Practice.Placement.Setting.3'\n",
       "33. 'Length.of.Placement.3..3.months.or.more.'\n",
       "34. 'Practice.Placement.Setting.4'\n",
       "35. 'Length.of.Placement.4..3.months.or.more.'\n",
       "36. 'Placement.1..SystemID'\n",
       "37. 'Placement.2..SystemID'\n",
       "38. 'Placement.3..SystemID'\n",
       "39. 'Placement.4..SystemID'\n",
       "\n",
       "\n"
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      "text/plain": [
       " [1] \"Programme.SystemID\"                      \n",
       " [2] \"Recruitment.Office\"                      \n",
       " [3] \"Region\"                                  \n",
       " [4] \"Sub.Region\"                              \n",
       " [5] \"Sector\"                                  \n",
       " [6] \"Post.Type\"                               \n",
       " [7] \"Programme.Preference\"                    \n",
       " [8] \"Abbreviation\"                            \n",
       " [9] \"Programme.Title\"                         \n",
       "[10] \"Programme.Description\"                   \n",
       "[11] \"Places.Available\"                        \n",
       "[12] \"Start.Date\"                              \n",
       "[13] \"Employer.Type\"                           \n",
       "[14] \"Employer.Name\"                           \n",
       "[15] \"Size.of.organisation..Primary.care.only.\"\n",
       "[16] \"Specialties..Hospital.only.\"             \n",
       "[17] \"Skilled.worker.visa\"                     \n",
       "[18] \"Number.of.Licences\"                      \n",
       "[19] \"Salary....\"                              \n",
       "[20] \"Training.Provider\"                       \n",
       "[21] \"Employer.website\"                        \n",
       "[22] \"Hours.per.Week\"                          \n",
       "[23] \"ProgrammeNumber\"                         \n",
       "[24] \"ProgrammeName\"                           \n",
       "[25] \"ICS.Name\"                                \n",
       "[26] \"Pharmacy.Programme.Number\"               \n",
       "[27] \"Number.of.Placements..3.months.or.more.\" \n",
       "[28] \"Practice.Placement.Setting.1\"            \n",
       "[29] \"Length.of.Placement.1..3.months.or.more.\"\n",
       "[30] \"Practice.Placement.Setting.2\"            \n",
       "[31] \"Length.of.Placement.2..3.months.or.more.\"\n",
       "[32] \"Practice.Placement.Setting.3\"            \n",
       "[33] \"Length.of.Placement.3..3.months.or.more.\"\n",
       "[34] \"Practice.Placement.Setting.4\"            \n",
       "[35] \"Length.of.Placement.4..3.months.or.more.\"\n",
       "[36] \"Placement.1..SystemID\"                   \n",
       "[37] \"Placement.2..SystemID\"                   \n",
       "[38] \"Placement.3..SystemID\"                   \n",
       "[39] \"Placement.4..SystemID\"                   "
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       "<ol class=list-inline><li>'Current.Assigned.Rank'</li><li>'Preference'</li><li>'Employer.Name'</li><li>'Programme.Title'</li><li>'Programme.Description'</li><li>'Region'</li><li>'Area.Sector.'</li><li>'Employer.Type'</li><li>'Size.of.Organisation'</li><li>'Specialties'</li><li>'Skilled.worker.visa'</li><li>'No.of.Licences'</li><li>'Number.of.Placements'</li><li>'Places.Available'</li><li>'Salary'</li><li>'Training.Provider'</li><li>'Employer.Website'</li><li>'Hours.Per.Week'</li><li>'Setting.1'</li><li>'Length.1'</li><li>'Setting.2'</li><li>'Length.2'</li><li>'Setting.3'</li><li>'Length.3'</li><li>'Setting.4'</li><li>'Length.4'</li><li>'Programme.Name'</li><li>'Programme.Number'</li><li>'Tags'</li></ol>\n"
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      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Current.Assigned.Rank'\n",
       "\\item 'Preference'\n",
       "\\item 'Employer.Name'\n",
       "\\item 'Programme.Title'\n",
       "\\item 'Programme.Description'\n",
       "\\item 'Region'\n",
       "\\item 'Area.Sector.'\n",
       "\\item 'Employer.Type'\n",
       "\\item 'Size.of.Organisation'\n",
       "\\item 'Specialties'\n",
       "\\item 'Skilled.worker.visa'\n",
       "\\item 'No.of.Licences'\n",
       "\\item 'Number.of.Placements'\n",
       "\\item 'Places.Available'\n",
       "\\item 'Salary'\n",
       "\\item 'Training.Provider'\n",
       "\\item 'Employer.Website'\n",
       "\\item 'Hours.Per.Week'\n",
       "\\item 'Setting.1'\n",
       "\\item 'Length.1'\n",
       "\\item 'Setting.2'\n",
       "\\item 'Length.2'\n",
       "\\item 'Setting.3'\n",
       "\\item 'Length.3'\n",
       "\\item 'Setting.4'\n",
       "\\item 'Length.4'\n",
       "\\item 'Programme.Name'\n",
       "\\item 'Programme.Number'\n",
       "\\item 'Tags'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Current.Assigned.Rank'\n",
       "2. 'Preference'\n",
       "3. 'Employer.Name'\n",
       "4. 'Programme.Title'\n",
       "5. 'Programme.Description'\n",
       "6. 'Region'\n",
       "7. 'Area.Sector.'\n",
       "8. 'Employer.Type'\n",
       "9. 'Size.of.Organisation'\n",
       "10. 'Specialties'\n",
       "11. 'Skilled.worker.visa'\n",
       "12. 'No.of.Licences'\n",
       "13. 'Number.of.Placements'\n",
       "14. 'Places.Available'\n",
       "15. 'Salary'\n",
       "16. 'Training.Provider'\n",
       "17. 'Employer.Website'\n",
       "18. 'Hours.Per.Week'\n",
       "19. 'Setting.1'\n",
       "20. 'Length.1'\n",
       "21. 'Setting.2'\n",
       "22. 'Length.2'\n",
       "23. 'Setting.3'\n",
       "24. 'Length.3'\n",
       "25. 'Setting.4'\n",
       "26. 'Length.4'\n",
       "27. 'Programme.Name'\n",
       "28. 'Programme.Number'\n",
       "29. 'Tags'\n",
       "\n",
       "\n"
      ],
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       " [1] \"Current.Assigned.Rank\" \"Preference\"            \"Employer.Name\"        \n",
       " [4] \"Programme.Title\"       \"Programme.Description\" \"Region\"               \n",
       " [7] \"Area.Sector.\"          \"Employer.Type\"         \"Size.of.Organisation\" \n",
       "[10] \"Specialties\"           \"Skilled.worker.visa\"   \"No.of.Licences\"       \n",
       "[13] \"Number.of.Placements\"  \"Places.Available\"      \"Salary\"               \n",
       "[16] \"Training.Provider\"     \"Employer.Website\"      \"Hours.Per.Week\"       \n",
       "[19] \"Setting.1\"             \"Length.1\"              \"Setting.2\"            \n",
       "[22] \"Length.2\"              \"Setting.3\"             \"Length.3\"             \n",
       "[25] \"Setting.4\"             \"Length.4\"              \"Programme.Name\"       \n",
       "[28] \"Programme.Number\"      \"Tags\"                 "
      ]
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      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Preference'</li><li>'Employer.Name'</li><li>'Programme.Title'</li><li>'Programme.Description'</li><li>'Region'</li><li>'Area.Sector.'</li><li>'Employer.Type'</li><li>'Size.of.Organisation'</li><li>'Specialties'</li><li>'Skilled.worker.visa'</li><li>'No.of.Licences'</li><li>'Number.of.Placements'</li><li>'Places.Available'</li><li>'Salary'</li><li>'Training.Provider'</li><li>'Employer.Website'</li><li>'Hours.Per.Week'</li><li>'Setting.1'</li><li>'Length.1'</li><li>'Setting.2'</li><li>'Length.2'</li><li>'Setting.3'</li><li>'Length.3'</li><li>'Setting.4'</li><li>'Length.4'</li><li>'Programme.Name'</li><li>'Programme.Number'</li><li>'Tags'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Preference'\n",
       "\\item 'Employer.Name'\n",
       "\\item 'Programme.Title'\n",
       "\\item 'Programme.Description'\n",
       "\\item 'Region'\n",
       "\\item 'Area.Sector.'\n",
       "\\item 'Employer.Type'\n",
       "\\item 'Size.of.Organisation'\n",
       "\\item 'Specialties'\n",
       "\\item 'Skilled.worker.visa'\n",
       "\\item 'No.of.Licences'\n",
       "\\item 'Number.of.Placements'\n",
       "\\item 'Places.Available'\n",
       "\\item 'Salary'\n",
       "\\item 'Training.Provider'\n",
       "\\item 'Employer.Website'\n",
       "\\item 'Hours.Per.Week'\n",
       "\\item 'Setting.1'\n",
       "\\item 'Length.1'\n",
       "\\item 'Setting.2'\n",
       "\\item 'Length.2'\n",
       "\\item 'Setting.3'\n",
       "\\item 'Length.3'\n",
       "\\item 'Setting.4'\n",
       "\\item 'Length.4'\n",
       "\\item 'Programme.Name'\n",
       "\\item 'Programme.Number'\n",
       "\\item 'Tags'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Preference'\n",
       "2. 'Employer.Name'\n",
       "3. 'Programme.Title'\n",
       "4. 'Programme.Description'\n",
       "5. 'Region'\n",
       "6. 'Area.Sector.'\n",
       "7. 'Employer.Type'\n",
       "8. 'Size.of.Organisation'\n",
       "9. 'Specialties'\n",
       "10. 'Skilled.worker.visa'\n",
       "11. 'No.of.Licences'\n",
       "12. 'Number.of.Placements'\n",
       "13. 'Places.Available'\n",
       "14. 'Salary'\n",
       "15. 'Training.Provider'\n",
       "16. 'Employer.Website'\n",
       "17. 'Hours.Per.Week'\n",
       "18. 'Setting.1'\n",
       "19. 'Length.1'\n",
       "20. 'Setting.2'\n",
       "21. 'Length.2'\n",
       "22. 'Setting.3'\n",
       "23. 'Length.3'\n",
       "24. 'Setting.4'\n",
       "25. 'Length.4'\n",
       "26. 'Programme.Name'\n",
       "27. 'Programme.Number'\n",
       "28. 'Tags'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Preference\"            \"Employer.Name\"         \"Programme.Title\"      \n",
       " [4] \"Programme.Description\" \"Region\"                \"Area.Sector.\"         \n",
       " [7] \"Employer.Type\"         \"Size.of.Organisation\"  \"Specialties\"          \n",
       "[10] \"Skilled.worker.visa\"   \"No.of.Licences\"        \"Number.of.Placements\" \n",
       "[13] \"Places.Available\"      \"Salary\"                \"Training.Provider\"    \n",
       "[16] \"Employer.Website\"      \"Hours.Per.Week\"        \"Setting.1\"            \n",
       "[19] \"Length.1\"              \"Setting.2\"             \"Length.2\"             \n",
       "[22] \"Setting.3\"             \"Length.3\"              \"Setting.4\"            \n",
       "[25] \"Length.4\"              \"Programme.Name\"        \"Programme.Number\"     \n",
       "[28] \"Tags\"                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colnames(OD2526)\n",
    "colnames(OD2425)\n",
    "colnames(OD2324)\n",
    "colnames(OD2223)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Do not need the following columns from 2526 data: \n",
    "\n",
    "'Programme.SystemID', 'Recruitment.Office', 'Post.Type', 'Abbreviation', 'Start.Date','Employer.website', 'ProgrammeNumber', 'ProgrammeName', 'Pharmacy.Programme.Number', 'Length.of.Placement.Rotation.1..weeks.', 'Length.of.Placement.Rotation.2..weeks', 'Length.of.Placement.Rotation.3..weeks.','Length.of.Placement.Rotation.4..weeks.','Placement.Rotation.1..SystemID','Placement.Rotation.2..SystemID','Placement.Rotation.3..SystemID','Placement.Rotation.4..SystemID'\n",
    "\n",
    "- Do not need the following columns from 2425 data:\n",
    "\n",
    "'Programme.SystemID','Recruitment.Office','Post.Type','Abbreviation','Start.Date','Employer.website','ProgrammeNumber','ProgrammeName','Pharmacy.Programme.Number','Placement.4..SystemID','Placement.3..SystemID','Placement.2..SystemID','Placement.1..SystemID','Length.of.Placement.4..3.months.or.more.','Length.of.Placement.2..3.months.or.more.','Length.of.Placement.1..3.months.or.more.','Length.of.Placement.3..3.months.or.more.'\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Region'</li><li>'Sub.Region'</li><li>'Sector'</li><li>'Programme.Preference'</li><li>'Programme.Title'</li><li>'Programme.Description'</li><li>'Places.Available'</li><li>'Employer.Type'</li><li>'Employer.Name'</li><li>'Size.of.organisation..Primary.care.only.'</li><li>'Specialties..Hospital.only.'</li><li>'Skilled.worker.visa'</li><li>'Number.of.Licences'</li><li>'Salary....'</li><li>'Training.Provider'</li><li>'Hours.per.Week'</li><li>'ICB.Name'</li><li>'Number.of.Placements.Rotations'</li><li>'Practice.Placement.Rotation.Setting.1'</li><li>'Practice.Placement.Rotation.Setting.2'</li><li>'Practice.Placement.Rotation.Setting.3'</li><li>'Practice.Placement.Rotation.Setting.4'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Region'\n",
       "\\item 'Sub.Region'\n",
       "\\item 'Sector'\n",
       "\\item 'Programme.Preference'\n",
       "\\item 'Programme.Title'\n",
       "\\item 'Programme.Description'\n",
       "\\item 'Places.Available'\n",
       "\\item 'Employer.Type'\n",
       "\\item 'Employer.Name'\n",
       "\\item 'Size.of.organisation..Primary.care.only.'\n",
       "\\item 'Specialties..Hospital.only.'\n",
       "\\item 'Skilled.worker.visa'\n",
       "\\item 'Number.of.Licences'\n",
       "\\item 'Salary....'\n",
       "\\item 'Training.Provider'\n",
       "\\item 'Hours.per.Week'\n",
       "\\item 'ICB.Name'\n",
       "\\item 'Number.of.Placements.Rotations'\n",
       "\\item 'Practice.Placement.Rotation.Setting.1'\n",
       "\\item 'Practice.Placement.Rotation.Setting.2'\n",
       "\\item 'Practice.Placement.Rotation.Setting.3'\n",
       "\\item 'Practice.Placement.Rotation.Setting.4'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Region'\n",
       "2. 'Sub.Region'\n",
       "3. 'Sector'\n",
       "4. 'Programme.Preference'\n",
       "5. 'Programme.Title'\n",
       "6. 'Programme.Description'\n",
       "7. 'Places.Available'\n",
       "8. 'Employer.Type'\n",
       "9. 'Employer.Name'\n",
       "10. 'Size.of.organisation..Primary.care.only.'\n",
       "11. 'Specialties..Hospital.only.'\n",
       "12. 'Skilled.worker.visa'\n",
       "13. 'Number.of.Licences'\n",
       "14. 'Salary....'\n",
       "15. 'Training.Provider'\n",
       "16. 'Hours.per.Week'\n",
       "17. 'ICB.Name'\n",
       "18. 'Number.of.Placements.Rotations'\n",
       "19. 'Practice.Placement.Rotation.Setting.1'\n",
       "20. 'Practice.Placement.Rotation.Setting.2'\n",
       "21. 'Practice.Placement.Rotation.Setting.3'\n",
       "22. 'Practice.Placement.Rotation.Setting.4'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Region\"                                  \n",
       " [2] \"Sub.Region\"                              \n",
       " [3] \"Sector\"                                  \n",
       " [4] \"Programme.Preference\"                    \n",
       " [5] \"Programme.Title\"                         \n",
       " [6] \"Programme.Description\"                   \n",
       " [7] \"Places.Available\"                        \n",
       " [8] \"Employer.Type\"                           \n",
       " [9] \"Employer.Name\"                           \n",
       "[10] \"Size.of.organisation..Primary.care.only.\"\n",
       "[11] \"Specialties..Hospital.only.\"             \n",
       "[12] \"Skilled.worker.visa\"                     \n",
       "[13] \"Number.of.Licences\"                      \n",
       "[14] \"Salary....\"                              \n",
       "[15] \"Training.Provider\"                       \n",
       "[16] \"Hours.per.Week\"                          \n",
       "[17] \"ICB.Name\"                                \n",
       "[18] \"Number.of.Placements.Rotations\"          \n",
       "[19] \"Practice.Placement.Rotation.Setting.1\"   \n",
       "[20] \"Practice.Placement.Rotation.Setting.2\"   \n",
       "[21] \"Practice.Placement.Rotation.Setting.3\"   \n",
       "[22] \"Practice.Placement.Rotation.Setting.4\"   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Region'</li><li>'Sub.Region'</li><li>'Sector'</li><li>'Programme.Preference'</li><li>'Programme.Title'</li><li>'Programme.Description'</li><li>'Places.Available'</li><li>'Employer.Type'</li><li>'Employer.Name'</li><li>'Size.of.organisation..Primary.care.only.'</li><li>'Specialties..Hospital.only.'</li><li>'Skilled.worker.visa'</li><li>'Number.of.Licences'</li><li>'Salary....'</li><li>'Training.Provider'</li><li>'Hours.per.Week'</li><li>'ICS.Name'</li><li>'Number.of.Placements..3.months.or.more.'</li><li>'Practice.Placement.Setting.1'</li><li>'Practice.Placement.Setting.2'</li><li>'Practice.Placement.Setting.3'</li><li>'Practice.Placement.Setting.4'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Region'\n",
       "\\item 'Sub.Region'\n",
       "\\item 'Sector'\n",
       "\\item 'Programme.Preference'\n",
       "\\item 'Programme.Title'\n",
       "\\item 'Programme.Description'\n",
       "\\item 'Places.Available'\n",
       "\\item 'Employer.Type'\n",
       "\\item 'Employer.Name'\n",
       "\\item 'Size.of.organisation..Primary.care.only.'\n",
       "\\item 'Specialties..Hospital.only.'\n",
       "\\item 'Skilled.worker.visa'\n",
       "\\item 'Number.of.Licences'\n",
       "\\item 'Salary....'\n",
       "\\item 'Training.Provider'\n",
       "\\item 'Hours.per.Week'\n",
       "\\item 'ICS.Name'\n",
       "\\item 'Number.of.Placements..3.months.or.more.'\n",
       "\\item 'Practice.Placement.Setting.1'\n",
       "\\item 'Practice.Placement.Setting.2'\n",
       "\\item 'Practice.Placement.Setting.3'\n",
       "\\item 'Practice.Placement.Setting.4'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Region'\n",
       "2. 'Sub.Region'\n",
       "3. 'Sector'\n",
       "4. 'Programme.Preference'\n",
       "5. 'Programme.Title'\n",
       "6. 'Programme.Description'\n",
       "7. 'Places.Available'\n",
       "8. 'Employer.Type'\n",
       "9. 'Employer.Name'\n",
       "10. 'Size.of.organisation..Primary.care.only.'\n",
       "11. 'Specialties..Hospital.only.'\n",
       "12. 'Skilled.worker.visa'\n",
       "13. 'Number.of.Licences'\n",
       "14. 'Salary....'\n",
       "15. 'Training.Provider'\n",
       "16. 'Hours.per.Week'\n",
       "17. 'ICS.Name'\n",
       "18. 'Number.of.Placements..3.months.or.more.'\n",
       "19. 'Practice.Placement.Setting.1'\n",
       "20. 'Practice.Placement.Setting.2'\n",
       "21. 'Practice.Placement.Setting.3'\n",
       "22. 'Practice.Placement.Setting.4'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Region\"                                  \n",
       " [2] \"Sub.Region\"                              \n",
       " [3] \"Sector\"                                  \n",
       " [4] \"Programme.Preference\"                    \n",
       " [5] \"Programme.Title\"                         \n",
       " [6] \"Programme.Description\"                   \n",
       " [7] \"Places.Available\"                        \n",
       " [8] \"Employer.Type\"                           \n",
       " [9] \"Employer.Name\"                           \n",
       "[10] \"Size.of.organisation..Primary.care.only.\"\n",
       "[11] \"Specialties..Hospital.only.\"             \n",
       "[12] \"Skilled.worker.visa\"                     \n",
       "[13] \"Number.of.Licences\"                      \n",
       "[14] \"Salary....\"                              \n",
       "[15] \"Training.Provider\"                       \n",
       "[16] \"Hours.per.Week\"                          \n",
       "[17] \"ICS.Name\"                                \n",
       "[18] \"Number.of.Placements..3.months.or.more.\" \n",
       "[19] \"Practice.Placement.Setting.1\"            \n",
       "[20] \"Practice.Placement.Setting.2\"            \n",
       "[21] \"Practice.Placement.Setting.3\"            \n",
       "[22] \"Practice.Placement.Setting.4\"            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "OD2526_irrelevant <- c('Programme.SystemID', 'Recruitment.Office', 'Post.Type', 'Abbreviation', 'Start.Date','Employer.website', 'ProgrammeNumber', 'ProgrammeName', 'Pharmacy.Programme.Number', 'Length.of.Placement.Rotation.1..weeks.', 'Length.of.Placement.Rotation.2..weeks.', 'Length.of.Placement.Rotation.3..weeks.','Length.of.Placement.Rotation.4..weeks.','Placement.Rotation.1..SystemID','Placement.Rotation.2..SystemID','Placement.Rotation.3..SystemID','Placement.Rotation.4..SystemID')\n",
    "OD2425_irrelevant <- c('Programme.SystemID','Recruitment.Office','Post.Type','Abbreviation','Start.Date','Employer.website','ProgrammeNumber','ProgrammeName','Pharmacy.Programme.Number','Placement.4..SystemID','Placement.3..SystemID','Placement.2..SystemID','Placement.1..SystemID','Length.of.Placement.4..3.months.or.more.','Length.of.Placement.2..3.months.or.more.','Length.of.Placement.1..3.months.or.more.','Length.of.Placement.3..3.months.or.more.')\n",
    "\n",
    "OD2526_modified <- select(OD2526, -one_of(OD2526_irrelevant))\n",
    "OD2425_modified <- select(OD2425, -one_of(OD2425_irrelevant))\n",
    "\n",
    "colnames(OD2526_modified)\n",
    "colnames(OD2425_modified)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "# Changing column names to match the 2022-2023 and 2023-2024 datasets and improve readability\n",
    "# Resume\n",
    "\n",
    "OD2526_modified <- OD2526_modified %>%\n",
    "  rename(\n",
    "    Region = Region,\n",
    "    SubRegion = Sub.Region,\n",
    "    Sector = Sector,\n",
    "    ProgramPreference = Programme.Preference,\n",
    "    ProgramTitle = Programme.Title,\n",
    "    ProgramDescription = Programme.Description,\n",
    "    AvailableSlots = Places.Available,\n",
    "    EmployerType = Employer.Type,\n",
    "    EmployerName = Employer.Name,\n",
    "    OrgSizePrimaryCareOnly = Size.of.organisation..Primary.care.only.,\n",
    "    HospitalSpecialties = Specialties..Hospital.only.,\n",
    "    SkilledWorkerVisa = Skilled.worker.visa,\n",
    "    LicenseCount = Number.of.Licences,\n",
    "    Salary = Salary....,\n",
    "    TrainingProvider = Training.Provider,\n",
    "    WeeklyHours = Hours.per.Week,\n",
    "    ICBName = ICB.Name,\n",
    "    PlacementRotationCount = Number.of.Placements.Rotations,\n",
    "    RotationSetting1 = Practice.Placement.Rotation.Setting.1,\n",
    "    RotationSetting2 = Practice.Placement.Rotation.Setting.2,\n",
    "    RotationSetting3 = Practice.Placement.Rotation.Setting.3,\n",
    "    RotationSetting4 = Practice.Placement.Rotation.Setting.4\n",
    "  )\n",
    "\n",
    "OD2425_modified <- OD2425_modified %>%\n",
    "  rename(\n",
    "    SubRegion = Sub.Region,\n",
    "    ProgramPreference = Programme.Preference,\n",
    "    ProgramTitle = Programme.Title,\n",
    "    ProgramDescription = Programme.Description,\n",
    "    AvailableSlots = Places.Available,\n",
    "    EmployerType = Employer.Type,\n",
    "    EmployerName = Employer.Name,\n",
    "    OrgSizePrimaryCareOnly = Size.of.organisation..Primary.care.only.,\n",
    "    HospitalSpecialties = Specialties..Hospital.only.,\n",
    "    SkilledWorkerVisa = Skilled.worker.visa,\n",
    "    LicenseCount = Number.of.Licences,\n",
    "    Salary = Salary....,\n",
    "    TrainingProvider = Training.Provider,\n",
    "    WeeklyHours = Hours.per.Week,\n",
    "    ICSName = ICS.Name,\n",
    "    PlacementCount = Number.of.Placements..3.months.or.more.,\n",
    "    PlacementSetting1 = Practice.Placement.Setting.1,\n",
    "    PlacementSetting2 = Practice.Placement.Setting.2,\n",
    "    PlacementSetting3 = Practice.Placement.Setting.3,\n",
    "    PlacementSetting4 = Practice.Placement.Setting.4\n",
    "  )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Region'</li><li>'SubRegion'</li><li>'Sector'</li><li>'ProgramPreference'</li><li>'ProgramTitle'</li><li>'ProgramDescription'</li><li>'AvailableSlots'</li><li>'EmployerType'</li><li>'EmployerName'</li><li>'OrgSizePrimaryCareOnly'</li><li>'HospitalSpecialties'</li><li>'SkilledWorkerVisa'</li><li>'LicenseCount'</li><li>'Salary'</li><li>'TrainingProvider'</li><li>'WeeklyHours'</li><li>'ICBName'</li><li>'PlacementRotationCount'</li><li>'RotationSetting1'</li><li>'RotationSetting2'</li><li>'RotationSetting3'</li><li>'RotationSetting4'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Region'\n",
       "\\item 'SubRegion'\n",
       "\\item 'Sector'\n",
       "\\item 'ProgramPreference'\n",
       "\\item 'ProgramTitle'\n",
       "\\item 'ProgramDescription'\n",
       "\\item 'AvailableSlots'\n",
       "\\item 'EmployerType'\n",
       "\\item 'EmployerName'\n",
       "\\item 'OrgSizePrimaryCareOnly'\n",
       "\\item 'HospitalSpecialties'\n",
       "\\item 'SkilledWorkerVisa'\n",
       "\\item 'LicenseCount'\n",
       "\\item 'Salary'\n",
       "\\item 'TrainingProvider'\n",
       "\\item 'WeeklyHours'\n",
       "\\item 'ICBName'\n",
       "\\item 'PlacementRotationCount'\n",
       "\\item 'RotationSetting1'\n",
       "\\item 'RotationSetting2'\n",
       "\\item 'RotationSetting3'\n",
       "\\item 'RotationSetting4'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Region'\n",
       "2. 'SubRegion'\n",
       "3. 'Sector'\n",
       "4. 'ProgramPreference'\n",
       "5. 'ProgramTitle'\n",
       "6. 'ProgramDescription'\n",
       "7. 'AvailableSlots'\n",
       "8. 'EmployerType'\n",
       "9. 'EmployerName'\n",
       "10. 'OrgSizePrimaryCareOnly'\n",
       "11. 'HospitalSpecialties'\n",
       "12. 'SkilledWorkerVisa'\n",
       "13. 'LicenseCount'\n",
       "14. 'Salary'\n",
       "15. 'TrainingProvider'\n",
       "16. 'WeeklyHours'\n",
       "17. 'ICBName'\n",
       "18. 'PlacementRotationCount'\n",
       "19. 'RotationSetting1'\n",
       "20. 'RotationSetting2'\n",
       "21. 'RotationSetting3'\n",
       "22. 'RotationSetting4'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Region\"                 \"SubRegion\"              \"Sector\"                \n",
       " [4] \"ProgramPreference\"      \"ProgramTitle\"           \"ProgramDescription\"    \n",
       " [7] \"AvailableSlots\"         \"EmployerType\"           \"EmployerName\"          \n",
       "[10] \"OrgSizePrimaryCareOnly\" \"HospitalSpecialties\"    \"SkilledWorkerVisa\"     \n",
       "[13] \"LicenseCount\"           \"Salary\"                 \"TrainingProvider\"      \n",
       "[16] \"WeeklyHours\"            \"ICBName\"                \"PlacementRotationCount\"\n",
       "[19] \"RotationSetting1\"       \"RotationSetting2\"       \"RotationSetting3\"      \n",
       "[22] \"RotationSetting4\"      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Region'</li><li>'SubRegion'</li><li>'Sector'</li><li>'ProgramPreference'</li><li>'ProgramTitle'</li><li>'ProgramDescription'</li><li>'AvailableSlots'</li><li>'EmployerType'</li><li>'EmployerName'</li><li>'OrgSizePrimaryCareOnly'</li><li>'HospitalSpecialties'</li><li>'SkilledWorkerVisa'</li><li>'LicenseCount'</li><li>'Salary'</li><li>'TrainingProvider'</li><li>'WeeklyHours'</li><li>'ICSName'</li><li>'PlacementCount'</li><li>'PlacementSetting1'</li><li>'PlacementSetting2'</li><li>'PlacementSetting3'</li><li>'PlacementSetting4'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Region'\n",
       "\\item 'SubRegion'\n",
       "\\item 'Sector'\n",
       "\\item 'ProgramPreference'\n",
       "\\item 'ProgramTitle'\n",
       "\\item 'ProgramDescription'\n",
       "\\item 'AvailableSlots'\n",
       "\\item 'EmployerType'\n",
       "\\item 'EmployerName'\n",
       "\\item 'OrgSizePrimaryCareOnly'\n",
       "\\item 'HospitalSpecialties'\n",
       "\\item 'SkilledWorkerVisa'\n",
       "\\item 'LicenseCount'\n",
       "\\item 'Salary'\n",
       "\\item 'TrainingProvider'\n",
       "\\item 'WeeklyHours'\n",
       "\\item 'ICSName'\n",
       "\\item 'PlacementCount'\n",
       "\\item 'PlacementSetting1'\n",
       "\\item 'PlacementSetting2'\n",
       "\\item 'PlacementSetting3'\n",
       "\\item 'PlacementSetting4'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Region'\n",
       "2. 'SubRegion'\n",
       "3. 'Sector'\n",
       "4. 'ProgramPreference'\n",
       "5. 'ProgramTitle'\n",
       "6. 'ProgramDescription'\n",
       "7. 'AvailableSlots'\n",
       "8. 'EmployerType'\n",
       "9. 'EmployerName'\n",
       "10. 'OrgSizePrimaryCareOnly'\n",
       "11. 'HospitalSpecialties'\n",
       "12. 'SkilledWorkerVisa'\n",
       "13. 'LicenseCount'\n",
       "14. 'Salary'\n",
       "15. 'TrainingProvider'\n",
       "16. 'WeeklyHours'\n",
       "17. 'ICSName'\n",
       "18. 'PlacementCount'\n",
       "19. 'PlacementSetting1'\n",
       "20. 'PlacementSetting2'\n",
       "21. 'PlacementSetting3'\n",
       "22. 'PlacementSetting4'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Region\"                 \"SubRegion\"              \"Sector\"                \n",
       " [4] \"ProgramPreference\"      \"ProgramTitle\"           \"ProgramDescription\"    \n",
       " [7] \"AvailableSlots\"         \"EmployerType\"           \"EmployerName\"          \n",
       "[10] \"OrgSizePrimaryCareOnly\" \"HospitalSpecialties\"    \"SkilledWorkerVisa\"     \n",
       "[13] \"LicenseCount\"           \"Salary\"                 \"TrainingProvider\"      \n",
       "[16] \"WeeklyHours\"            \"ICSName\"                \"PlacementCount\"        \n",
       "[19] \"PlacementSetting1\"      \"PlacementSetting2\"      \"PlacementSetting3\"     \n",
       "[22] \"PlacementSetting4\"     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Current.Assigned.Rank'</li><li>'Preference'</li><li>'Employer.Name'</li><li>'Programme.Title'</li><li>'Programme.Description'</li><li>'Region'</li><li>'Area.Sector.'</li><li>'Employer.Type'</li><li>'Size.of.Organisation'</li><li>'Specialties'</li><li>'Skilled.worker.visa'</li><li>'No.of.Licences'</li><li>'Number.of.Placements'</li><li>'Places.Available'</li><li>'Salary'</li><li>'Training.Provider'</li><li>'Employer.Website'</li><li>'Hours.Per.Week'</li><li>'Setting.1'</li><li>'Length.1'</li><li>'Setting.2'</li><li>'Length.2'</li><li>'Setting.3'</li><li>'Length.3'</li><li>'Setting.4'</li><li>'Length.4'</li><li>'Programme.Name'</li><li>'Programme.Number'</li><li>'Tags'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Current.Assigned.Rank'\n",
       "\\item 'Preference'\n",
       "\\item 'Employer.Name'\n",
       "\\item 'Programme.Title'\n",
       "\\item 'Programme.Description'\n",
       "\\item 'Region'\n",
       "\\item 'Area.Sector.'\n",
       "\\item 'Employer.Type'\n",
       "\\item 'Size.of.Organisation'\n",
       "\\item 'Specialties'\n",
       "\\item 'Skilled.worker.visa'\n",
       "\\item 'No.of.Licences'\n",
       "\\item 'Number.of.Placements'\n",
       "\\item 'Places.Available'\n",
       "\\item 'Salary'\n",
       "\\item 'Training.Provider'\n",
       "\\item 'Employer.Website'\n",
       "\\item 'Hours.Per.Week'\n",
       "\\item 'Setting.1'\n",
       "\\item 'Length.1'\n",
       "\\item 'Setting.2'\n",
       "\\item 'Length.2'\n",
       "\\item 'Setting.3'\n",
       "\\item 'Length.3'\n",
       "\\item 'Setting.4'\n",
       "\\item 'Length.4'\n",
       "\\item 'Programme.Name'\n",
       "\\item 'Programme.Number'\n",
       "\\item 'Tags'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Current.Assigned.Rank'\n",
       "2. 'Preference'\n",
       "3. 'Employer.Name'\n",
       "4. 'Programme.Title'\n",
       "5. 'Programme.Description'\n",
       "6. 'Region'\n",
       "7. 'Area.Sector.'\n",
       "8. 'Employer.Type'\n",
       "9. 'Size.of.Organisation'\n",
       "10. 'Specialties'\n",
       "11. 'Skilled.worker.visa'\n",
       "12. 'No.of.Licences'\n",
       "13. 'Number.of.Placements'\n",
       "14. 'Places.Available'\n",
       "15. 'Salary'\n",
       "16. 'Training.Provider'\n",
       "17. 'Employer.Website'\n",
       "18. 'Hours.Per.Week'\n",
       "19. 'Setting.1'\n",
       "20. 'Length.1'\n",
       "21. 'Setting.2'\n",
       "22. 'Length.2'\n",
       "23. 'Setting.3'\n",
       "24. 'Length.3'\n",
       "25. 'Setting.4'\n",
       "26. 'Length.4'\n",
       "27. 'Programme.Name'\n",
       "28. 'Programme.Number'\n",
       "29. 'Tags'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Current.Assigned.Rank\" \"Preference\"            \"Employer.Name\"        \n",
       " [4] \"Programme.Title\"       \"Programme.Description\" \"Region\"               \n",
       " [7] \"Area.Sector.\"          \"Employer.Type\"         \"Size.of.Organisation\" \n",
       "[10] \"Specialties\"           \"Skilled.worker.visa\"   \"No.of.Licences\"       \n",
       "[13] \"Number.of.Placements\"  \"Places.Available\"      \"Salary\"               \n",
       "[16] \"Training.Provider\"     \"Employer.Website\"      \"Hours.Per.Week\"       \n",
       "[19] \"Setting.1\"             \"Length.1\"              \"Setting.2\"            \n",
       "[22] \"Length.2\"              \"Setting.3\"             \"Length.3\"             \n",
       "[25] \"Setting.4\"             \"Length.4\"              \"Programme.Name\"       \n",
       "[28] \"Programme.Number\"      \"Tags\"                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colnames(OD2526_modified)\n",
    "colnames(OD2425_modified)\n",
    "colnames(OD2324)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 1 × 1</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>mean(WeeklyHours)</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>38.74936</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 1 × 1\n",
       "\\begin{tabular}{l}\n",
       " mean(WeeklyHours)\\\\\n",
       " <dbl>\\\\\n",
       "\\hline\n",
       "\t 38.74936\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 1 × 1\n",
       "\n",
       "| mean(WeeklyHours) &lt;dbl&gt; |\n",
       "|---|\n",
       "| 38.74936 |\n",
       "\n"
      ],
      "text/plain": [
       "  mean(WeeklyHours)\n",
       "1 38.74936         "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 1 × 1</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>mean(Salary)</th></tr>\n",
       "\t<tr><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>25588.76</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
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      "text/latex": [
       "A data.frame: 1 × 1\n",
       "\\begin{tabular}{l}\n",
       " mean(Salary)\\\\\n",
       " <dbl>\\\\\n",
       "\\hline\n",
       "\t 25588.76\\\\\n",
       "\\end{tabular}\n"
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      "text/markdown": [
       "\n",
       "A data.frame: 1 × 1\n",
       "\n",
       "| mean(Salary) &lt;dbl&gt; |\n",
       "|---|\n",
       "| 25588.76 |\n",
       "\n"
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      "text/plain": [
       "  mean(Salary)\n",
       "1 25588.76    "
      ]
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 1 × 1</caption>\n",
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       "\t<tr><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>38.58384</td></tr>\n",
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      "text/latex": [
       "A data.frame: 1 × 1\n",
       "\\begin{tabular}{l}\n",
       " mean(WeeklyHours)\\\\\n",
       " <dbl>\\\\\n",
       "\\hline\n",
       "\t 38.58384\\\\\n",
       "\\end{tabular}\n"
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      "text/markdown": [
       "\n",
       "A data.frame: 1 × 1\n",
       "\n",
       "| mean(WeeklyHours) &lt;dbl&gt; |\n",
       "|---|\n",
       "| 38.58384 |\n",
       "\n"
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       "  mean(WeeklyHours)\n",
       "1 38.58384         "
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 1 × 1</caption>\n",
       "<thead>\n",
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       "\t<tr><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>23314.93</td></tr>\n",
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       "</table>\n"
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      "text/latex": [
       "A data.frame: 1 × 1\n",
       "\\begin{tabular}{l}\n",
       " mean(Salary)\\\\\n",
       " <dbl>\\\\\n",
       "\\hline\n",
       "\t 23314.93\\\\\n",
       "\\end{tabular}\n"
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      "text/markdown": [
       "\n",
       "A data.frame: 1 × 1\n",
       "\n",
       "| mean(Salary) &lt;dbl&gt; |\n",
       "|---|\n",
       "| 23314.93 |\n",
       "\n"
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      "text/plain": [
       "  mean(Salary)\n",
       "1 23314.93    "
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "23200.32"
      ],
      "text/latex": [
       "23200.32"
      ],
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       "23200.32"
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      "text/plain": [
       "[1] 23200.32"
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     "metadata": {},
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   ],
   "source": [
    "# Summary statistics for the 2025-2026 and 2024-2025 datasets\n",
    "average_working_hours_in_2526 <- OD2526_modified %>%\n",
    "    summarise(mean(WeeklyHours))\n",
    "\n",
    "average_working_hours_in_2526\n",
    "\n",
    "average_salary_in_2526 <- OD2526_modified %>%\n",
    "    summarise(mean(Salary))\n",
    "\n",
    "average_salary_in_2526\n",
    "\n",
    "average_working_hours_in_2425 <- OD2425_modified %>%\n",
    "    summarise(mean(WeeklyHours))\n",
    "\n",
    "average_working_hours_in_2425\n",
    "\n",
    "average_salary_in_2425 <- OD2425_modified %>%\n",
    "    summarise(mean(Salary))\n",
    "\n",
    "average_salary_in_2425\n",
    "\n",
    "# UK national minimum wage from 1st April 2024 is £11.44 per hour for ages 21 and over\n",
    "\n",
    "UK_minimum_hourly_wage <- 11.44\n",
    "UK_minimum_salary <- UK_minimum_hourly_wage * 39 * 52\n",
    "UK_minimum_salary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“\u001b[1m\u001b[22mUsing `size` aesthetic for lines was deprecated in ggplot2 3.4.0.\n",
      "\u001b[36mℹ\u001b[39m Please use `linewidth` instead.”\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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+f8kll/jxOqaG9Oyzz6ZcUOOH6zgbjiPaTpVdZlK5b7TRRn56rSvkU+979eoVu5vZme/VnXfemW7Pp3zpuKZ1uIszqT/96U/pbOU7DqQnzHjjOiXyy/vxj3/cYRXVjNn8d6uY38Jsx95i99OOHFWNtdgyz9wmPiOAQOMKUMWuwLINJ+I6oLorYil3x8jXv87XJiBUm9EJnt67K3spHfjVjsJdafMH6Gi7lGwBUrHLCHnt2bNnyl2hT1177bUpnTip7ZTWpW046KCD2m35XXfd5ccVUsUnnIipuoXaTrjewlIPPPBA+odZ64ie2GULVkLj4HPOOccHAlqG673Pnxhrfv3QK+mE3d1B8nlzPZ2lPv3005S7Y+XHdbSt2dYZqmNp+a7nNN8mRVWw1GbE3THz6/jb3/7ml61/sv1Ip0e6N9EASe3RlDedYGv5OunSZ520ZzsZ1HJCOxe1l9FJsZahNkHhZFknMRoWUgiQdDKmAOr2229PKYBXnnVipvVmnvSHecOr9gOtS9OqnYDyqD+dfCgVk6dwAqJ9Tes/44wzfGDemQ5Lfvazn/m8qWxDCid5uQL3RRdd1M+TLYAKywivqn6nk1MFQZnTuztRfjlXXXWVn7wSAVK27dPKQnU+fWdVNtE/zeN6GwubkPO11O9KsceYbPtzCJC0b6pNmIIkWesvbLPacob9rBzLEISOZbLSsUgdA+j7pu9zCKo1Ll+ApHn0/VdAMcG1o8lM7g6YDzR0rFNydxlT7q6wv/D1hz/8wbd/0wWdf/zjH76DFq0z2gZR86jjAg0//vjjU7poonUqyNLFGg1XmzgdA5VK/V4pqNd+re+jjvv6vZGzjqXhO6JOZJTyHQf8RFn+Ud7DsVIGuljl7hyn3N2iLFN/N6jYfSzbsbfYZXTkWGyZf7clvEMAgWYQIEAqopR1FVFX+vRjFv7CiaraP+iAm5lclSD/o+uqXmWOSrkuw/1yXDem6XHZAqRilxGCBp38Zp5Q6gdDPe/ph00/nNEU7mS4KlvRwe3eu2pePt9afvTkXROGHzD55AuQdKdKnpluCix0J8RVbUuvO1e7io62taMASVd+w8lIWIlObpRvnQyFlO1HOozTazRACsODY/QEKdvJoKsO5denE7nMcoouWycfIYUAST07Zeb/iiuu8MvT3ZF8yVUL9NOqjU40FZuncAIiN1e9Krqokt6HAEUXD8IdLd1h1fJ1BTxXCsGFepvsKCmY1H6r5ckrmnTipxNLdQQSTuLLHSBl2z7lYerUqem7veo576yzzvJBr+5ohpNR3d0I+YrmO/N9Kd+VYo8x2fbnECDJNvMOivZV9TaocbqTolSOZbhqqX6ZumudeSxSz4Zan/7yBUjKj+4SatrzzjtPH9MpeOqCSkghKLv00kvDoPSrLhRpObq4EZL2LQUu+t5mHu+0f2uc5gnBWanfqy233NIvJ9sFCvdoAz/OVbNLHztyHQdCvnO9Kp/Z7kDpe/vrX//aX4DJnLfYfSzbsbfYZeRzLKbMM7eHzwgg0NgC7RuhuKM0KbvA//3f//n2Ce4KvbmqG75Ou/vh988scoGNbbPNNuZOwGIzuxMF37ZG7SSiye1Wvq6+hqkee0ep1GWoTY074Yst2l1FNHcC79fpApH0OLWLUv19tdtQG6COkur0K6l9RmY7JtVzj9al72g5qpvuTpLs5z//uW+/5U7+/ORqL/D3v//dG3c0f3Rctm2Njs98r2dXqZ1LNG2//fY+7+5kxrcrio6rxHt39dgvVnnJLCeN0P6m5K6G+9foPyrDzPyHtl3uZDs6aVHvO5unolaWMbHaQqntgjtZNH3H3B0pP4U78fWv2YzCIsI4tbfIldwJl2+35gJ33ybFXclPT6rvsb6jWrfaVLk7Celx5XqTa/u0fBcM+nZsavunNmV6VpOrtuif+aQ2du7ugqls3J3nTmcn23el1GNMrszoeTjRpH3VBbF+UKH7ZyHLULtPJbUTyzwWqV3JoEGD/PhC/nF3Tv1k2veiSTZK7kJWerALgvw+onZ7mUltI9VmUe0z1RZIaY011vC/Azp2uruXsVlcwJS2yfZboO96IUnfE7VRVHtHtTHNTMqXjrlqY/rOO+9kji7qs9qS/fvf//Z/rgaAf8aYytjdwTN358q341LbzWgqxz7WmWVkcyymzKPbwnsEEGh8gfiRuvG3t9NbqIfD6kQqBDw62VJDfdclse+EQY2D1YA0+mOtk66RI0faiy++mG6cq4au7uqWz084Aewoc6UsQ41/syX9KLgqF/4kVB0IKLmqWqYf6uhJQLZ5NUydBCipo4RsSet1VxizjYoNO//8832w5tpZmP7cFWZTkKIAST9m7u5SbPqOPuTa1lzzuGfiZB2lzgaUd5Wra0eTdZpyDXTVYfyicuVFwaqSu+LuX6P/ZGsEruBXqZD9Kbqs6PtS8+TuBpp7jlF0UQW/18UC1/W2f8Cke6aKqXOLzTffPD2/AiXtCzrZ1LTZghd1EqIUgqr0zN++kaEawqvDAHXgoU4fot/R008/3e/X+h501Jg/LPeVV17x+Q2fw6vy7e5qho/+Nd/2aSJ3F9Fcj3qx+cIHuaoTGFc91NydEHPVW8Ookl5zfVdKOcZky4Dym+27W8z+WegywsWaEHxl5sfdLfTH3szh2T67u6nm2gj5izUqX3XYoIBb5aL9W8GrkvZDXVBS5yEKOrIlHUuVFIiEDgC037o7xeaqw/qOYbRPqpMQvYaLQ5nf3WK+VzpuqVMCHU9czYZs2fIXwNRxjNap7e1scneRfOcseoC6Lna5KtLmqnGbHsTt7rL576teQyrHPlbKMnI5FlrmIf+8IoBA8wgQIBVQ1urVSneG1l133XZT6wdYJy+6C6IfV/1I6cpauAujHs50sh+udOpHVfPoTot6jrr88svbLTNzQKnLUMCRLelH3T3o1v+I6YdeJyO6MqcTRleFIdsssWHKj1Kuk1Etr5DkqgyZTkR0xVE9QelkQicj+nPVQHzgud566xWyKB9cFTThtxMp0M2Wwjbpx76QFE5sCpk2c5pwt1E/3tlSyEu4Ch2dRicJlUil5inXvpYvjzoh1FV47X+uKpnv4StbmWt/1YUH3X3IVnaufY5fVTZLXZhQcKQgylX/Mde+KNaznU5S9T3UCbz2R/2FpLs3SurRT3f0dAVe3xEdE1ybvTBZ+jXcyQoDCt2+MH2uV/WOpqS8djZlK6tSjzHZ8lKOfbPQZbi2cz4LrtpwtqxkDdSyTvjtQF080rFad5EUIOlEX98J9Y4YyjYc/xSERIPs6HLD3dzoccRVezPXLsvfSdK02t+0P+kilXryDBcnosvJVlbR8dH3+b67mrajY0p0Wbnea3vUS6B649R3MpoUFLtnlfk/3VXSXVBd+AoBUjn2sVKX0ZFjIWUe3U7eI4BAcwhQxa6Acna99ZhO2qInTpmz6apzuMKoLmNDUlez+sHVD4eurukET12v6oQwdOerK8wdpXIsI7p8BWmqIqirnOrqVSeeqg6iqjeFXD0PJ2uqTpEtqSpToUnV8Vw9fn/HRl3CXnPNNT4QVTWQQoK1QteTOV24e5c5PGyT7iQphbsVmVd2w3w6WSg1hTtwYZ2Zy1E35EpLLLFE5qiKfa5mnlStTd2V67ugKkiqWpYtONLGhpMxdfOemVSWujKvaj+6AxVN+s6p6quCTNeG0O9f2v+jSYGTvoMKsi677LLYn06QlXTRQ+NCtVTdKVbX85l/ulgSUjHbp26kFcjpu5gtuXYqfnCl9oVyH2OybUMlhoXvab7vUKHrVnf9CoR0Yq99QncUlcJJvt7r7q2OCwrKdGzv6M91KqNZ/J2/4447zs+nC0I61mm/1f6puy/h+JLvt8AvLMc/+b67mq2zxxRVfdYFvtCdfo6s+AsRGpf030LlsZAy13QkBBBoLgECpALKO9RdHjZsWIdTq9qCku4kKemkR+0GdGVNgYhrQBu7oqlASSn8OPoPGf+UYxkZi/Qfww++qgfq7o1SIdXrNJ2qVSjpOSeZyXW56589kjk887NOdHU19fe//316lH7gdYVfJ50yi1ZDTE9Upjc6Gc9MOmHROnWCpJNtJdXnV8rWbiJcTdX4Uk5sQtU63Z3IllyHCX5wCEizTVPuYdXKk+68qaqb9j99L1QFVXcNcyVdpFDS9ygzhWG6IxlNjz/+uL9Tq0BFJ7yhTVd0Gr3XM3p0IpftT/uo0v777+/Huwb8/rMCFV1QyPzTspSK3T5VeVXQpUAlWwptw3THodypUseYcucz2/JC9TW1CcpMatcV3DLH5fqsO5Bq+6U7U9of9MwifSdUNiHp7paCJAXdoYpfGKdX7W86jqnaZrgQo/1cxwgF0GovFYIZTa9qcQqYlDr6LfATdPCP7sDqDpGCoGxVnBVkh4t8pe5HuhOrtkY6Rusuaq5UT7+FhZR5ru1kOAIINK4AAVIBZavGwrpiqCoSunKmq9XRpHrq+jHU1UCdOLmezfxo/VAq6QcwVAXxA9w/+mFVXW0ljc+VyrGMbMvWj74aMCvPt912m6+2pBODQpJ7dpOvHqhqKOEHN8ynq+w64cqXVE3KdY9rOuHU3atoUlURGeuBg6FqRKjeUsiyo8vK9f6GG27wd/Ki41WGCnrUeD80pNbJkPKgqh3h7kGY58QTT8waGBWaV90hU2Nu3UHJDNh0giNLVeEpNHAN+erMa7XyJH/Xa6B/sKZOQkPVn1x51wmnykIPIo3eodRJsL6XGqcqPSFp/1EnIgrY1emC7lTlSrrrpO9Ctr/QtkV3VjU+BJC5lhWGF7t9roc0X+1P7fvkEU2q5qdqgdqvdBciXyp0/wvLqdQxJiy/kq/6bqj9ltqUqW1PSNqmY445xgcxYVihr6HhvgJq3V3M9v0L7cxUHtFqdFqH9kP3vCFfBTO0uwrGagMXTQqaDj/88HRg1NFvQXS+XO+VHwVZrrdLX0MgOp3uVClg08OZO7oYEZ0n872+p6qire1RcJrtIpke2KttUgoXF8P2J/G3UPkspMw1HQkBBJpIwB2gSQUIuCuAKXcipbpw/mGe7qp+yl1VTrkqFOnua/UcC1dNJrY0d+XRz6Pp1SWsa1+TclcQ/TMp3MmWH6cuakPK1s13scsIXV9n61o8rEev7iTOr1/b5H7QoqPyvndX/H134e5OT0rdaWtZ6l7aBZLpbonzdfPtGub79euZKa7Ti5S6SncBaPrhsS5ASOdDXT67YMFPr+fE6Hk7Sh1ta0fdfKus9DBTPatFD090nUP4Zav7b60rmtyJkh/ngjr/zBJ1wazuvdXtdOjqVs8fCSl0xa11uGqXKXdXKmuXxppebjJTd/HaFnWVfeqpp6bcVU0/XM/Liqaw7GxdamvfU1lqW/IlF/D5aTO7+dZ8xeTJnXD55biqTvlWmR4vX5W58uouKPjn/6ib7mx/7gQ1PV8oT3f13T9raciQIb5Ldi0ns7vlwYMH++W76nRZlxvWpWdwdZRK6ea71O3TQzS1Le4KfcrdXfPloG6I9R3Tdlx33XUdZTU9rpTvSrHHGBcU+Ly6wDG93tDNt7p6zpbc3Qc/jx4ToFSOZWg56p4/HJv1vXRtelIuAPBu4VlI7m6iJi0ouQAj/Yw6HXNc9b1287kT/vRDt12Vs9QFF1zgnzGnrsBVVvo+R7sWdz2E+m3XcNfDnH8AsLpwd516+PLWPq2yd3dD/bpK+V5pxunTp6e7sdexScdQdfntghq/fFeFNfY8rY6OA+02+tsB2r/CM+yUZ9eW1j9Tzt39TOl4ou3XcB3LXTXu9GKK3ceydfNd7DIKdSykzNMbwhsEEGgKAV0BJxUo4K7uplxbovSPp34E9KfnlOy5555Zf0hdWxr/XJUwrV51cqgfR/146ERNJ8jujoHPRbYAqdhldBQ0RDdVP3Q6+VKeFPAUm/S8Ij3gNPwguquLKXe1Pv1QyHwBkquGlNKJrLvK6vMQjFz1lZS7q9UuO3ogo9ah6RTIKHW0reGEWif8IYUHxeqZIDoJDUGXtsHdKYydPIR5dDLk7hb5gDDkUSdFMgvrd1VKwuQpnXS4q6u+XDW9nueU7WQwzPCvf/0rFYJlTa8TZHe3IusDX6sRIClfheap0BOQsK16dXctY+UdTLO96mGW0aQTvnAyrOl1wum6Bk/pYb/RpAsX2ZaXOczdZYjO1u59KQFSqdun74O+PwqsQz51bNC+ofIoJhX7XSn2GJNtf65VgCQXPfhYD1fWcUFBt56j5nprS1/4cHepi+HzF2BUBgosciV3dzKliyfR/VHz6LuvfSAz6cGtuvARylbHHle91D801t2N98Nd1Wc/Wynfq7A+lYN+R9ydxPS6XBu+lLs77B8OG6bTaykBkuZTQOHulKVcO9r0M5y0XTp2aZi2NTMVu49lC5CKXUYxjrrolq/MM7eJzwgg0LgCLdo0d1AgFSngggvfVaqqdxTSsYH7ITJVr1Bjc1UdKyWVYxnR9bqTHN+VtfIf6oxHxxf6Xo3bVR9dXaa6H/1CZ0tPp84i1MhaVevUBXGoVpeeIPJGu6s6RlBPeaEqUWR00W/Vtki956nXKbV76igpn2o3pu6/Vd8/X9KyVdVLvRW6E918k/vqPGqLoLyol6gkJFUxSlqe1L5H3bC7q+W+wXhoJ5YEr3LkQfu4vg/6Tqmrd7WRKCWV8l0p9zGmlHwXM4/2hY6OOe6Og+/8QvtwtN1PvnW4Cze+8wR10qBG/B0lOevYruq/aruo73uupCpm48eP98cFfc9VNbRSSVXt1OmHjj3qWKFSSWUgXx3v1AYvV4+CYf3l2MfKsYyQn/BaTJmHeXhFAIHGFSBAatyyzbtleuiknqmiXuRcVZ680zMBAgggkCQBtQvUMUxtSNRLYTSpnacet6B2QGq3VshFCs2vwEIXanTCr4sx+U74o+vkfX0KUOb1WW7kGoFKCrRWcuEsO3kCutKpRt+uqoLvWEKdJagxOwkBBBCoNwH1qKne2a644grf8YB6WVNHAq6Km+8sQR3ouDZ9BQVH6hxDnQm4KrG+FzjX1pDgqN52iCLzS5kXCcbkCDSRAHeQmqiwtanqdcg1DPZb7drd+J7Z9NBaEgIIIFCPAqoGp4s8qjKcmc4//3xzncFkDs76WV3Jq2t4JdeGzXdl7dq4ZZ2WgY0hQJk3RjmyFQhUQoAAqRKqCV6mnt1x+eWX++6p1QVreGZTgrNM1hBAAIEOBVxnHr6rb7WF0YUfPWpB7Y9chxcdzhcdqWcp6fk+elixHu2gO1GkxhagzBu7fNk6BDojQIDUGT3mRQABBBBAAAEEEEAAgYYSKL7LsYbafDYGAQQQQAABBBBAAAEEEPhOgADpOwveIYAAAggggAACCCCAQJMLECA1+Q7A5iOAAAIIIIAAAggggMB3AgRI31nwDgEEEEAAAQQQQAABBJpcgACpyXcANh8BBBBAAAEEEEAAAQS+EyBA+s6CdwgggAACCCCAAAIIINDkAgRITb4DsPkIIIAAAggggAACCCDwnQAB0ncWNXmXSqWsra3NP7i1JhkocKXKp/6Snshn+UqIfbN8lloS+2b5PNk3y2cZ9k39DiU91cN3qF72zaSXNflDoNYCBEg1LoGZM2fa559/bnpNcpo3b55NmjQpyVn0eZs4caLpL+lJljJNcmLfLG/pfPHFF3Wxb06ePNnmzp1b3o0v89LCvjljxowyL7m8i9N3/Ouvvy7vQiuwNPbN8qHOmjXL/6Ynfd8s3xazJAQaU4AAqTHLla1CAAEEEEAAAQQQQACBEgQIkEpAYxYEEEAAAQQQQAABBBBoTAECpMYsV7YKAQQQQAABBBBAAAEEShAgQCoBjVkQQAABBBBAAAEEEECgMQUIkBqzXNkqBBBAAAEEEEAAAQQQKEGAAKkENGZBAAEEEEAAAQQQQACBxhQgQGrMcmWrEEAAAQQQQAABBBBAoAQBAqQS0JgFAQQQQAABBBBAAAEEGlOAAKkxy5WtQgABBBBAAAEEEEAAgRIECJBKQGMWBBBAAAEEEEAAAQQQaEwBAqTGLFe2CgEEEEAAAQQQQAABBEoQIEAqAY1ZEEAAAQQQQAABBBBAoDEFWhtzs9iqfAKpqVPN3hwTn2yTja2lpSU+jE8IlFngG5tmb9ubsaWuZ27fc/+REEAAAQQQQACBWgsQINW6BGq1/tGv2vwtt4utveucaWbdusWG8QGBcguMs9dtX9s6ttgxNsV6WM/YMD4ggAACCCCAAAK1EKCKXS3UWScCCCCAAAIIIIAAAggkUoAAKZHFQqYQQAABBBBAAAEEEECgFgIESLVQZ50IIIAAAggggAACCCCQSAECpEQWC5lCAAEEEEAAAQQQQACBWggQINVCnXUigAACCCCAAAIIIIBAIgUIkBJZLGQKAQQQQAABBBBAAAEEaiFAgFQLddaJAAIIIIAAAggggAACiRQgQEpksZApBBBAAAEEEEAAAQQQqIUAAVIt1FknAggggAACCCCAAAIIJFKAACmRxUKmEEAAAQQQQAABBBBAoBYCBEi1UGedCCCAAAIIIIAAAgggkEgBAqREFguZQgABBBBAAAEEEEAAgVoIECDVQp11IoAAAggggAACCCCAQCIFCJASWSxkCgEEEEAAAQQQQAABBGohQIBUC3XWiQACCCCAAAIIIIAAAokUaE1krshU5QV69TL7/irx9bS0xD/zCYEKCPS0XraCrZqxZPa9DBA+IoAAAggggECNBBIVIH388cc2cuRI23vvvdtxfPjhh37coosuaoMGDbIFF1wwNk2+8dOmTbPnnnvO9LrxxhvbgAEDYvM324eWDQda67g3mm2z2d4ECKxp69ljxr6XgKIgCwgggAACCCCQRSAxAdI333xjp5xyivXo0aNdgHTrrbfajTfeaFtssYV98sknps9XXXWV9e3b129SvvETJkywQw45xFZccUVbdtll7brrrrPzzjvPNtlkkywkDEKg9gJffPGFzZkzp6YZmTlzpk2dOtW6detmvXTHkYQAAggggAACCDSBQCICpBdffNEuueQSmzx5sq2wwgoxdt0ZGjp0qP3hD3+wdddd1+bNm2dHHnmk3XHHHf4133gt7MILL7Rdd93Vjj/+eGtx1chuvvlmGzJkiA0fPtx/jq2QDwgkQGDnnXe2l156KQE5MfvjH/9oxxxzTCLyQiYQQAABBBBAAIFKC9Q8QFKVt9NOO832339/v60vvPBCbJt1ktivXz8fHGlEa2ur7bDDDnb77bf7ACnf+K+++srGjh1rp556ajoY0smn7kiNGTPG1lhjjdj6Mj+kUinTX6VSW1ubX7TWEd5Xal2dWa7ylvQ8RrcvyZbKZ7DMlc+wz/X7wU7Rzarq+xmTP7LJn76ezmtVV17Eyupl3wxlmqvMi9jkik6ab9+s6MoLXHiwDHktcLaqT1Yv+2aAYd8MEqW/Vmvf1MVe/ZEQQKAyAjUPkBZYYAEbMWKELbbYYjZs2LB2W/npp5/6anHREQqYvvzySx9Q5Bv/2Wef+Vk1T0haV/fu3W3ixIl5A6TZs2fbpEmTwqwVe1VVJv0lPX3++edJz6LPXz3k8+uvv85pOXfuXHO/frbJPjflnKbSI94f/Vcbdf+JNmvWLKsHz3rIo8qsHvKp4149JF1g01/SUz2UuQzrIZ/sm//b2xdZZBHT+RMJAQQqI1DzAEl3hBSw5EoKcBZaaKHY6D59+vjgaMqUKZZvvAIotWvSXzRpGYUEPl26dGk3b3Q5nX0/f/58X21QDl27du3s4io2v64sKq9qj5LkFH48M8s7aXlWAKTy1v6VLeUanm3aSg9TPpPsyb5Z3j0g375Z3rWVtrR6Om6qWrguyCU5NcpxMwnGYd/UcVO/65VKSfqNqNQ2slwEailQuW9vmbZKJ+T6gYmm8FkNx0sZr2XpIFZIw3P9sKnnvEqlGTNmmAK93r17F5SfSuUj33J10qQrtZW0yJeHQsaHK6BJz6fuHilIzxVwVvKHtRDH6DSV/g5E11XK+3rZN3XHWtVvkr5v6sKRjkdJPqkPx00dw5XXpCbtm6oZkPQy176pCw1Jz2c97Jvq3EbtqbVfJnnfTOp3hnwhkBSB7Jevk5I7l4/FF1+8XRUK/eCoBztd1S5kvIIh/aBGk5axzDLLRAfxHgEEEEAAAQQQQAABBJpcIPEBknq1GzduXOwu0ptvvplul5RvfP/+/f1tbs0Tkjpt0NWyaLukMI5XBBBAAAEEEEAAAQQQaF6BxAdI22yzjS+d2267zQc148ePt4ceesgOPPBAPzzf+IUXXti2224731W4nrWkBufqwU494S2xxBLNW/JsOQIIIIAAAggggAACCLQTSHyApGp0gwcPtnvuuccHNSeccILtueeeNmjQIL8x+cZrIj03SfXpd9llF9t99939HaVjjz22HQYDEEAAAQQQQAABBBBAoLkFEtVJw0EHHWT6y0zrrbee3Xvvvb4LUt31yey9Jd94tVe68sorfWNZ9SxDw8lMYT4jgAACCCCAAAIIIICABBIVIOUrkqWWWqrDSfKNz+wuvMOFMRIBBBBAAAEEEEAAAQSaTiDxVeyarkTYYAQQQAABBBBAAAEEEKiZAAFSzehZMQIIIIAAAggggAACCCRNgAApaSVCfhBAAAEEEEAAAQQQQKBmAnXVBqlmSg244pR7wrt73Hdsy1ro9jzmwYfKCMy1uTbV4vveYkaX+5XRZqkIIIAAAgggUKwAAVKxYo0y/cjnbf6W28W2puucadbSrVtsGB8QKLfAa/aS7WtbxxY7xqZYD+sZG8YHBBBAAAEEEECgFgJUsauFOutEAAEEEEAAAQQQQACBRAoQICWyWMgUAggggAACCCCAAAII1EKAAKkW6qwTAQQQQAABBBBAAAEEEilAgJTIYiFTCCCAAAIIIIAAAgggUAsBAqRaqLNOBBBAAAEEEEAAAQQQSKQAAVIii4VMIYAAAggggAACCCCAQC0ECJBqoc46EUAAAQQQQAABBBBAIJECBEiJLBYyhQACCCCAAAIIIIAAArUQIECqhTrrRAABBBBAAAEEEEAAgUQKECAlsljIFAIIIIAAAggggAACCNRCgACpFuqsEwEEEEAAAQQQQAABBBIpQICUyGIhUwgggAACCCCAAAIIIFALAQKkWqizTgQQQAABBBBAAAEEEEikAAFSIouFTCGAAAIIIIAAAggggEAtBAiQaqHOOhFAAAEEEEAAAQQQQCCRAq2JzBWZqrxAS4tZF/dHQqDqAi2m/0gIIIAAAggggEASBQiQklgqVchTy+Y/stb5M6uwJlaBQFxgoA2yd21WfCCfEEAAAQQQQACBhAhQxS4hBUE2EEAAAQQQQAABBBBAoPYCBEi1LwNygAACCCCAAAIIIIAAAgkRIEBKSEGQDQQQQAABBBBAAAEEEKi9AAFS7cuAHCCAAAIIIIAAAggggEBCBAiQElIQZAMBBBBAAAEEEEAAAQRqL0CAVPsyIAcIIIAAAggggAACCCCQEAECpIQUBNlAAAEEEEAAAQQQQACB2gsQINW+DMgBAggggAACCCCAAAIIJESAACkhBUE2EEAAAQQQQAABBBBAoPYCBEi1LwNygAACCCCAAAIIIIAAAgkRIEBKSEGQDQQQQAABBBBAAAEEEKi9AAFS7cuAHCCAAAIIIIAAAggggEBCBAiQElIQZAMBBBBAAAEEEEAAAQRqL0CAVPsyIAcIIIAAAggggAACCCCQEAECpIQUBNlAAAEEEEAAAQQQQACB2gsQINW+DMgBAggggAACCCCAAAIIJESAACkhBVHtbKSeG2nzFlky9peaN6/a2WB9TSgw2l60dW2J2N9sm92EEmwyAggggAACCCRRoDWJmSJPVRBQMDRlanxFqVT8M58QqIDAfJtn0yxj3zP2vQpQs0gEEEAAAQQQKEGAO0gloDELAggggAACCCCAAAIINKYAAVJjlitbhQACCCCAAAIIIIAAAiUIECCVgMYsCCCAAAIIIIAAAggg0JgCBEiNWa5sFQIIIIAAAggggAACCJQgQIBUAhqzIIAAAggggAACCCCAQGMKECA1ZrmyVQgggAACCCCAAAIIIFCCAAFSCWjMggACCCCAAAIIIIAAAo0pQIDUmOXKViGAAAIIIIAAAggggEAJAgRIJaAxCwIIIIAAAggggAACCDSmAAFSY5YrW4UAAggggAACCCCAAAIlCBAglYDGLAgggAACCCCAAAIIINCYAgRIjVmubBUCCCCAAAIIIIAAAgiUIECAVAIasyCAAAIIIIAAAggggEBjChAgNWa5slUIIIAAAggggAACCCBQggABUglozIIAAggggAACCCCAAAKNKdDamJvFVuUV2Hgj6zp+bGyylm7dYp/5gEAlBNayDexJGxdbdHfrEfvMBwQQQAABBBBAoFYCBEi1kq/xelt69jRbYYUa54LVN6NAD+tp3zP2vWYse7YZAQQQQACBehCgil09lBJ5RAABBBBAAAEEEEAAgaoIECBVhZmVIIAAAggggAACCCCAQD0IECDVQymRRwQQQAABBBBAAAEEEKiKAAFSVZhZCQIIIIAAAggggAACCNSDAAFSPZQSeUQAAQQQQAABBBBAAIGqCBAgVYWZlSCAAAIIIIAAAggggEA9CBAg1UMpkUcEEEAAAQQQQAABBBCoigABUlWYWQkCCCCAAAIIIIAAAgjUgwABUj2UEnlEAAEEEEAAAQQQQACBqggQIFWFmZUggAACCCCAAAIIIIBAPQgQINVDKZFHBBBAAAEEEEAAAQQQqIoAAVJVmFkJAggggAACCCCAAAII1IMAAVI9lBJ5RAABBBBAAAEEEEAAgaoIECBVhZmVIIAAAggggAACCCCAQD0IECDVQymRRwQQQAABBBBAAAEEEKiKQGtV1sJKEieQGjXa5h9xdCxfXZ9/2lpa2SViKHwou8BYe91OtSNiyx1hT1l39x8JAQQQQAABBBCotQBnw7UugVqtf9o0s5dHxdeeSsU/8wmBCghMt2n2hsX3vZS1VWBNLBIBBBBAAAEEEChegCp2xZsxBwIIIIAAAggggAACCDSoAAFSgxYsm4UAAggggAACCCCAAALFC1DFLo/Z7NmzbcqUKXmmKn10W9v/qhZNnTrVvvnmm9IXVOScrZMm20IZ83wxcaJZt24ZQ//3MeWq3ymvEzVNglPwTHo+58+fb3PnzrWWlpasmhqXlDRr1qyylvukbpPM+sa3TuXVw3rGBxb4qV72TZW5Uj3sm3PmzMm5bxZYLBWdLHzPp7mqwtOnT6/oujqzcPbNzui1n1flzr75P5eFFlrIevYs7ZjZXpYhCCCQKUCAlCmS8bl79+62xBJLZAwt38cZM2aYgqM+ffpYr169yrfgPEtKLbJwu1Yfi7vtbMkRIOmEXQFc374ZZ7Z51lPt0eHks5JlVo5tmjRpki244IIuHs0ekLYmqLMM/QiX03MRW6QdoZZfaoBUL/vmF198YTphLqdlO8gyDNC+2bt3b9OxL6lp5syZ/sJVtY+bxXrMmzfPH98XXXTRYmet6vTaNxV8JH3fnDx5sv+drId9U8d3fY9ICCBQnwIESHnKLdcV/jyzFTw6LF+v4X3BM3dmwix3LjrKQ8hbeO3Mqqsxbz3ksxDvalgVso5yero9vd0qvUWW4e0mzDIg5C28ZpkkUYOSnk9fFtU+HnWihJLuqU2rhzzWSz7D/tmJXaais4ayTno+K4rAwhFoAAHaIDVAIbIJCCCAAAIIIIAAAgggUB4BAqTyOLIUBBBAAAEEEEAAAQQQaAABAqQGKEQ2AQEEEEAAAQQQQAABBMojQIBUHkeWggACCCCAAAIIIIAAAg0gQIDUAIXIJiCAAAIIIIAAAggggEB5BAiQyuPIUhBAAAEEEEAAAQQQQKABBAiQGqAQ2QQEEEAAAQQQQAABBBAojwABUnkcWQoCCCCAAAIIIIAAAgg0gAABUgMUIpuAAAIIIIAAAggggAAC5REgQCqPI0tBAAEEEEAAAQQQQACBBhBobYBtYBNKEVh7Levyz7/H52xld4iD8KkSAqvaGjbMHogtupt1j33mAwIIIIAAAgggUCsBzohrJV/j9bb07Wst221b41yw+mYUWMgWsR8Z+14zlj3bjAACCCCAQD0IUMWuHkqJPCKAAAIIIIAAAggggEBVBAiQqsLMShBAAAEEEEAAAQQQQKAeBAiQ6qGUyCMCCCCAAAIIIIAAAghURYAAqSrMrAQBBBBAAAEEEEAAAQTqQYAAqR5KiTwigAACCCCAAAIIIIBAVQQIkKrCzEoQQAABBBBAAAEEEECgHgQIkOqhlMgjAggggAACCCCAAAIIVEWAAKkqzKwEAQQQQAABBBBAAAEE6kGAAKkeSok8IoAAAggggAACCCCAQFUECJCqwsxKEEAAAQQQQAABBBBAoB4ECJDqoZTIIwIIIIAAAggggAACCFRFgACpKsysBAEEEEAAAQQQQAABBOpBgACpHkqJPCKAAAIIIIAAAggggEBVBFqrshZWggACCCDQEAIHHHCAjRo1qqbb0tbWZvo7/fTT7aCDDqppXlg5AggggEDjCRAgNV6ZskUIIIBAxQQ++OADGzdunHXr0adi68i34La2eTZ/7kybPHlyvkkZjwACCCCAQNECBEhFkzXGDKmx46zt3PNjG9PlL8OspWvX2DA+IFBugfH2lv3BBscWe5kNtW7uP1L9COz8u7espaU2tbQ/fO1Oe/neY+sHi5wigAACCNSVAAFSXRVXGTM7caKlht8ZX+AtfzYjQIqb8KnsAl/bl/aAxfe9S+xGtx4CpLJjs0AEEEAAAQQQKFqgNpf/is4mMyCAAAIIIIAAAggggAAClRcgQKq8MWtAAAEEEEAAAQQQQACBOhEgQKqTgiKbCCCAAAIIIIAAAgggUHkBAqTKG7MGBBBAAAEEEEAAAQQQqBMBAqQ6KSiyiQACCCCAAAIIIIAAApUXIECqvDFrQAABBBBAAAEEEEAAgToRIECqk4IimwgggAA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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Salary plots\n",
    "# Expand the data to show the number of available slots\n",
    "\n",
    "OD2526_expanded <- OD2526_modified %>%\n",
    "    uncount(AvailableSlots) \n",
    "\n",
    "vlines_data_for_2526 <- data.frame(\n",
    "  intercepts = c(25600, UK_minimum_salary),\n",
    "  labels = c(\"Training Grant\", \"UK Minimum Salary\"),\n",
    "  colors = c(\"red\", \"green\")\n",
    ")\n",
    "\n",
    "vlines_data_for_2425 <- data.frame(\n",
    "  intercepts = c(18440, UK_minimum_salary),\n",
    "  labels = c(\"Training Grant\", \"UK Minimum Salary\"),\n",
    "  colors = c(\"red\", \"green\")\n",
    ")\n",
    "\n",
    "OD2526_salary_plot_expanded <- ggplot(OD2526_expanded, aes(x = Salary)) + \n",
    "  geom_histogram(binwidth = 1000, colour = 'black',fill = 'cornflowerblue') + \n",
    "  ggtitle(\"Salary distribution for 2025-26 training year\") + \n",
    "  xlab(\"Salary (£)\") + \n",
    "  ylab(\"Frequency\") +\n",
    "  scale_x_continuous(breaks = seq(0, max(OD2526_modified$Salary, na.rm = TRUE), by = 2500)) +\n",
    "  geom_vline(data = vlines_data_for_2526, aes(xintercept = intercepts, color = labels),linetype=\"dashed\", size = 1.2) +\n",
    "  scale_color_manual(name = \"Legend\", values = c(\"Training Grant\" = \"red\", \"UK Minimum Salary\" = \"green\")) +\n",
    "  theme_minimal()\n",
    "\n",
    "\n",
    "OD2526_salary_plot_expanded\n",
    "\n",
    "OD2425_expanded <- OD2425_modified %>%\n",
    "    uncount(AvailableSlots)\n",
    "\n",
    "OD2425_salary_plot_expanded <- ggplot(OD2425_expanded, aes(x = Salary)) + \n",
    "  geom_histogram(binwidth = 1000, colour = 'black', fill = 'cornflowerblue') + \n",
    "  ggtitle(\"Salary distribution for 2024-25 training year of Salary\") + \n",
    "  xlab(\"Salary (£)\") + \n",
    "  ylab(\"Frequency\") +\n",
    "  scale_x_continuous(\n",
    "    breaks = seq(0, max(OD2526_modified$Salary, na.rm = TRUE), by = 2500), \n",
    "    labels = scales::comma  # Use comma format for large numbers\n",
    "  ) +\n",
    "  geom_vline(data = vlines_data_for_2425, aes(xintercept = intercepts, color = labels), size = 1.2,linetype=\"dashed\") +\n",
    "  scale_color_manual(name = \"Legend\", values = c(\"Training Grant\" = \"red\", \"UK Minimum Salary\" = \"green\")) +\n",
    "  theme_minimal() \n",
    "\n",
    "OD2425_salary_plot_expanded\n",
    "\n",
    "# Working hour plot\n",
    "# Salary and visa plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "'Number of placements with skilled worker visa availability in 2025-26: 1194'"
      ],
      "text/latex": [
       "'Number of placements with skilled worker visa availability in 2025-26: 1194'"
      ],
      "text/markdown": [
       "'Number of placements with skilled worker visa availability in 2025-26: 1194'"
      ],
      "text/plain": [
       "[1] \"Number of placements with skilled worker visa availability in 2025-26: 1194\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "'Number of placements with skilled worker visa availability in 2024-25: 1502'"
      ],
      "text/latex": [
       "'Number of placements with skilled worker visa availability in 2024-25: 1502'"
      ],
      "text/markdown": [
       "'Number of placements with skilled worker visa availability in 2024-25: 1502'"
      ],
      "text/plain": [
       "[1] \"Number of placements with skilled worker visa availability in 2024-25: 1502\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "'Number of placements with skilled worker visa availability in 2023-24: 1284'"
      ],
      "text/latex": [
       "'Number of placements with skilled worker visa availability in 2023-24: 1284'"
      ],
      "text/markdown": [
       "'Number of placements with skilled worker visa availability in 2023-24: 1284'"
      ],
      "text/plain": [
       "[1] \"Number of placements with skilled worker visa availability in 2023-24: 1284\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "'Number of placements with skilled worker visa availability in 2022-23: 1146'"
      ],
      "text/latex": [
       "'Number of placements with skilled worker visa availability in 2022-23: 1146'"
      ],
      "text/markdown": [
       "'Number of placements with skilled worker visa availability in 2022-23: 1146'"
      ],
      "text/plain": [
       "[1] \"Number of placements with skilled worker visa availability in 2022-23: 1146\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "'Average number of applicants needing visa: 287'"
      ],
      "text/latex": [
       "'Average number of applicants needing visa: 287'"
      ],
      "text/markdown": [
       "'Average number of applicants needing visa: 287'"
      ],
      "text/plain": [
       "[1] \"Average number of applicants needing visa: 287\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "visa_availability_2526 <- OD2526_expanded %>%\n",
    "  count(SkilledWorkerVisa) %>%\n",
    "  filter(SkilledWorkerVisa == \"Y\") %>%\n",
    "  pull(n)\n",
    "\n",
    "visa_availability_2425 <- OD2425_expanded %>%\n",
    "    count(SkilledWorkerVisa) %>%\n",
    "    filter(SkilledWorkerVisa == \"Y\") %>%\n",
    "    pull(n)\n",
    "\n",
    "visa_availabilty_2324 <- OD2324 %>%\n",
    "    uncount(Places.Available) %>%\n",
    "    count(Skilled.worker.visa) %>%\n",
    "    filter(Skilled.worker.visa == \"Yes\") %>%\n",
    "    pull(n)\n",
    "\n",
    "visa_availablilty_2223 <- OD2223 %>%\n",
    "    uncount(Places.Available) %>%\n",
    "    count(Skilled.worker.visa) %>%\n",
    "    filter(Skilled.worker.visa == \"Yes\") %>%\n",
    "    pull(n)\n",
    "\n",
    "paste0(\"Number of placements with skilled worker visa availability in 2025-26: \", visa_availability_2526)\n",
    "paste0(\"Number of placements with skilled worker visa availability in 2024-25: \", visa_availability_2425)\n",
    "paste0(\"Number of placements with skilled worker visa availability in 2023-24: \", visa_availabilty_2324)\n",
    "paste0(\"Number of placements with skilled worker visa availability in 2022-23: \", visa_availablilty_2223)\n",
    "\n",
    "years <- c(\"2022-23\", \"2023-24\", \"2024-25\", \"2025-26\")\n",
    "visa_availability <- c(visa_availablilty_2223, visa_availabilty_2324, visa_availability_2425, visa_availability_2526)\n",
    "# Below numbers taken fron oriel reports NHS HEE\n",
    "visa_needed_in_2018_2019 <- 297\n",
    "visa_needed_in_2019_2020 <- 281\n",
    "visa_needed_in_2020_2021 <- 276\n",
    "visa_needed_in_2021_2022 <- 315\n",
    "visa_needed_in_2022_2023 <- 284\n",
    "visa_needed_in_2023_2024 <- 270\n",
    "average_visa_needed <- mean(c(visa_needed_in_2018_2019, visa_needed_in_2019_2020, visa_needed_in_2020_2021, visa_needed_in_2021_2022, visa_needed_in_2022_2023, visa_needed_in_2023_2024))\n",
    "paste0('Average number of applicants needing visa: ', round(average_visa_needed))\n",
    "\n",
    "\n",
    "df.visa <- as.data.frame(cbind(years, visa_availability ))\n",
    "df.visa$visa_availability <- as.numeric(df.visa$visa_availability)\n",
    "\n",
    "ggplot(df.visa, aes(x=years, y=visa_availability)) +\n",
    "  geom_col(fill = 'cornflowerblue', colour = 'black') +\n",
    "  labs(title=\"Number of placements with skilled worker visa availability\", x=\"Year\", y=\"Number of placements\") +\n",
    "  geom_hline(aes(yintercept=average_visa_needed, color = \"Average Number of Applicants Who Need Skilled Worker\"), linetype=\"dashed\", lwd = 1.5) +\n",
    "  scale_color_manual(name = \"Legend\", values = c(\"Average Number of Applicants Who Need Skilled Worker\" = \"red\")) +\n",
    "  theme_minimal() +\n",
    "  theme(legend.position = \"top\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Visa availability going down?\n",
    "https://www.lasepharmacy.hee.nhs.uk/national-recruitment/evaluation/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "# Is each programme offering over national minimum salary?\n",
    "is_it_over_national_minimum_hourly_wage <- function(hourly_wage){\n",
    "    UK_minimum_hourly_wage <= hourly_wage\n",
    "    # returns TRUE if hourly wage of the programme is higher than the national minimum hourly wage\n",
    "\n",
    "}\n",
    "\n",
    "OD2526_expanded <- OD2526_expanded %>%\n",
    "    mutate(hourly_wage = round(Salary/52/WeeklyHours,digits = 2)) %>%\n",
    "    mutate(higher_than_minimum_hourly_wage = is_it_over_national_minimum_hourly_wage(hourly_wage))\n",
    "\n",
    "OD2425_expanded <- OD2425_expanded %>%\n",
    "    mutate(hourly_wage = round(Salary/52/WeeklyHours,digits = 2)) %>%\n",
    "    mutate(higher_than_minimum_hourly_wage = is_it_over_national_minimum_hourly_wage(hourly_wage))\n",
    "\n",
    "# Meaning all places being offered for 2025-26 are being paid at minimum of the national minimum wage or more"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Region'</li><li>'SubRegion'</li><li>'Sector'</li><li>'ProgramPreference'</li><li>'ProgramTitle'</li><li>'ProgramDescription'</li><li>'EmployerType'</li><li>'EmployerName'</li><li>'OrgSizePrimaryCareOnly'</li><li>'HospitalSpecialties'</li><li>'SkilledWorkerVisa'</li><li>'LicenseCount'</li><li>'Salary'</li><li>'TrainingProvider'</li><li>'WeeklyHours'</li><li>'ICSName'</li><li>'PlacementCount'</li><li>'PlacementSetting1'</li><li>'PlacementSetting2'</li><li>'PlacementSetting3'</li><li>'PlacementSetting4'</li><li>'hourly_wage'</li><li>'higher_than_minimum_hourly_wage'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Region'\n",
       "\\item 'SubRegion'\n",
       "\\item 'Sector'\n",
       "\\item 'ProgramPreference'\n",
       "\\item 'ProgramTitle'\n",
       "\\item 'ProgramDescription'\n",
       "\\item 'EmployerType'\n",
       "\\item 'EmployerName'\n",
       "\\item 'OrgSizePrimaryCareOnly'\n",
       "\\item 'HospitalSpecialties'\n",
       "\\item 'SkilledWorkerVisa'\n",
       "\\item 'LicenseCount'\n",
       "\\item 'Salary'\n",
       "\\item 'TrainingProvider'\n",
       "\\item 'WeeklyHours'\n",
       "\\item 'ICSName'\n",
       "\\item 'PlacementCount'\n",
       "\\item 'PlacementSetting1'\n",
       "\\item 'PlacementSetting2'\n",
       "\\item 'PlacementSetting3'\n",
       "\\item 'PlacementSetting4'\n",
       "\\item 'hourly\\_wage'\n",
       "\\item 'higher\\_than\\_minimum\\_hourly\\_wage'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Region'\n",
       "2. 'SubRegion'\n",
       "3. 'Sector'\n",
       "4. 'ProgramPreference'\n",
       "5. 'ProgramTitle'\n",
       "6. 'ProgramDescription'\n",
       "7. 'EmployerType'\n",
       "8. 'EmployerName'\n",
       "9. 'OrgSizePrimaryCareOnly'\n",
       "10. 'HospitalSpecialties'\n",
       "11. 'SkilledWorkerVisa'\n",
       "12. 'LicenseCount'\n",
       "13. 'Salary'\n",
       "14. 'TrainingProvider'\n",
       "15. 'WeeklyHours'\n",
       "16. 'ICSName'\n",
       "17. 'PlacementCount'\n",
       "18. 'PlacementSetting1'\n",
       "19. 'PlacementSetting2'\n",
       "20. 'PlacementSetting3'\n",
       "21. 'PlacementSetting4'\n",
       "22. 'hourly_wage'\n",
       "23. 'higher_than_minimum_hourly_wage'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Region\"                          \"SubRegion\"                      \n",
       " [3] \"Sector\"                          \"ProgramPreference\"              \n",
       " [5] \"ProgramTitle\"                    \"ProgramDescription\"             \n",
       " [7] \"EmployerType\"                    \"EmployerName\"                   \n",
       " [9] \"OrgSizePrimaryCareOnly\"          \"HospitalSpecialties\"            \n",
       "[11] \"SkilledWorkerVisa\"               \"LicenseCount\"                   \n",
       "[13] \"Salary\"                          \"TrainingProvider\"               \n",
       "[15] \"WeeklyHours\"                     \"ICSName\"                        \n",
       "[17] \"PlacementCount\"                  \"PlacementSetting1\"              \n",
       "[19] \"PlacementSetting2\"               \"PlacementSetting3\"              \n",
       "[21] \"PlacementSetting4\"               \"hourly_wage\"                    \n",
       "[23] \"higher_than_minimum_hourly_wage\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colnames(OD2425_expanded)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ggAACCCCAAAIIVH0N0oIFC+zYY4+1k08+2d5//30777zz7OCDD7bZs2eHZ++GG26w/fbbz95++2275ZZb7NBDD7Vvv/02XD5+/Hjbeeed7bbbbrO33nrLDjjgAHv++efD5UwggAACCCCAAAIIIIAAAhKo+gDp3nvvtZdfftmuuOIKO+200+ymm25ytUMjR450Z1A1R9dcc42NGjXKTj31VPv73/9uXbp0sdGjR4dn+KyzzrKddtrJ5TFixAgXTF1wwQWWy+XCdZhAAAEEEEAAAQQQQAABBKo+QHrjjTds5ZVXthVXXNGdrY4dO9qWW25pjz/+uM2fP99efPFFW3LJJV2zO61QX19v22yzjT388MNu/a+//treeecdV4NUFzxUVWmHHXawzz77zNU4uRn8hwACCCCAAAIIIIAAAggEApnog6SgJ5rUvE7/vvnmG/v8889twIAB0cUuYPrqq69MfZe++OILt0xBlE99+vSxzp0726RJk2y11Vbzs4v+nTdvXl5zPq00d+5cU9M/BWiVSOoX1VpJJq25v1LHJUclmVZTuUqVu1qXq1a02s5xtVrFKZd/j0+fPt06dKj635PiHFKbrqP3uZKuUVLLBLyhvqP47GyZpd+az04v0fTfXr16Nb2QJQjUkEB+5FGFB6YBGVQb9Nprr9laa61lU6ZMsQcffNCVdObMmS4AWmihhfJKrjewPui0rgIoNbnTv2jSOtF+StFl0WndwOvmqDDpxmnOnDmFs8t6PWPGjLK2K2cjuRQ7nnLyquQ2+pLXP1JlBKrxHFfmyNomF33WkCon4AOlyuXYfnPSdxHv98qdfyybtyRAat6HpbUjUPUB0vbbb29PP/20DR8+3JZffnn75JNPXH+id99917p16+ZGs/O/8vrT4l9379696HKtp8BHy0sljZankfGiSQGNarUKg67oOkmmW/OXae2r8HiSlLXS6/pfP7t27RrrfFR6/7WWn2qQ9MNA7969a+3Q2uR49Mu8rlF5tub7tE0OthV2OmvWLFNTZ73fSS0T0HeY3utqDVE4amvLcm6/W+tH00UWWaT9AnDkCCAQClR9gKQ+R2effba9+uqr9uWXX9oaa6xhkydPtttvv93dtPTt29cmBMN/R9PUqVPdh5wCGC3XF4l+AY4GRFqnf//+0c2KTmv/+hdNat6nwKlSAVKl8omWsalp3eS15v6aKoef7/uFybiayuXLl7W/CpBkimVlzpyv3dVNaOHnQGX20L5yUbDJ9VmZc+5/COSzszKeyoVrs3KW5IRA1gWqvlH9uHHj3PDc66yzjm233XY2cOBAe+GFF9zADboJXHbZZW3s2LF5/YHGjBkT9kvS+qrt0TyfNGiDmppF+yX5ZfxFAAEEEEAAAQQQQACB9itQ9QGSmoNdeuml7iGwOk3qi3TPPfe4Jnd6vcUWW+iP3XjjjS7o+fDDD+2+++5zQ3lr/sILL2xbbbWVGwpcbYtV+3PllVe6ke4WW2wxrZLp1GnebLvxtBXCf3s8/r/hzzN9UBQeAQQQQAABBBBAAIE2Eqj6AElBzJFHHumec6RA59xzz7XDDjssHH1OtUh6PtKdd97pgp5jjjnGdtttNxsyZEhIesghh7h22jvuuKPtsssurkZJedZKqm+YZ/5fh9z/RoWrlWPjOBBAAAEEEEAAAQQQaE2Bqu+DJIxdd93V/dMzjTREd2HS6HZ33XWX66OkgKqwM7U6XV544YWmfkdqr92jR4/CLHiNAAIIIIAAAggggAACCGTjOUj+PBULjvwy/V188cWjLxtNFw4H3mgFZiCAAAIIIIAAAggggEC7Fqj6Jnbt+uxw8AgggAACCCCAAAIIINCqAgRIrcrNzhBAAAEEEEAAAQQQQKCaBQiQqvnsUDYEEEAAAQQQQAABBBBoVQECpFblZmcIIIAAAggggAACCCBQzQIESNV8digbAggggAACCCCAAAIItKoAAVKrcrMzBBBAAAEEEEAAAQQQqGYBAqRqPjuUDQEEEEAAAQQQQAABBFpVgACpVbnZGQIIIIAAAggggAACCFSzAAFSNZ8dyoYAAggggAACCCCAAAKtKkCA1Krc7AwBBBBAAAEEEEAAAQSqWaC+mgtH2UoLzK/vbCP+7+ZwxckLDwinmUAAAQQQQAABBBBAAIFkAgRIybyqbu1cXQd7e5kNq65cFAgBBBBAAAEEEEAAgSwK0MQui2eNMiOAAAIIIIAAAggggEAqAgRIqbCSKQIIIIAAAggggAACCGRRgAApi2eNMiOAAAIIIIAAAggggEAqAgRIqbCSKQIIIIAAAggggAACCGRRgAApi2eNMiOAAAIIIIAAAggggEAqAgRIqbCSKQIIIIAAAggggAACCGRRgAApi2eNMiOAAAIIIIAAAggggEAqAgRIqbCSKQIIIIAAAggggAACCGRRgAApi2eNMiOAAAIIIIAAAggggEAqAgRIqbCSKQIIIIAAAggggAACCGRRgAApi2eNMiOAAAIIIIAAAggggEAqAgRIqbCSKQIIIIAAAggggAACCGRRoD6LhabMPwh0XDDP9njignDGmGU2tDeX3zh8zQQCCCCAAAIIIIAAAgjEFyBAim9VlWt2aFhguz79t7Bsubo6AqRQgwkE2qfAhRdeaA899FCrHPyIESNs3XXXbZV9sRMEEEAAAQRaQ4AAqTWU2QcCCCDQigJvvvmm3X///a2yx8MPP7xV9sNOEEAAAQQQaC0BAqTWkmY/CCCAQCsLbHbgv61n3xVS2et7z15i454alUreZIoAAggggEBbChAgtaU++0YAAQRSFKjv0ss6d104lT10rO+WSr5kigACCCCAQFsLMIpdW58B9o8AAggggAACCCCAAAJVI0CAVDWngoIggAACCCCAAAIIIIBAWwsQILX1GWD/CCCAAAIIIIAAAgggUDUCBEhVcyooCAIIIIAAAggggAACCLS1AAFSW58B9o8AAggggAACCCCAAAJVI0CAVDWngoIggAACCCCAAAIIIIBAWwsQILX1GWD/CCCAAAIIIIAAAgggUDUCBEhVcyooCAIIIIAAAggggAACCLS1AAFSW58B9o8AAggggAACCCCAAAJVI1BfNSWhIGUJ5Orq7NUVh4bbftZnuXCaCQQQQAABBBBAAAEEEEgmQICUzKvq1p5f38XO3ueaqisXBUIAAQQQQAABBBBAIIsCNLHL4lmjzAgggAACCCCAAAIIIJCKAAFSKqxkigACCCCAAAIIIIAAAlkUIEDK4lmjzAgggAACCCCAAAIIIJCKAAFSKqxkigACCCCAAAIIIIAAAlkUIEDK4lmjzAgggAACCCCAAAIIIJCKAAFSKqxkigACCCCAAAIIIIAAAlkUIEDK4lmjzAgggAACCCCAAAIIIJD2lEz1AABAAElEQVSKAAFSKqxkigACCCCAAAIIIIAAAlkUIEDK4lmjzAgggAACCCCAAAIIIJCKAAFSKqxkigACCCCAAAIIIIAAAlkUIEDK4lmjzAgggAACCCCAAAIIIJCKAAFSKqxkigACCCCAAAIIIIAAAlkUqM9ioSlzvkCPWVPCGXPru9i8Tl3D10wggAACCCCAAAIIIIBAfAECpPhWVblmp3mz7epz1gjLdsfGR9jooceFr5lAAAEEEEAAAQQQQACB+AI0sYtvxZoIIIAAAggggAACCCBQ4wLUINX4CebwyhN4/vnn7fXXXy9v44RbDR061AYNGpRwK1ZHAAEEEEAAAQQQSEOAACkNVfLMvMAdd9xh5557bqscx7XXXkuA1CrS7AQBBBBAAAEEECgtQIBU2og12rHAShsNt559V0hFYPL4p23iG7ekkjeZIoAAAggggAACCJQnQIBUnhtb1bhAXV2dO8LFVxhqfX+0QSpHu2DeLAKkVGTJFAEEEEAAAQQQKF+AQRrKt2NLBBBAAAEEEEAAAQQQqDEBAqQaO6EcDgIIIIAAAggggAACCJQvQIBUvh1bIoAAAggggAACCCCAQI0JECDV2AnlcBBAAAEEEEAAAQQQQKB8AQKk8u3YEgEEEEAAAQQQQAABBGpMgACpxk4oh4MAAggggAACCCCAAALlCxAglW/HlggggAACCCCAAAIIIFBjAgRINXZCORwEEEAAAQQQQAABBBAoX4AHxZZvVxVbzqvvYscc/mhYlmndFgmnmUAAAQQQQAABBBBAAIFkAgRIybyqb+26Ovus7wrVVy5KhAACCCCAAAIIIIBABgVoYpfBk0aREUAAAQQQQAABBBBAIB0BAqR0XMkVAQQQQAABBBBAAAEEMihAgJTBk0aREUAAAQQQQAABBBBAIB0BAqR0XMkVAQQQQAABBBBAAAEEMihAgJTBk0aREUAAAQQQQAABBBBAIB0BAqR0XMkVAQQQQAABBBBAAAEEMihAgJTBk0aREUAAAQQQQAABBBBAIB0BAqR0XMkVAQQQQAABBBBAAAEEMihAgJTBk0aREUAAAQQQQAABBBBAIB0BAqR0XMkVAQQQQAABBBBAAAEEMihQn8Eyt2qR586dazNmzMjb57x580z/Zs+enTe/3BdTpkwpd9PE2y1YsMC+/fbbxNultUFDQ4PLWpYqW7WkSp3bOMej66tS5ySXy5lMK5VfnPLX8jp6nyvpPVpXV5eZQ50zZ06rlXX69Omxr7f58+e7culzldQyAf/ZqXPN+71lln5rPju9RPG/+gzs3bt38YXMRaDGBAiQSpzQ+vp669GjR95auqHV/C5duuTNL/eFvwkrd/sk23Xo0KHR8STZvtLr6th1s9SpU6eqKpfK01pJ11HhNVbuvhUgybRS+ZVbjlrZTkG7bpq6d+9ueu9kJenzqbVSkut35syZzrFr166tVbya3Y+uTX12FvuOqtmDTvnA5MlnZ8rIZI9ARgRa71s0IyCFxdRNUefOnfNmz5o1y30pFc7PWynBi5bk03HBXPv1vX8M9/bKoJ/ZS6tsE74unNAvQC3ZX2F+lXrdsWPHqiqXytNaSTc4lTonCpCq9Ry3lmcl9+ODIgXMrXlNtPQYWrOssol7/eoGlOuzpWf3f9v72rhq++yszNG1XS5xr+W2KyF7RgCB1hAgQGoN5RT30SH4dXvz128J9/Btr37NBkjhikwggAACCCCAAAIIIIBAI4HstBlpVHRmIIAAAggggAACCCCAAAKVFSBAqqwnuSGAAAIIIIAAAggggECGBQiQMnzyKDoCCCCAAAIIIIAAAghUVoAAqbKe5IYAAggggAACCCCAAAIZFiBAyvDJo+gIIIAAAggggAACCCBQWQECpMp6khsCCCCAAAIIIIAAAghkWIAAKcMnj6IjgAACCCCAAAIIIIBAZQUIkCrrSW4IIIAAAggggAACCCCQYQECpAyfPIqOAAIIIIAAAggggAAClRUgQKqsJ7khgAACCCCAAAIIIIBAhgUIkDJ88ig6AggggAACCCCAAAIIVFaAAKmynuSGAAIIIIAAAggggAACGRaoz3DZKXog0NChgz221l6hxYf9Vw+nmUAAAQQQQAABBBBAAIFkAgRIybyqbu0FHTvbZTudU3XlokAIIIAAAggggAACCGRRgCZ2WTxrlBkBBBBAAAEEEEAAAQRSESBASoWVTBFAAAEEEEAAAQQQQCCLAgRIWTxrlBkBBBBAAAEEEEAAAQRSESBASoWVTBFAAAEEEEAAAQQQQCCLAgRIWTxrlBkBBBBAAAEEEEAAAQRSESBASoWVTBFAAAEEEEAAAQQQQCCLAgRIWTxrlBkBBBBAAAEEEEAAAQRSESBASoWVTBFAAAEEEEAAAQQQQCCLAgRIWTxrlBkBBBBAAAEEEEAAAQRSESBASoWVTBFAAAEEEEAAAQQQQCCLAgRIWTxrlBkBBBBAAAEEEEAAAQRSESBASoWVTBFAAAEEEEAAAQQQQCCLAvVZLDRljgjkcjbgq/fDGVO7L2rTevQJXzOBAAIIIIAAAggggAAC8QUIkOJbVeWanebPsZGXbBGW7Y6Nj7DRQ48LXzOBAAIIIIAAAggggAAC8QVoYhffijURQAABBBBAAAEEEECgxgUIkGr8BHN4CCCAAAIIIIAAAgggEF+AACm+FWsigAACCCCAAAIIIIBAjQsQINX4CebwEEAAAQQQQAABBBBAIL4AAVJ8K9ZEAAEEEEAAAQQQQACBGhcgQKrxE8zhIYAAAggggAACCCCAQHwBAqT4VqyJAAIIIIAAAggggAACNS5AgFTjJ5jDQwABBBBAAAEEEEAAgfgCBEjxrVgTAQQQQAABBBBAAAEEalyAAKnGTzCHhwACCCCAAAIIIIAAAvEFCJDiW7EmAggggAACCCCAAAII1LgAAVKNn2AODwEEEEAAAQQQQAABBOILECDFt2JNBBBAAAEEEEAAAQQQqHGB+ho/vpo/vHmdutr+f/hveJzz6ruE00wggAACCCCAAAIIIIBAMgECpGReVbn2zK4LV2W5KBQCCCCAAAIIIIAAAlkToIld1s4Y5UUAAQQQQAABBBBAAIHUBAiQUqMlYwQQQAABBBBAAAEEEMiaAAFS1s4Y5UUAAQQQQAABBBBAAIHUBAiQUqMlYwQQQAABBBBAAAEEEMiaAAFS1s4Y5UUAAQQQQAABBBBAAIHUBAiQUqMlYwQQQAABBBBAAAEEEMiaAAFS1s4Y5UUAAQQQQAABBBBAAIHUBAiQUqMlYwQQQAABBBBAAAEEEMiaQOIA6ZxzzrFhw4bZ448/brlcLmvHS3kRQAABBBBAAAEEEEAAgSYFEgdIAwcOtLvuusuGDh1qyy23nJ188sn24YcfNrkDFiCAAAIIIIAAAggggAACWRFIHCDts88+9sUXX9jNN99sq666qp155pm2wgor2CabbGJXX321TZs2LSvHTjkRQAABBBBAAAEEEEAAgTyBxAGStu7atavttdde9u9//9s++eQTO//8823evHl20EEH2RJLLGG/+tWvaIKXx8wLBBBAAAEEEEAAAQQQyIJAWQFS9MAWX3xxO+aYY+yqq66yI444wubMmWM33HCDa4K38sor25133hldnekKC9TPn2N/uHFY+G+TN26v8B7IDgEEEEAAAQQQQACB9iNQ35JDnThxot100032j3/8w8aMGWOdO3e2XXfd1fbff3/r2LGjjRw50nbffXfX9E4DO5AqL1AXDJSx9vuPhxlP6L9aOM0EAggggAACCCCAAAIIJBNIHCBNmTLFbr31VhcUPfnkk24ku7XWWssuuugiU/+kPn36hCXYcsstTbVI6ptEgBSyMIEAAggggAACCCCAAAJVKpA4QFKt0Kmnnmp9+/a14cOHu9qiNddcs+jhdejQwfr3729qhkdCAAEEEEAAAQQQQAABBKpdIHGAtM4669jtt99uO+ywg2tSV+oAn3jiCaurqyu1GssRQAABBBBAAAEEEEAAgTYXSDxIw0477WS77LKLXXfddfbQQw+FB6CgabPNNrP7778/nKcJgqM8Dl4ggAACCCCAAAIIIIBAFQskDpA0nPfaa69tBx98sL3//vvhoWlQhpdeesm23357N3BDuIAJBBBAAAEEEEAAAQQQQCAjAokDJDWZe/PNN+3ee++1ww47LDxM1Sp9/PHHpoEZfvvb31pDQ0O4jAkEEEAAAQQQQAABBBBAIAsCiQOku+++2zbddFNXU1R4gIsuuqgdffTR9uWXX9r48eMLF/MaAQQQQAABBBBAAAEEEKhqgcQBko6mU6dOTR6UgiQlPROJhAACCCCAAAIIIIAAAghkSSBxgLT55pvb448/bs8880yj41SzunPPPdf69etnSy21VKPlzEAAAQQQQAABBBBAAAEEqlkg8TDfW2+9ta2//vpuxLo999zTBg8ebL169bJPP/3UbrvtNhs7dqzdeOON1XzMlA0BBBBAAAEEEEAAAQQQKCqQOEDq2bOnPfzww24UO/VHuummm8KMVWuk13vvvXc4jwkEEEAAAQQQQAABBBBAICsCiQMkHVjXrl3t+uuvt1wu5wZjUO3RsssuawMGDOC5R1k585QTAQQQQAABBBCoYoGvvvrKZsyY4bptdOiQuFdIFR/ZD0XTwGbz589399A/zGWqrQXKCpB8ofUQ2OWWW8798/P427oCDR062h0bHxHu9O1lNgynmUAAAQQQQAABBLIqcMQRR9jo0aNt8uTJ1rdv36weRrPl3nfffd1zRRn9uVmmVl/YogCp1UvLDhsJLOjYyUYPPa7RfGYggAACCCCAAAIIIIBAcoGyAqTbb7/dzj//fPvoo49s1qxZrqld4a6//fbbwlm8RgABBBBAAAEEEEAAAQSqWiBxgPTss8/aXnvtZd26dbM111zTDemtpnYkBBBAAAEEEEAAAQTaSuDNN9+0W265xd555x1beumlbYcddrChQ4c2Ks7TTz9t999/v02YMMF++tOf2kEHHWRnnHGGbbnllrbRRhuF68fJ7/LLL7dFFlnE9Bica6+91l5++WXr37+/7bHHHjZkyJAwL01MmjTJ/vWvf9ljjz3m+u4PGzYsbzkvqkcgcYB06623ukEaXn31VVtxxRWr50goCQIIIIAAAggggEC7FLjsssts+PDh7tj1SJr//Oc/dsEFF9jvfvc794xOj3L22Wfb8ccfb2ussYa7jx0xYoQLqrS+fvz3AVLc/K688krr0qWLnXTSSfbZZ5/Z2muvbffee69dfPHFrv/U7rvv7natASfWW289++abb1zQ9uijj9qll15qCy20kC8af6tIIPGQIJ9//rn95Cc/ITiqopNIURBAAAEEEEAAgfYq8P7777vgSLVBGln5nnvusVdeecX++Mc/2nnnnWcKRpSeeOIJO/HEE+3II4+0119/3T2/c8yYMS5oidrFzc9voxqpnXbayTQinfbx2muvuWBL3VF82meffey7775zNUx33XWXPffcc/aHP/zB1WL5dfhbPQKJAyQFR6o9mjlzZvUcBSVBAAEEEEAAAQQQaJcCl1xyic2dO9fVDEVHuzv22GOtU6dO9re//c25qA+9aonUnM53D9H6p512Wp5b3Pz8RqpBOv30013emqcWVuqGor76SlOnTrVHHnnEfv3rX9ugQYPcPP2n8qkpIKn6BBI3sVN7SVUnnnLKKe5i6Ny5c/UdFSVCAAEEEEAAAQQQaBcC48aNcwGP+gPpHjWaunfvbu+++66bpVql5Zdf3nr16hVdxTWLi86Im5/fZqmllrLC++F+/frZ22+/7Vb573//6wY0U7O+aOrYsaMLpNTXiVRdAokDpMcff9wWW2wx157zoosusoEDB1qPHj0aHdUbb7zRaB4zEEAAAQQQQAABBBCopID696gWp76+8W3tNttsYz179nS70/OUevfu3WjXqlWKprj5+W0UhBUm1VDlcjk3++uvv3Z/fTmi6y666KLRl0xXiUDjK6lEwTR895w5c2zdddctsSaLEUAAAQQQQAABBBBIV2C55ZazF1980U499dS8Jmza6/z588PAaYUVVnB9gBS4+CZ2WufDDz/UnzDFzS/coMTE4MGD3RoTJ05stKYGdiBVn0DiPkgHH3ywuwh1ITb3r9KHqg5zepryAw88YDNmzGiUvS66m2++2R566CGbPn16o+XTpk1z22oUvmIXaKMNmIEAAggggAACCCBQ9QIanEHp+uuvzyurmrap1uaoo45y83fbbTdT7ZDuF6NJI85FU9z8ots0N/2jH/3IFl988UblU3D01FNPNbcpy9pIIHENUrScuvDUrlNtOTWkojqj6SKodLrjjjvs73//uxur/osvvnDN+/TaDzN+ww03uDanm266qRtiUa/V/E/j0iuNHz/eDjzwQNMvAgMGDDAN3ajOdBtssEGli0p+CCCAAAIIIIAAAhUUOPnkk8MBEKLZbrbZZu5ZR7/5zW9MAytceOGFrhvIFltsYerqoXs9BUh/+tOf3Gb777+/uwdUf3qNNKcBE+677z73A7pW8LVKcfOLlqXU9BVXXGG77LKL7b333m7ocQ3coEEaFixYUGpTlreBQFkBkjqdHXLIIWHUqwfHKkDSiB0ag17DKqotaCWSmvRp9BGNWa8HeCmdddZZds0119iZZ57paoM0PWrUKFMVpqpSVTbVNumvX1/DL+oXBF381113nRsbX78g+DeDW5H/MiGgD7P33nsv1bLqQW8kBBBAAAEEEGh7AQU/xVKHDh1cgKSR6vQco8MPP9wFH7oXVNIP6f/85z9d0KTX6qOk9Y477ji788473fDem2yyiRvue/vttw/71MfNT3nGTTvuuKMpSNJzmDQitAZoUMC22mqrmYYJJ1WXQOIASRHvdtttZ/PmzXOR77PPPuuOSBGwOsJpqESNQX/VVVdV5Eh1M6yBIHxwpEwVhM2aNcvlr2Z+Sy65pAuONEMXv8qhN4QCJHWM0xOVTzjhhDAY0pOVNcqJAj1dmKRsCSggvu2227JVaEqLAAIIIIAAAokE9EN2YXO4pjLQAGK33HKLG+5b3TIWXnhhd38Y/SFcrZA0sFhhwKUByJSiQ4THyU/b6D60WNKQ4oXpgAMOMP2bMGGC21exQRsKt+F12wgkDpA0hOKUKVNc1aXGbt9zzz1dyRUJ6yJWEzY1b9O/YqPbJT3Mjz/+2DXbe+aZZ1w16OzZs+1nP/uZC9KUlx5cq31GkwImtTFtaGgwvRmUNM+nPn36uOEYJ02aVDJA0rj6hX2a9MuEAkQfpPl8y/0rz3JTXa7BVp3wfLj55N4DbdIiTY+pr0BWT3GulqRzpKTz6n/xKVU2nROlwdv9xTp3azwaTant4ywf89hfbMa3E+Ks2uJ1dH1V8pxU2zluMVAbZqD3uZIe7hf9km3DIsXatQbSaa2k/p1xr1/flKQ1y9daDq29H//ZKcu4/q1dxqztT6ZYNn3W9Bnouy40vVbbL9Fw26uuumrRgqiPkh7OqnvKIUOGhOuoZZKOz/c9ChcEE83lF10vyfQyyyyTZHXWbQOBxAGS2myqzWdTD7b6xS9+YSNHjnTRcSVqZzQko4Ig9XVSzY+i7nPPPdfU9O6Xv/ylC4AWWmihPDr1idIHnQIPbavmfoVN/rSO8iiVlE+xL3P/RV9q+zjLi+UfZzutUz9/rv35+r3D1e/Y+AgbPfS48HXhhEZuacn+CvOr1Gt5xjX16/VfaWvrtlD/ShUhL5/3nrus1QIkBYaVPieVzi8Ppx2+8EF5Vg7dv0dao7wKIpNeb3F/DGmN8md9H019R2X9uNqq/Emv5bYqJ/stT0BdQs455xx3P7nVVlu5gRMee+wxGzNmjKkCQM8zIiEggcQBksZ6b65/xsyZM52samkqkfRF/8knn5hGn9MIIEoKbtSPSB3d1E608MvWv1ZZiy1XHsq32Lj1WhZNCqz0sK9o0i+myrdr167R2WVPFz5crOyMYmyomr7C44mxWWqr6MZTv87rXMStaq6Ue2oHlTBjBfiVOicKgNWsNNpMIGFxWD0ioGtT16g81dY9K6k13yNqxhL3+tUIpPqVNs5nb1as26qc+p5TbYfOdeGPhG1VpqzvVz/IqlkVqXYFNJCYBhhT940HH3zQNY9Tq6Tzzz/fFDCREPACiQOk9dZbz/XfUee2XXfd1efj/qp/0ogRI1xztiWWWCJvWbkv9GG1yiqrhMGR8tloo41cHxR9OejGRbVK0aRyqBpYwY2WKxhS4Bb9UtY6/fuXrn3Ql7mCimjSPN0sFc6PrpNkulL5xNlnseOJs11a6/hjT1IurVtLqZLXkn+2g3etJae2OBZ/rVXyHLXGcbRmMKdrLe71pnIlea+3hlVW96H3uhKelTuDWFbOsppzUpeLgw46yP2r5nJStrYVSPyTqEbc0OgbGkte7Tc10MEHH3zgmrspKFJHtwsuuKBiR6Whub/88svwacTKWPtTLZJqqZZddlkbO3ZsXi2Sqkp9vyQN8KCBGzTPJw3aoGYJ0X5Jfhl/EUAAAQQQQAABBBBAoP0KJA6QFGyoalKjcLzwwgsu8FCTu5tuusl69+5tegaRH7ihEqzqd6TBEPTcIzV1UV+ke+65xzbffHP3y5nGule68cYbXdCjpyGrfPvtt5+br+YfqjbVyGfqDK/BADSCnUa6oyrdEfEfAggggAACCCCAAAIIfC+QuImdtlNgoWG81WZTz6PRiHGq6dE/9c2pZFJNkQZ90PDhGtpZzQo23nhjO/roo91u1IxOy9S0T0FSt27dwtotXw4N963lGoNe6+t5TUceeaRfzF8EEEAAAQQQQAABBBBAwAmUFSB5O9UYrbvuuv5lan81Gp6GEFcgpoBJQU40rbXWWnbXXXe5pngK3grb36s/kp6urH5HaitfieHHo/tnGgEEEEAAAQQQQAABBGpDIHGApNqcUaNGlTz6jz76qOQ6SVcoNTKXH+WuqXwZ6acpGeYjgAACCCCAAAIIIICABBIHSApSBg0alKenUeImTpxoCopUW6PnE5EQQAABBBBAAAEEEGgtgYabbwl3VbfSIKtba3D4mgkEkggkDpB+9atfmf4VSxogYeutt441fHax7ZmHAAIIIIAAAggggEA5Ah1+sWc5m7ENAo0EEo9i1yiHyAwN0vDHP/7RTj/9dPfsocgiJhFAAAEEEEAAAQQQQACBqheoaICko11qqaVs2rRpbnS7qj96CogAAggggAACCCCAAAIIRAQqGiDNnDnTLrnkEjdS3NJLLx3ZDZMIIIAAAggggAACCCCAQPULJO6DdMUVV7hnIBUe2rx589wgDV9//bUNGzbMunfvXrgKr1MSmNexc5jzgg6JT2m4LRMIIIAAAggggAACCLR3gcR303PnzrUZM2Y0ctPzhX784x+7QRqOOuqoRsuZkY7AvE5dbd8/vZdO5uSKAAIIIIAAAggggEA7E0gcIB1++OGmfyQEEEAAAQQQQAABBBBAoNYEKtoHqdZwOB4EEEAAAQQQQAABBBBoXwKJa5BGjhxpo0aNSqS066672oUXXphoG1ZGAAEEEEAAAQQQQAABBFpbIHEN0iqrrGLLLLOMTZw40Y1Wt95667l+R6uvvrp99dVXbv6PfvQjGzRoUPhviSWWaO3jYn8IIIAAAggggAACCFRc4LzzzrMRI0bY+PHji+b917/+1S3XY2+Ubr75Zrv33nuLrls4880337RzzjmncHZVvNYYBDrut99+O68877//vpv/6KOP5s2fOnWqm//BBx/kzc/Ci8Q1SHoY7FtvvWXnn3++aTAGDc7g05dffmnbb7+9rbjiikVHuvPr8RcBBBBAAAEEEEAAgSwKnHvuuTZp0iSbP3++nXbaaXmH8Mknn9jw4cMtl8vZQQcdZL169bJbbrnFVFmwww475K1b7IUCJAVgv//974stbtN5PXr0sCuvvNId2ymnnBKW5cYbb3QOm266qf3sZz8L5z/11FN26qmnZnLsgsQ1SNdff72ts8469tvf/jYvOJLG4osv7gKn6667zj0sNhRiAgEEEEAAAQQQQACBGhFQS6lbb7210dGMHj3allxyybz5d9xxh3tOaN7MJl7ss88+LvhqYnGbz95iiy3s6aefzivHAw88YPvtt5+bP3369HDZf/7zH1t77bWtb9++4bysTCQOkCZMmGD9+/dv8vgUXS5YsMBUm0RCAAEEEEAAAQQQQKDWBH7+85/be++9Z//973/zDk3N6fbaa6+8eX/729/sH//4h5v3/PPP2xlnnGEvv/yyHXjggbbddtu5ygXdOyu98MILdvTRR7tpPWP017/+tduPapS07umnn+7us//973/bnnvu6VpzRcugPv+qsYqmk046yXzzNzX/e+ihh+yyyy6znXbayQ499FD78MMPTff3GqV6jz32sNtuuy26ed60AiSV0Zf3m2++sRdffNFOOOEE9wzUxx57LFz/ySeftK222ip8rf3o2LbZZhvbbbfdTDVxenyQT1r+5z//2R3nySefbKqB0utoUkWNjltlv+CCC1wtXnR5paYTB0ibbbaZa0dZrN2lqhP/8pe/WJ8+fWz55ZevVBnJBwEEEEAAAQQQQACBqhFQkzk1KYsGI+pro6BJgUw0KSDxtS5ariBGNS5LLbWUbbDBBnbiiSe6oEnbqD/PDTfc4DZXEKImbVtvvbVrtbX++uu7/kkKMBQ4DBkyxK2/yy67hLu777777Lnnngtfa0JlVPcYpQcffNAFZv/617/M1wbtuOOOpjwWWmghW3nllV2A98orr7j1C/9TEzrVEr3xxhtukY5N3W9Uo6b87r//fjdf/ZWUhw+QFDesscYapoBKx67uOGqe+Kc//cmt//XXX7vmeQ8//LALflT7pHJFa+nUtefYY4912+rY1VdLgWoaKXEfpJ133tnOOussW2uttRywHg6rWqOPPvrIFNXpBCh6rqurS6O85IkAAggggAACCCCAQCOB+SuvHs7rMOxX1uH448LXaUyopkijO6tWR0n3vwo0unbt2uzuNKiZalo0wJnSp59+agoMCmtLfCbaj+69lcaNG2f//Oc/7eOPP7aBAwfa3nvv7fo3qe+Sz89v19Rf3bffddddVl9f74I01eboOI455hi3iYKTu+++23WpKcxDgaHu/RXwqfmcmtcpgFNSMHTmmWe66WeffdY5KJBRUrl1HFdccYV16NDBfvnLX9rkyZNNNWpK6nc1c+ZM03aKIQ455BBbbbXVrKGhwS1/9913TbVfqonTMSspOFKgpfIqWK1kShwg9evXz1WlqXCKgH3BVSiNXqcoVdVzJAQQQAABBBBAAAEEWk1g3HvhrnLBIAppp913392OOOIIV5uy5pprugBJN/qlUrdu3fKCmaWXXtrdWze13U9+8pNwkVpoKUBRcKTk+/d88cUXeXmGGxSZUFkVHCn5Fl+qlfJpscUWM+XXVFIt0jPPPGNHHnmkq5G6/PLL3aoKlA4++GDTQBVqXqdWZ506dXLLlL9eKzB855133Eh4jzzyiAvutIKaHG677bZ5FSwa1OKee+5x22u5Wqq99NJLYe2VFvTs2dNt2+YBkgqjk6FIV9VnqmJTtdgKK6zg/nkIrUdCAAEEEEAAAQQQQKAWBXQ/PHToUNcMTAGH+t8reFAfneZS9+7d8xarRkU3/02lRRddNG+RRsbzqViLrcK8ov18tJ26whQmNa+Lm9SUTn2X1PdJTeY233xzt6kCPTXRUxM/BUjR5m9aVwFU586dbeONN7af/vSnrqmeapaUFEuouWE09e7dO3z53XffuaCuS5cueUGUgjTVNFU6Ja5BihZAbS0/++wzN4Shno+kZnaqRSIhgAACCCCAAAIIIFDrAmo2pr4weuyNWlD5mpm2Om4FENGR5DQUuWp0KplUW6MapptuuskFOqrF8UlBkAZXUE2PmtP5pGHBFTyp1sg/IkjN9PxgDwpyXn31Vb+6+6v+Uj6pIkaDVqhfkm+2p201crb6P1U6JR6kQQXQA6I22WQTUxWdLoZrrrnGlUuv1X5yzpw5lS4n+SGAAAIIIIAAAgggUFUCu+66qxsF7pJLLrFf/OIXbV42BQt6KK0Ge9CDWjWogQKJwlqllhRUNVgaMEJN63z/I5+fXmuQCXXJiQYu6ruk2qZZs2a5sqiPk0bL8zGD+j8pIFJ5VdukUezUjM8n1VKttNJKLs4YM2aMzZ492xR0/eEPf3CDS/j1KvU3cYAkbI3OodojHcSGG27oyiJ8tS/UiBSHHXZYpcpHPiUEOs2fbWddtn34b6uXri+xBYsRQAABBBBAAAEEKiGwyCKLuMEJ1K9oo402qkSWLcpD9+ZqzaXBC/R8UtW6qElcsaZ4LdmR8lSzt8IASbVLCoL86HV+H3p+6sILL+zKpKaJF198sRvmW/GEYgsN+KD+RuqjJEc1U9SDdv2AF+rCo6BKAzloMArloaHLFYxputIpcRM7RYtTpkxxfY/U1lBjkSupukyjdwwYMMAuuugi90+jZJBSFgiarC73xf+GbtSeXp+2Wco7JHsEEEAAAQQQQKD9ChQ+61M1NtGk/jXRGhvd2PukIa71L5r0DCH9U9LobvqnpOAgmo/mqSJC/3wq7L+kh9QquFAZVdNT2N9Jw3tHk4beLtzH7bffHl2l6LRqb/SvMGl/qt0pTGoip35J6mukfki+H9Xw4cPdqhrTQMOFv/baa+GmWqaaKJ9Ug6RR7hSHqOlgsb5Uft2W/k1cg6SCaxQKBUfFkqoXVWg9cIqEAAIIIIAAAggggAACrSug2qPC4Kh1S1B8bwpqfHAUXUP9ltQqTc3q1IdKQaeeAaU+XoVJNVFpBkfaX+IaJGFrqL2mkqq+lNIueFP7Zz4CCCCAAAIIIIAAAghkR0DPPdKznTRM+NixY13/pTPOOMMOOOCANjmIxDVI6623nulhTXfeeWejAqsN4YgRI0zVe+qMRUIAAQQQQAABBBBAAAEEmhPQ6H9nn322aQAGVbboWUn+wbXNbZfWssQ1SPvvv78btUJP3VVVmIIidUxTe0kFTeqYNXr06LTKS74IIIAAAggggAACCCBQowIaqrytU+IASRHefffdZ8cff7xde+211tDQ4I5Bze769+/vgic/cENbHxz7RwABBBBAAAEEEEAAAQSSCCQOkCZPnmx6Iu9VV11l559/vr333nv21VdfuZEnNPqEhuEjIYAAAggggAACCCCAAAJZFEjcB0mBkUawGzdunPXu3dvWXXdd23bbbd3DmwiOsngJUGYEEEAAAQQQQAABBBDwAolrkNRpSmmppZbyefAXAQQQQAABBBBAAIE2Fehw9WXh/utWWzWcZgKBpAKJa5AOP/xwN4T3SSedVPRBUEkLwPoIIIAAAggggAACCLRUoMP+/2f+X91667Y0O7ZvxwKJa5A0Rvlqq61mI0eOtAsvvNDVJBV75tErr7zSjlk5dAQQQAABBBBAAAEEEMiiQOIASYM0fPfddzZ48ODweP1IduEMJhBAAAEEEEAAAQQQQACBDAokDpD0pFv9IyGAAAIIIIAAAggggAACtSaQOECqNYCsH8+CjvV29bYjwsP4cMk1wmkmEEAAAQQQQAABBBBAIJlAyQBpxowZdtddd7nhvAcNGpQsd9ZOXaChQ709uN6w1PfDDhBAAAEEEEAAAQQQaA8CJUex00Ng9913X3vooYfyPF5++WW7/PLLbcGCBXnzeYEAAggggAACCCCAAAIIZFWgZIDU1IHdc8899pvf/Mbmzp3b1CrMRwABBBBAAAEEEEAAAQQyJVB2gJSpo6SwCCCAAAIIIIAAAggggEAMAQKkGEisggACCCCAAAIIIIAAAu1DgACpfZxnjhIBBBBAAAEEEEAAAQRiCBAgxUBiFQQQQAABBBBAAAEEEGgfAiWH+fYM77//vj311FP+pU2cONFNP/3009a1a9dwvp/YeOON/SR/EUAAAQQQQAABBBBAAIFMCMQOkEaNGmX6V5i22mqrwlnudS6XKzqfmQgggAACCCCAAAIIIIBAtQqUDJB69+5tI0b8f3t3AiZXVSYM+HS6OyEJIQSS8EPCzrCKAzoaFlFZBEQ2cVBmFERAR2TVGQQVBcWBQUdAcWNgQMZhWEQUnGEfx41F2UUgQFhlC1nIStJJL399F6rsTjpJVVK3U7f6vc+T9K17T537nfdUV/fX59xTX23U+MVFgAABAgQIECBAgACBugmsMEEaPXp0+spXvlK3C6qIAAECBAgQIECAAAECjSpgkYZG7RlxESBAgAABAgQIECAw4AISpAEnd0ECBAgQIECAAAECBBpVYIVT7Bo1cHG9IdDS3ZV2fuS/KxwvjN8yPb/eNpXHdggQIECAAAECBAgQqF5AglS9VUOWbOtanE667sRKbNftdrwEqaJhhwABAgQIECBAgEBtAqbY1ealNAECBAgQIECAAAECTSwgQWriztU0AgQIECBAgAABAgRqE5Ag1ealNAECBAgQIECAAAECTSwgQWriztU0AgQIECBAgAABAgRqE5Ag1ealNAECBAgQIECAAAECTSwgQWriztU0AgQIECBAgAABAgRqE5Ag1ealNAECBAgQIECAAAECTSwgQWriztU0AgQIECBAgAABAgRqE5Ag1ealNAECBAgQIECAAAECTSwgQWriztU0AgQIECBAgAABAgRqE5Ag1ealNAECBAgQIECAAAECTSwgQWriztU0AgQIECBAgAABAgRqE2irrbjSDSfQktK00RMqYc1fY63Kvh0CBAgQIECAAAECBGoTkCDV5tVwpRe3rZGOP/nOhotLQAQIECBAgAABAgSKKGCKXRF7TcwECBAgQIAAAQIECOQiIEHKhVWlBAgQIECAAAECBAgUUUCCVMReEzMBAgQIECBAgAABArkISJByYVUpAQIECBAgQIAAAQJFFJAgFbHXxEyAAAECBAgQIECAQC4CEqRcWFVKgAABAgQIECBAgEARBSRIRew1MRMgQIAAAQIECBAgkIuABCkXVpUSIECAAAECBAgQIFBEAQlSEXtNzAQIECBAgAABAgQI5CIgQcqFVaUECBAgQIAAAQIECBRRQIJUxF4TMwECBAgQIECAAAECuQhIkHJhVSkBAgQIECBAgAABAkUUkCAVsdfETIAAAQIECBAgQIBALgJtudSq0gETaO9cmC789m6V69046ah0w7uOrTy2Q4AAAQIECBAgQIBA9QISpOqtGrNkT0pj5r1aiW34onmVfTsECBAgQIAAAQIECNQmIEFagVdHR0eaM2dOn1JdXV1p4cKFad68+iQjs2fP7lN/ng86OzvTtGnT8rxETXX39JQyvNL2+uuvp7CuZqu2XDV1NUKZeH3Vq0/CM16f9aqvEXxWZwxhGduMGTNSS0vL6gylpmsvWLCgpvKrUjjev6p9vXV3d2eXiu9326oJlN8742dRtf6rdsXmf3a8Plkuu5/jPXDs2LHLLuAMgSYSkCCtoDOHDh2a1l133T6l5s6dm9rb29Maa6zR5/jKPmhtbV3Zp9b8vLjWku2puZI6PmHRokXptddeS8OHD0+jRo2qqubok2ba1lxzzbr1SfzSNH369LrV10zOK9OWWbNmZYn7Ouusk4YMKc4tm/V6b6rGLL5vq31PmT9/fpZojhgxopqqlVmOQPyxKxL3YcOGpdGjRy+npFPVCkRyVO1rudo6lSNAoJgCEqQV9Fv8xaS/vxzHsXr9wlSvelbQlOx0PeOu5norKlNuey1x9dcfK7pOI58Pg7LDqsYZCVItlqt6vcHy/KKZDuT3SC2v34iraJaN+hovv2fwrG8PlV3rW6vaCBAomkBx/iRaNFnxEiBAgAABAgQIECBQOAEJUuG6TMAECBAgQIAAAQIECOQlIEHKS1a9BAgQIECAAAECBAgUTkCCVLguEzABAgQIECBAgAABAnkJSJDyklUvAQIECBAgQIAAAQKFE5AgFa7LBEyAAAECBAgQIECAQF4CEqS8ZNVLgAABAgQIECBAgEDhBCRIhesyARMgQIAAAQIECBAgkJeABCkvWfUSIECAAAECBAgQIFA4gbbCRSzgPgKdre3pvEN/UDn24tgtKvt2CBAgQIAAAQIECBCoTUCCVJtXw5XuGdKafr/tfg0Xl4AIECBAgAABAgQIFFHAFLsi9pqYCRAgQIAAAQIECBDIRUCClAurSgkQIECAAAECBAgQKKKABKmIvSZmAgQIECBAgAABAgRyEZAg5cKqUgIECBAgQIAAAQIEiiggQSpir4mZAAECBAgQIECAAIFcBCRIubCqlAABAgQIECBAgACBIgpIkIrYa2ImQIAAAQIECBAgQCAXAQlSLqwqJUCAAAECBAgQIECgiAISpCL2mpgJECBAgAABAgQIEMhFQIKUC6tKCRAgQIAAAQIECBAoooAEqYi9JmYCBAgQIECAAAECBHIRkCDlwqpSAgQIECBAgAABAgSKKNBWxKDF/BeBId2d6f2/v6xyYMqEHdLjG72j8tgOAQIECBAgQIAAAQLVC0iQqrdqyJKtXZ3piFu/Xontut2OlyBVNOwQIECAAAECBAgQqE3AFLvavJQmQIAAAQIECBAgQKCJBSRITdy5mkaAAAECBAgQIECAQG0CEqTavJQmQIAAAQIECBAgQKCJBSRITdy5mkaAAAECBAgQIECAQG0CEqTavJQmQIAAAQIECBAgQKCJBSRITdy5mkaAAAECBAgQIECAQG0CEqTavJQmQIAAAQIECBAgQKCJBSRITdy5mkaAAAECBAgQIECAQG0CEqTavJQmQIAAAQIECBAgQKCJBSRITdy5mkaAAAECBAgQIECAQG0CEqTavJQmQIAAAQIECBAgQKCJBSRITdy5mkaAAAECBAgQIECAQG0CbbUVV7rRBHpaWtITE3ashDVjrQ0q+3YIECBAgAABAgQIEKhNQIJUm1fDle5sG5a+fMzPGy4uAREgQIAAAQIECBAoooApdkXsNTETIECAAAECBAgQIJCLgAQpF1aVEiBAgAABAgQIECBQRAEJUhF7TcwECBAgQIAAAQIECOQiIEHKhVWlBAgQIECAAAECBAgUUUCCVMReEzMBAgQIECBAgAABArkISJByYVUpAQIECBAgQIAAAQJFFJAgFbHXxEyAAAECBAgQIECAQC4CEqRcWFVKgAABAgQIECBAgEARBSRIRew1MRMgQIAAAQIECBAgkIuABCkXVpUSIECAAAECBAgQIFBEAQlSEXtNzAQIECBAgAABAgQI5CIgQcqFVaUECBAgQIAAAQIECBRRQIJUxF4TMwECBAgQIECAAAECuQi05VKrSgdMoH3xwvTjs7eqXO+63U5I1+zxT5XHdggQIECAAAECBAgQqF5AglS9VcOWbOkVWUvq6fXILgECBAgQIECAAAECtQiYYleLlrIECBAgQIAAAQIECDS1gASpqbtX4wgQIECAAAECBAgQqEVAglSLlrIECBAgQIAAAQIECDS1gASpqbtX4wgQIECAAAECBAgQqEVAglSLlrIECBAgQIAAAQIECDS1gASpqbtX4wgQIECAAAECBAgQqEVAglSLlrIECBAgQIAAAQIECDS1gASpqbtX4wgQIECAAAECBAgQqEVAglSLlrIECBAgQIAAAQIECDS1gASpqbtX4wgQIECAAAECBAgQqEVAglSLlrIECBAgQIAAAQIECDS1gASpqbtX4wgQIECAAAECBAgQqEWgrZbCyjaeQGfb0PSVT1xbCWz66A0q+3YIECBAgAABAgQIEKhNQIJUm1fDle5pGZIe3+gdDReXgAgQIECAAAECBAgUUcAUuyL2mpgJECBAgAABAgQIEMhFQIKUC6tKCRAgQIAAAQIECBAoooAEqYi9JmYCBAgQIECAAAECBHIRkCDlwqpSAgQIECBAgAABAgSKKCBBKmKviZkAAQIECBAgQIAAgVwEJEi5sKqUAAECBAgQIECAAIEiCkiQithrYiZAgAABAgQIECBAIBcBCVIurColQIAAAQIECBAgQKCIAhKkIvaamAkQIECAAAECBAgQyEVAgpQLq0oJECBAgAABAgQIECiigASpiL0mZgIECBAgQIAAAQIEchGQIOXCqlICBAgQIECAAAECBIoo0FaUoJ966ql09913pwkTJqRJkyal4cOH9wn9+eefT3feeWdaZ5110i677JLWXHPNPufnzp2b7rjjjhRf4/kbbbRRn/NFfdDatTgd9stvVsL/06a7poe2eE/lsR0CBAgQIECAAAECBKoXKMQI0plnnplOPvnkFEnQRRddlI4//vg0e/bsSit//OMfp8MPPzw9+uij6ZprrknHHntseu211yrnn3nmmXTQQQela6+9Nv3pT39KRx11VJZsVQoUeGdId1c68M6LKv+2fv4PBW6N0AkQIECAAAECBAisXoGGH0F6+OGH069+9at05ZVXpvXXXz8tWrQoffCDH0w33XRTOuyww7Kk6bLLLkvf/va30w477JA6OzvTpz/96XT11VdnX4P3nHPOSQceeGA66aSTUktLS7r88svT+eefn6666qrs8ertgua6+uLFi1N3d3fVjYr+7OjoSG1tbdnXap7Y1dVVTTFlCBAgQIAAAQIECNQs0PAjSGPHjk3nnntulhxF6+IX6bXWWivNnDkza+wf/vCHtMEGG2TJUfn8vvvum2677bbs/IwZM9Jjjz2WjSBFchTb/vvvn1566aVsxCk74L+6Cey0005pjTXWqPpf9OWmm26axo8fX/Vzfvazn9UtXhURIECAAAECBAgQ6C3Q8CNIMWoU/2KbMmVKuvHGG7Ppdfvss0927OWXX87uS8oevPlfJEzTp0/PRjJeeeWV7GgcK2/rrrtuGjp0aHr11VfTdtttVz7c79cY3eg9nS8KxQjJwoULs/uZ+n1SjQeXrL/Gp9dUPEbYot15bTGCFNvYjXfO6xJpxp/vTT3db1wnt4sMYMVz5sypa5/ECFuefTyANKv9UuXRyng/Kf+BZbUHVUUACxYsqKJUfYrMmjWr6tdbeXR5/vz59bn4IK6lp6cna338LPL9Xp8XQrw+WS7bMt4Dx40bt+wCzhBoIoGGT5DK1tOmTUvHHXdcev3117MRoA033DA7FQlQjEL03kaNGpUlMZF4RAI1bNiw7N+SZXrfp9T7XO/9+CFU/kFUPr7k4/Lxlf1a7/pWFEfe1xvS2p7efWR+ozw3nrdjWjj35RU1szDnoz/q1SflespfC4PQ4IHyXHYHhU2tPrWWX/bVB++ZsuHK+A9etRW3vOy64pJKECDQzAKFSZDirxa33HJLNop01llnpdNPPz194xvfSO3t7dl9R707KUZJYhsxYkS/5+Nc/GU4zq9oK08X610uEq8YgVpyJb3eZWrZjwRuoLaYorjeeuvldrnoD1ttAqNHj65bn8QP9/hjQkxZtK26QEzljVHkeP9pbW1d9QoHqIZ6vTdVE+6YMWOqfv3OmzcvG4kbOXJkNVUrsxyB+DkX3+vR12uvvfZySjpVrcDUqVOrfi1XW6dyBAgUU6Dh70FaknWLLbZIH/7wh1PcexTTNOIepVi6u/cWU5bih3YkHnE+kqEYeeq9RZny1L3ex+0TIECAAAECBAgQIDB4BRo+QYrV6D772c/26aFIjGKucMyHjRv8J0+e3GcU6ZFHHqnclzRx4sRsYYc4Vt5i0YZ4fu/7ksrnfCVAgAABAgQIECBAYPAKNHyC9N73vjc98MAD6Re/+EWWBD300EPppz/9aYrjMUVur732ynrviiuuyJKep59+OlvIIT4XKbaYvrT33nunWAo8pnfEDa2XXHJJipXu3GyYEfmPAAECBAgQIECAAIE3BRo+QYr7ZeLzi77zne+kWLkuPiQ2Vp77/Oc/nzUhptHFPUmx9HMkPTHadMghh6Rddtml0snxuUhxz9ABBxyQDj744GxE6YQTTqict0OAAAECBAgQIECAAIEQKMQiDfHBsJHcxIp1sUT3kjcg77jjjunnP/95ihssY1RoyJC+eV/cj3TBBRekuO8obrR2g7AXPwECBAgQIECAAAEC/QkUIkGKwGP1tbifaHnbilZnW3I58OXV5RwBAgQIECBAgAABAoNPoO9Qy+BrvxYTIECAAAECBAgQIECgIlCYEaRKxHb6CHSXphP+Yau9K8deHLtFZd8OAQIECBAgQIAAAQK1CUiQavNquNJdrUPTtw67uOHiEhABAgQIECBAgACBIgqYYlfEXhMzAQIECBAgQIAAAQK5CEiQcmFVKQECBAgQIECAAAECRRSQIBWx18RMgAABAgQIECBAgEAuAhKkXFhVSoAAAQIECBAgQIBAEQUkSEXsNTETIECAAAECBAgQIJCLgAQpF1aVEiBAgAABAgQIECBQRAEJUhF7TcwECBAgQIAAAQIECOQiIEHKhVWlBAgQIECAAAECBAgUUUCCVMReEzMBAgQIECBAgAABArkISJByYVUpAQIECBAgQIAAAQJFFJAgFbHXxEyAAAECBAgQIECAQC4CEqRcWFVKgAABAgQIECBAgEARBdqKGLSY+wqsNX965UBH+4jUMXRE5bEdAgQIECBAgAABAgSqF5AgVW/VkCXbFy9MF//r2yuxXbfb8enqPU6pPLZDgAABAgQIECBAgED1AqbYVW+lJAECBAgQIECAAAECTS4gQWryDtY8AgQIECBAgAABAgSqF5AgVW+lJAECBAgQIECAAAECTS4gQWryDtY8AgQIECBAgAABAgSqF5AgVW+lJAECBAgQIECAAAECTS4gQWryDtY8AgQIECBAgAABAgSqF5AgVW+lJAECBAgQIECAAAECTS4gQWryDtY8AgQIECBAgAABAgSqF5AgVW+lJAECBAgQIECAAAECTS4gQWryDtY8AgQIECBAgAABAgSqF5AgVW+lJAECBAgQIECAAAECTS4gQWryDtY8AgQIECBAgAABAgSqF5AgVW+lJAECBAgQIECAAAECTS7Q1uTta/rmLW4blk484TeVds4bPrqyb4cAAQIECBAgQIAAgdoEJEi1eTVe6ZaWNHWdjRsvLhERIECAAAECBAgQKKCAKXYF7DQhEyBAgAABAgQIECCQj4AEKR9XtRIgQIAAAQIECBAgUEABCVIBO03IBAgQIECAAAECBAjkIyBBysdVrQQIECBAgAABAgQIFFBAglTAThMyAQIECBAgQIAAAQL5CEiQ8nFVKwECBAgQIECAAAECBRSQIBWw04RMgAABAgQIECBAgEA+Aj4HKR/Xhqy1q7MjTZ8+PX3ta1/LLb6XX345pZ7cqlcxAQIECBAgQIAAgVwFJEi58jZW5d2di9KMGTPSGWeckWtgLUO8rHIFVjkBAgQIECBAgEBuAn6TzY22MSsePmr9tOOB38otuLuvOjL19HTnVr+KCRAgQIAAAQIECOQpIEHKU7cB624dOiL9vy32yC2ylpYhEqTcdFVMgAABAgQIECCQt4BFGvIWVj8BAgQIECBAgAABAoURMIJUmK7qP9DWrkXp0zecWjl571Z7pd9v+4HKYzsECBAgQIAAAQIECFQvIEGq3qohSw7p7k7v/uN1ldimj95AglTRsEOAAAECBAgQIECgNgFT7GrzUpoAAQIECBAgQIAAgSYWkCA1cedqGgECBAgQIECAAAECtQlIkGrzUpoAAQIECBAgQIAAgSYWkCA1cedqGgECBAgQIECAAAECtQlIkGrzUpoAAQIECBAgQIAAgSYWkCA1cedqGgECBAgQIECAAAECtQlIkGrzUpoAAQIECBAgQIAAgSYWkCA1cedqGgECBAgQIECAAAECtQlIkGrzUpoAAQIECBAgQIAAgSYWkCA1cedqGgECBAgQIECAAAECtQlIkGrzUpoAAQIECBAgQIAAHtkNcgAAKMtJREFUgSYWkCA1cedqGgECBAgQIECAAAECtQm01VZc6UYT6B7Smm57+0crYU2ZsENl3w4BAgQIECBAgAABArUJSJBq82q40l2t7emS/c9uuLgERIAAAQIECBAgQKCIAqbYFbHXxEyAAAECBAgQIECAQC4CEqRcWFVKgAABAgQIECBAgEARBSRIRew1MRMgQIAAAQIECBAgkIuABCkXVpUSIECAAAECBAgQIFBEAQlSEXtNzAQIECBAgAABAgQI5CIgQcqFVaUECBAgQIAAAQIECBRRQIJUxF4TMwECBAgQIECAAAECuQhIkHJhVSkBAgQIECBAgAABAkUUkCAVsdfETIAAAQIECBAgQIBALgJtudSqUgIEVigw65VHsjJnnXVWuuiii1ZYvpoCPT09qbOzM7W3t/cpfvTRR6f4ZyNAgAABAgQIEFi+gARp+T7OEshNoLNjblb3U089leJfntvee++dZ/XqJkCAAAECBAg0jYAEqWm6UkOKKvD2g76dNvrrD+cS/vMP/STdd/2J6a677krnn39+LtcoV7rtttumffbZp/zQVwIECBAgQIBAIQUkSIXstl5Bl6ZUbfTq5MqB2SPXTbPXHF95bKcYAi0tLbkEumDuy1m9t956a4p/eW6HH364BClPYHUTIECAAAECAyIgQRoQ5vwu0t7Zkb75w30rF7hut+PT1XucUnlsh0AITNhm/zRhuwNzwVg4b2r6481fzqVulRIgQIAAAQIEBlpAgjTQ4q5HYDUIjBq/VZqYU4I0b+YzEqTV0KcuSYAAAQIECOQjYJnvfFzVSoAAAQIECBAgQIBAAQUkSAXsNCETIECAAAECBAgQIJCPgAQpH1e1EiBAgAABAgQIECBQQAH3IFXRafHhm/1tyzreX9nlHatXPcu7hnME8haI13GzvpaL1raB7IdabKJsrNg4kPHl/bpfXfWXDWvxX12xFum6ZdcixTxQsea12upAxe86BGoRkCCtQKujoyPNmjWrT6nu7u60YMGCNGfOnD7HV/bB7NmzV/apnkegYQQWLlyYXn311YaJpx6BxPd6bNOnT89+sa9HnQNRR/TFQG3x/lhtv5d/+Zw3b95Ahde01ylbNuP33erqtPh+r/a1vLpiXJ3XjQRp/HgfI7I6+8C1B05AgrQC62HDhqX11luvT6lIaIYOHZqGDx/e5/jKPohr2AgUXSC+H5b8Xil6m2bOnJnijyTjxo1Lra2thWlOvd6bqmnwmDFjqu73SIzil6yRI0dWU7UyyxHo7OxM06ZNy34Orb322ssp6VS1AlOnTq36tVxtncoRIFBMAQlSMftN1AQaRmDRgjdGQO+///506qmn5hrXJptsko499thcr6FyAgQIECBAYHALSJAGd/9rPYFVFujseGOq6SOPPJLiX57brrvuKkHKE1jdBAgQIECAQJIgeREQIFAXgfGbvSdt/e6T61LXkpX09HSn317+oSUPe0yAAAECBAgQqLuABKnupCokMDgFhq05Lo3deOdcGh8Jko0AAQIECBAgMBACPgdpIJRdgwABAgQIECBAgACBQghIkArRTYIkQIAAAQIECBAgQGAgBEyxGwjlHK+xuH2NdMQXHqtcobO1vbJvhwABAgQIECBAgACB2gQkSLV5NWTpjqEjGjIuQREgQIAAAQIECBAomoApdkXrMfESIECAAAECBAgQIJCbgAQpN1oVEyBAgAABAgQIECBQNAEJUtF6TLwECBAgQIAAAQIECOQmIEHKjVbFBAgQIECAAAECBAgUTUCCVLQeEy8BAgQIECBAgAABArkJSJByo1UxAQIECBAgQIAAAQJFE5AgFa3HxEuAAAECBAgQIECAQG4CPgcpN1oVEyBQL4Genp6sqqlTp6ZLL720XtX2W8+IESPSYYcd1u85BwkQIECAAIHmF5AgNX8fayGBJhB4I0GaMmVKOvroo3Ntz/rrry9BylVY5QQIECBAoLEFJEiN3T+iI0Cgl8DIMZukLd91Qq8j9d39021npfJoVX1rVhsBAgQIECBQFAEJUlF6SpwECKRha45Lm77to7lJTP71eaW6u3KrX8UECBAgQIBA4wtYpKHx+0iEBAgQIECAAAECBAgMkIARpAGCzusybZ0d6dQrj6pU/7vtD06/3uHQymM7BAgQIECAAAECBAhULyBBqt6qIUu2lFb3euvTv6vENmXCDpV9OwQIECBAgAABAgQI1CZgil1tXkoTIECAAAECBAgQINDEAkaQmrhzNY0AAQIECBBYPQJXXXVVOvfccwfk4scff3zuH4EwIA1xEQINIiBBapCOEAYBAgQIECDQPALTpk1LDz74YGoZ0pZaWvKZsNPT0516ujvTK6+80jxwWkKgAQQkSA3QCUIgQIAAAQIEmlPgbw6+MG24/QdzadzLT9ya7rryiFzqVimBwSyQz580BrOothMgQIAAAQIECBAgUFgBCVJhu07gBAgQIECAAAECBAjUW0CCVG9R9REgQIAAAQIECBAgUFgBCVJhu07gBAgQIECAAAECBAjUW0CCVG9R9REgQIAAAQIECBAgUFgBCVJhu07gBAgQIECAAAECBAjUW0CCVG9R9REgQIAAAQIECBAgUFgBCVJhu07gBAgQIECAAAECBAjUW8AHxdZbdIDr62ptSz95z8mVqz628aTKvh0CBAgQIECAAAECBGoTkCDV5tVwpbuHtKVr3/vZhotLQAQIECBAgAABAgSKKGCKXRF7TcwECBAgQIAAAQIECOQiIEHKhVWlBAgQIECAAAECBAgUUUCCVMReEzMBAgQIECBAgAABArkISJByYVUpAQIECBAgQIAAAQJFFJAgFbHXxEyAAAECBAgQIECAQC4CEqRcWFVKgAABAgQIECBAgEARBSRIRew1MRMgQIAAAQIECBAgkIuABCkXVpUSIECAAAECBAgQIFBEAQlSEXtNzAQIECBAgAABAgQI5CIgQcqFVaUECBAgQIAAAQIECBRRQIJUxF4TMwECBAgQIECAAAECuQhIkHJhVSkBAgQIECBAgAABAkUUaCti0GL+i0BLT3fa/unfVQ5MHbNRmrrOJpXHdggQIECAAAECBAgQqF5AglS9VUOWbOtclL70n4dXYrtut+PT1XucUnlshwABAgQIECBAgACB6gVMsaveSkkCBAgQIECAAAECBJpcQILU5B2seQQIECBAgAABAgQIVC8gQareSkkCBAgQIECAAAECBJpcwD1ITd7BmkeAAAECBIokcOWVV6bJkycPSMif/OQn08SJEwfkWi5CgEBxBCRIxekrkRIgQIAAgaYXuOqqq9INN9wwIO3cb7/9JEgDIu0iBIolIEEqVn+JlgABAgQIDAqBd/7tv6X2NUbn0tZn7v1RemnyTbnUrVICBIovIEEqfh9qAQECBAgQaDqBcZvskoaNHJtLu6Y+eXsu9aqUAIHmELBIQ3P0o1YQIECAAAECBAgQIFAHAQlSHRBVQYAAAQIECBAgQIBAcwhIkJqjH7WCAAECBAgQIECAAIE6CEiQ6oCoCgIECBAgQIAAAQIEmkNAgtQc/agVBAgQIECAAAECBAjUQcAqdnVAXN1VLGwfUQlhcevQyr4dAgQIECBAgAABAgRqE5Ag1ebVcKUXt6+RPv7FxxouLgERIECAAAECBAgQKKKAKXZF7DUxEyBAgAABAgQIECCQi4AEKRdWlRIgQIAAAQIECBAgUEQBCVIRe03MBAgQIECAAAECBAjkIiBByoVVpQQIECBAgAABAgQIFFFAglTEXhMzAQIECBAgQIAAAQK5CFjFLhdWlRIgQIDAqgrcdttt6cwzz1zVaqp6/kc+8pF04oknVlVWIQIECBBobgEJUnP3r9YRIECgsALTpk1Ld95554DEP2nSpAG5josQIECAQOMLSJAav49ESIAAgUEt8NZ9z0qbv/OYXAxmvnBf+vWl++dSt0oJECBAoJgCEqRi9puoCRDIQaCrsyN1dHSlW2+9Nat9zpw5afHixWnttddOra2tdb3iXnvtlYYMcRtodagtqaWlpbqitZbKq95a41CeAAECBBpGQILUMF0hEAIEVrfA4gWvpdde70r77LNP7qFMmTIlDRs2LJfrzJ8/P5d6VUqAAAECBAaDgARpMPSyNhIgULVAa/uI9Fe7HFt1+VoLPvG776buro60xRZb1PpU5QkQIECAAIEBEJAgDQCySxAgUByBtmFrpm3fe0puAT9198VZgrTB1vuVpo3lM8XulSn/l7oWG0XKrRNVTIAAAQJNLSBBauru1TgCBBpV4B0f+kFqbctnit0tF+6S5s98ulGbLi4CBAgQINDQAhKkhu6eFQfX3rkwnX3xgZWC//u2v0s3T/pE5bEdAgQIECBAgAABAgSqF5AgVW/VmCV7Utro1ccrsY2eP72yb4cAAQIECBAgQIAAgdoEJEi1eSlNgAABAiWBRQtmZQ733Xdf1UugL1iwIFuue4011qjK8KGHHqqqnEIECBAgQKCeAhKkemqqiwABAoNEYPbUR7OWnnHGGYOkxZpJgAABAoNFYNAkSHPnzk133HFHiq+TJk1KG2200WDpY+0kQIBAbgIT3/LBNGrdzXOp/+Unb0+zXnowl7rLlS6c92q2+9vf/jaddtpp5cO5fN12223TEUcckUvdKiVAgACB+gkMigTpmWeeSUcffXTabLPN0oQJE9JFF12Uvv71r6eddtqpfpJqIkCAwCAU2HD7Q9L6W74vl5Z3vD4j9wRp0eszs9jvvffeFP/y3A466CAJUp7A6iZAgECdBAZFgnTOOeekAw88MJ100knZ/PfLL788nX/++emqq67KHtfJUjUECBAgUFCBCdsekDZ/51G5RL9owex099VH5lL3QFf66KOPpriXLM9t1qw37m/L8xrqJkCAwPIEmj5BmjFjRnrsscfSF77whUoytP/++6dLLrkkxRv9dttttzyf1NNTWiZuiS2Olf8tcWqlHnZ3d2fP6+nuKn24Y20/eFoXL+xzzZ6uzuXXUYq91mv0ucAKHpS18rxGSm9cpau0xHle1+np6cpa2t21KL9rlPo7tu6uxfldo1R3bD05XqOrZJRdo3sFr72s1Mr9112qO9t6unOzqkQ2kN8jpfbksr1Zb3dnR25eA/M98ka/9+T52nrz9Tts5Lg0ZoMdcumOjjdXF+3s7Eyvv/56Xa4RdUWiEj+Lhg4dmtXZ0tLS78+sulzwzUoOPfTQ7GdnPetcVl15vsd3v/n+G4blPomv5f1lxVTL8UWL3nhvzPPnSPz8iK2ev5Msr43xGrMRGAwCLaVvqvLvtE3Z3kceeSR9+tOfTrfffnsaNuwvH8q45557ptNPPz3tvvvuy233woUL02uvvbbcMqt6Mv5aFnPTV2aLtaDmpr+06+zUmc5Ib/zivTL1eQ4BAgQIFFNgrbXWSnPmzClm8KJeJYFTTz01myWzSpVU8eT111+/ilKKECi+QNOPIL388stZYtQ7OYpuGzVqVFWJz5AhQyp/nSt3d/zlLo7Hv3psI0aMSLvttttKVTW0q/QX6Dv/Mm9+ow03SrttMrHfuiJZbGtrS1tttVW/5+tx8Mknn0yRVG6//fZVVVf+q1f8Varav0w999xzafbs2WmbbbZJ7e3tVV2n1kLxupk2bVrafPPN08iRI2t9elXlY3TzxRdfTBtuuGEaM2ZMVc+pplCMSJZfm7EoSdyDt95662X/qnl+rWU6OjrS448/nrUh2pLHFq+Thx9+OOuL6JO8tsmTJ2d/iY3XVmzl0d1aXp8riu3pp59O8+bNS295y1sq/bSi59R6/oUXXkgzZ85MW265Zap2Se1ar/Hqq6+mV155JW2yySYpfjGvZiv/Pa7a7/X449Hzzz+fNthggzR27NhqLlFzmRgxmDJlSlZ/XCevLUYqpk6dmnnV4xr9vXfGz7n4fsxze+KJJ7L7eeNnSV7bs88+myV68YfDPK8TP0vGjRuX4mdwbL3fO+vRtunTp2fvJ3GNvLf4PiyPJOZ1rWq/b/O6vnoJDKRAfu9wA9mK5VwrfoGOhGbJraurq/KmuOS53o/jDWfdddftfSj75TyODx8+vM/xlX0Q9f/mN79Zqaf3lH7odo34yy/Xhx9xeDry619dqbpWx5NiCkIkCpGEVPtL1uqIsyjXjF+aIrEbP358UUJu6DgjyYhfOMOztbW1oWMtQnCRGMYvWXn90aEIBvWKMX6uxfd6/Bxae+2161XtoK4nEtj4Y5KNAAEC9RkCaWDH+KtjJENLziuOaQiGihu444RGgAABAgQIECBAYDUINH2CNHHixGyIPqaXlbdYtCGG0vOcTlG+lq8ECBAgQIAAAQIECBRHoOkTpNGjR6e99947XXbZZdm8/7g/Jlaw23fffbO5x8XpKpESIECAAAECBAgQIJC3QNPfgxSAsYrdV7/61XTAAQdkCzb89V//dTrhhBPyth2Y+kv3WA354YWVa7W8bcfKvh0CBAgQIECAAAECBGoTGBQJUqwQdsEFF2Sr4sSN1s10g3BLaSWhln/4ZG29rjQBAgQIECBAgAABAv0KDIoEqdxyq6SVJXwlQIAAAQIECBAgQKA/gaa/B6m/RjtGgAABAgQIECBAgACB/gQkSP2pOEaAAAECBAgQIECAwKAUkCANym7XaAIECBAgQIAAAQIE+hOQIPWn4hgBAgQIECBAgAABAoNSQII0KLtdowkQIECAAAECBAgQ6E9AgtSfimMECBAgQIAAAQIECAxKAQnSoOx2jSZAgAABAgQIECBAoD8BCVJ/Ko4RIECAAAECBAgQIDAoBSRIg7LbNZoAAQIECBAgQIAAgf4EJEj9qThGgAABAgQIECBAgMCgFJAgDcpu12gCBAgQIECAAAECBPoTaOvvoGPFEejp6ko9V1xZCbhl+7eklh13qDy2Q4AAAQIECBAgQIBA9QISpOqtGrPkokWp++PHVGJr+dKpqVWCVPGwQ4AAAQIECBAgQKAWAVPsatFSlgABAgQIECBAgACBphaQIDV192ocAQIECBAgQIAAAQK1CEiQatFSlgABAgQIECBAgACBphaQIDV192ocAQIECBAgQIAAAQK1CEiQatFSlgABAgQIECBAgACBphaQIDV192ocAQIECBAgQIAAAQK1CEiQatFSlgABAgQIECBAgACBphaQIDV192ocAQIECBAgQIAAAQK1CEiQatFSlgABAgQIECBAgACBphaQIDV192ocAQIECBAgQIAAAQK1CEiQatFSlgABAgQIECBAgACBphaQIDV192ocAQIECBAgQIAAAQK1CLTVUljZNwTa2tpSa2trY3CU4mjZa49KLC1bbF7ZL8JOS0tLGjp0aApTW30EwtNWH4H29vbU09OT4nVqW3WBeN9kueqOUYP3zvo49q7Fe2dvDfsEBrdAS+mHf8/gJtB6AgQIECBAgAABAgQIvCFgip1XAgECBAgQIECAAAECBN4UkCB5KRAgQIAAAQIECBAgQOBNAQmSlwIBAgQIECBAgAABAgTeFJAgeSkQIECAAAECBAgQIEDgTQEJkpcCAQIECBAgQIAAAQIE3hSQIHkpECBAgAABAgQIECBA4E0BCZKXAgECBAgQIECAAAECBN4UkCB5KQy4wIsvvph+8pOfLHXd7u7u9NBDD6XLL7883Xzzzamjo2OpMg4QyFvgN7/5TXrggQeWeZnp06enSy+9NHV1dS2zjBME8hBY1ntnXGvKlCnp6quvzt4758+fn8fl1UmAAIFBIyBBGjRd3RgNnTdvXjrttNPSLbfc0ieg+KXzkEMOSWeffXaKXwK+973vpSOPPDLNmTOnTzkPCOQp8OCDD6avfOUr6dFHH+33MvG52uecc0667LLLJEj9CjmYl8Cy3jvjetddd136zGc+kyZPnpyuv/76dOCBB6Ynn3wyr1DUS4AAgaYXkCA1fRc3TgN///vfp49//OPppZdeWiqoa6+9Nm2wwQbZX0C/+MUvpmuuuSbNmjUre7xUYQcI1Fmgs7MzS3o+97nPpZaWlmXWHq/TZSVPy3ySEwRWUWB5752vvfZa9gelU045JZ1xxhnpBz/4Qdprr72y1/MqXtbTCRAgMGgFJEiDtusHtuFz585Nkfi8//3vT3/3d3+31MVHjBiRjjjiiMrx4cOHp6233rrfZKpSyA6BOgnceOON6X/+53+yEcwNN9yw31qfeeaZbPrnscce2+95BwnkIbCi98547U6cODG9733vq1z+xBNPTJHs2wgQIEBg5QTaVu5pnkWgNoFIeGJUaN11100/+tGPlnpy7+QoTs6cOTO7D+S4445bqqwDBOotsOuuu6b99tsvtbW1pe9///tLVb948eL01a9+NX3qU59KEyZMWOq8AwTyEljRe+ef//zntPHGG6c77rgjRbK0cOHCtOeee2av57xiUi8BAgSaXcAIUrP3cIO0L37xjOSomm3RokXpzDPPzH7oH3zwwdU8RRkCqyQQr814jS5ru/jii9P48eOzezuWVcZxAnkIrOi9c9q0adkCDRdeeGHaZptt0pgxY9I3v/nNdMUVV+QRjjoJECAwKASW/RvBoGi+RjaaQCzK8IUvfCFbnOH8889P7e3tjRaieAaZwP33359uuummbHrdIGu65hZAIFZTfOGFF7KVQddbb70s4lGjRmWv15jOPGSIv4MWoBuFSIBAgwlIkBqsQwZzOLGS3cknn5xGjhyZvvvd76bRo0cPZg5tbxCBiy66KMU9cueee24W0ezZs7Ovp59+ejrggAPSbrvt1iCRCmMwCowbNy4bOSonR2Hwrne9K8WCIjFVeezYsYORRZsJECCwSgISpFXi8+R6CUydOjWdcMIJafPNN8+m1w0bNqxeVauHwCoJfOADH0ixUlh5i1UYH3nkkWwRkXXWWad82FcCq0Vgs802S/fcc0+KJejLKzA+9dRTKUaRqp3WvFoCd1ECBAg0sIAEqYE7ZzCF9q1vfSv7XJlDDz00+yyPctvXWmuttOmmm5Yf+kpgwAXiM2V6b/fdd192M/zHPvaxNHTo0N6n7BMYcIH9998/W/jmhz/8YTr66KPTs88+m2644Ya0++67VxKmAQ/KBQkQIFBwAQlSwTuwGcKPv8jfddddWVNOOumkPk2aNGlS+td//dc+xzwgQIAAgTcEYqTovPPOS2eddVY2rS5GkmLaZ0xXthEgQIDAygm0lN5Me1buqZ5FgAABAgQINIpA3McZCZMpyo3SI+IgQKCoAhKkovacuAkQIECAAAECBAgQqLuA9T/rTqpCAgQIECBAgAABAgSKKiBBKmrPiZsAAQIECBAgQIAAgboLSJDqTqpCAgQIECBAgAABAgSKKiBBKmrPiZsAAQIECBAgQIAAgboLSJDqTqpCAgQIECBAgAABAgSKKiBBKmrPiZvAIBOYNWtWeu6559KiRYuW2fLnn38+vfLKK8s8n9eJ119/PYtt4cKFeV2isPXedNNNKfql99bR0ZHuvvvu7ANN//SnP/U+le3feuut6ZlnnlnquAMECBAgQGAgBCRIA6HsGgQIrLLAv/zLv6RNNtkk/fGPf1xmXX/1V3+VDj300GWez+tEJAER269+9au8LlHIem+//fb0iU98Io0ZM6YS/4033pg233zztPPOO6eDDjoobb/99tkHm7744ouVMk899VTWj11dXZVjdggQIECAwEAJSJAGStp1CBAgMIgEYlTtU5/6VPryl7+cfXhpNP3RRx9NH/7wh9Po0aPT9ddfn1599dX0ne98JxtN6p3YxvPmzJmTvvWtbw0iMU0lQIAAgUYRkCA1Sk+IgwABAk0k8MMf/jDNnj07HXPMMZVW/eQnP0nz589PX//619OBBx6Yxo0bl0444YT093//9+muu+5KDz/8cFa2tbU1/eM//mP653/+5yxRqlRghwABAgQIDICABGkAkF2CAIHVJ7BgwYJ04YUXpo9//OPpYx/7WPrmN7+Z4n6m3tv3vve9dPHFF/c+lO3/x3/8RzrvvPMqxydPnpzOOOOMNG3atHTWWWelo48+Ot1yyy2V87ETIx9R5uc//3mf4/Hg5Zdfzs7dc889S52LAxdccEH6t3/7tz7nnn766ew5//u//9vneNync+aZZ6byNLSIKUZcPvnJT6a//du/Taeeemr67W9/2+c55Qe/+93v0pe+9KX00Y9+NH3/+9/P7uuKmON47y0SlhgBivo+97nPpV/+8pe9Ty9zv7OzM337299OBx98cBo2bFil3OOPP57tv/Od76wci53ok7jWVlttVTn+oQ99KEum+uuXSiE7BAgQIEAgD4EeGwECBAogUPqFv6f0HthTSi6WGe3QoUN73vWud1XOl+5r6SndG9QTx9/3vvf17L///j0jR47smTBhQs+9995bKfeWt7ylZ9KkSZXH5Z299tqrZ6ONNio/7CklPVkMpelg2dchQ4b0/MM//EPPtddemz0u3YuUlS3dV9Oz4YYb9nR3d1eeGztnn312T0tLS0/pHps+x8sPSglcz/Dhw3tKSV35UPacaPe+++5bORY7u+66ayXmUmLTUxqN6VlzzTWzdoZBaRQmu9a///u/93le6V6uLNa3vvWtPaUkpGf8+PE973nPe7Jj55xzTqVsaQQocwu7Aw44oOdtb3tbVuaf/umfKmWWtfN///d/fTzK5eK50ZZf/OIX5UPL/brnnnv27Ljjjsst4yQBAgQIEKi3QFseSZc6CRAgkJfAcccdV7mnZclrLF68uM+hGOGZOnVqNpJSHrV44okn0rvf/e505JFHpgceeCC1tdX+NlhKANIjjzyS1l9//Wz0ZcmRl1iYIEZcfv3rX6f3vve9lZhiRGq33XZLm222WeVY751YtOA///M/s3hLCV126rbbbkulJCU7Fu1rb29PM2bMyKakxRS02L74xS+mWEFvypQpab311suOvfDCC2nTTTdNMTp21FFHZcdiEYkoG9PaYoSnlKyl6dOnpz322CM7X/4v6jnxxBNTKQlL11xzTRo7dmx26vTTT8+mvZWStVRKXsrFl/panir3N3/zN5VzTz75ZHbvURwoJUiV/Rg1KiVplXK9d97xjndko2oxShbT7mwECBAgQGAgBIYMxEVcgwABAvUSeO2117Jf6uMX+yX/9b5GJAg333xzNuWsnBzF+S233DKbfhbLS0cCszJbTGPbdttts9XZyglJ73pi6lokMpHslLeYVhdT9CIxW9a2zz77ZMlQedpeLHRwxx13ZM+Je3f+8Ic/ZE+NVfNKo1PZFLbSX82ypCeSjt6xTJw4MZVGxbLpgOXr/fSnP02lEaosyYnkKLZIfmK6YO+tPO3utNNOqyRHcT7uC4p2RdK1vC2Sx7hOObGKst/4xjey6XqxH9MII0mNf+W2xvElt9IoXJb4xTRDGwECBAgQGCiB2v90OlCRuQ4BAgT6Efiv//qv1HtkoneR3ve7PPbYY9mp3slRuWwkDrFFwrK8kZBy+SW/RpK1vC1GRD7wgQ+k0tS79N3vfjetscYaKUaPStP7lrsM+ahRo9Luu++e4v6i2CKBi899ikTl8ssvz+4BilGd//7v/05bb7119i/KRWIViWMkQLFSXNzrE6Njsd87abrvvvuyJbbjOr230vS53g+z50cCFYnMJZdc0ufciBEjUozCLW+LBCkStN7b+eefn0pTDLNY43ORyv2z1lpr9S7WZ780vTF7HPXFEu42AgQIECAwEAJGkAZC2TUIEBhwgZiGFlt/v4CX7tXJzi05JS872Ou/8gIIvQ5lu+uuu+6Sh5Z6HNPsYhW3SGbiOldddVWKhQfK117qCW8eiNXdYoraSy+9lCVK2223XTZVbpdddskSpFgAIUZdYjpeefvxj3+cYrQlFlO49NJLU4w8xaIUb3/728tFsq+xkENM11tyi9Ge3luMzEWyGdMPS/dZ9fkX0+t22mmn3sWX2o8P641EqvcW7Y5V66LO8Iv9+Nc7qe1dPvbLdayOD/9dMhaPCRAgQGDwCBhBGjx9raUEBpVAfBhpbM8++2z2tfd/5WM77LBDdjjub+kvWYqRjpXd9ttvv+zemriHJ0ZsIumIpGVFWyRIcZ9VjCLFynXlEa7SghHpa1/7Wop7kmIVvlghLra4xyruMYq2xAhSedQlzsWoVUzBK29bbLFFKi1OkR0rT7GLc0tOYYt7pGI6X1xvydGySNBWdN9WjFo9+OCDS11n5syZKUaxon3VbOWRqmXdo1RNHcoQIECAAIFaBYwg1SqmPAEChRDYZpttsnuEfvSjH/VJEiL4GGWJrZwgrb322um5557LRl6yE6X/ImmIYyu7RRIRy4rH/UKRJG288cbZ9LkV1RdT02LKW0wljPukIjGKLb52dHRk9xvF4hDlaYIxlS6Slg9+8IN9kqNYFCESjDhX3g455JAsUYvRrN5bLIPee4tpfLFFgtV7++Mf/5iNgJ100km9Dy+1H22Ie6biPrDeW0yzK60guNQ9T73L9N6PKZCxxeiYjQABAgQIDJSABGmgpF2HAIEBFYgpXfGBpPfff3+KxCA+iDRGL0rLcqfrr78+ux8mEqPY4h6emJJ3+OGHZ6M2kVTFsTFjxqxSzDHNbt68edn9Q0cccUS2alw1FcYoUowUxchWaQnu7CkxXS7ijZGZOF8eAYopeLFwQmk57ywZi6QuEqBIqGJ63Ny5cysJYsQT9RxZWiji85//fHZ/UdjEyFNs5TrDKBLM+FymWO0u7gGKhO2www7LEqRYzW55W3nUq5zgRNnSEuJZf8Q1IgGM+8jiA2Ljc6bi/qqIbclFM+JequiD0lLfy7uccwQIECBAoK4CptjVlVNlBAg0ksBnPvOZbDW1+NDUuIcntpgyFr+Uf/azn62EGiMiMdoS9/Jcd9112ZS4SALig13j8cpupc9XyhKBmNZWzfS68nXi/qIzzzwze275HqpIlmIBh5/97GeV6XVRPkZXrrjiiiyRKX3OU7a6XUxJi+Qw7qE69thjsw+AjeXFY1QrkpBTTjklqyemvMVKcrGYRCwqEYtIxBYJV5SLqXClzy6qjELFQglXXnlldu9QVnAZ/0UckQg99NBDqbxceXlVu/e///3ZggtxP9Ttt9+eJXMxDTDaFysDlhPCWKUvRqxiquKKpvQtIwyHCRAgQIDASgm0xAcrrdQzPYkAAQIFEvjzn/+c/RK+wQYbLDPqWNwg7juKRCB+Ya/HtvPOO2cLIyw5OlKPupesI+5HinupllxBrlwuFjuIJGjJVezic53is5Ai+YlRot5brKIXn4s0evToFHblUabeZfrbjxGzO++8M1sRLyxjyl2MaPW3IESYxxTE3otfRGJa+kDe7J4pI0j9CTtGgAABAnkJSJDyklUvAQKDXiA+QDZGbuLzkOKzkVb3Fp9FFKNp8dlK5RG1iGnvvffORnNiel697vd58cUXU3wIbEz9+8hHPlJz0+Meq+23336pZcZrrsgTCBAgQIBAjQISpBrBFCdAgMCKBC6++OJsul7c8xTTxuL+p0aYJhYJUNyDFNPXIimK1eZ++ctfZvcYxWceHXPMMStqWk3n4wNoY0pg3AdWyxYjWjHNMBaa6P05TrXUoSwBAgQIEFhZAYs0rKyc5xEgQGAZArHUdkzXiyliN9xwQ0MkRxFqTGOL+3piJCnuT4qlvGNBhZtvvrnuyVFcL+5fivuZ7rnnnnhY9Rar/sUS45KjqskUJECAAIE6ChhBqiOmqggQIECAAAECBAgQKLaAEaRi95/oCRAgQIAAAQIECBCoo4AEqY6YqiJAgAABAgQIECBAoNgCEqRi95/oCRAgQIAAAQIECBCoo4AEqY6YqiJAgAABAgQIECBAoNgCEqRi95/oCRAgQIAAAQIECBCoo4AEqY6YqiJAgAABAgQIECBAoNgCEqRi95/oCRAgQIAAAQIECBCoo4AEqY6YqiJAgAABAgQIECBAoNgC/x+qWhmbeUEQHgAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ggplot(data = OD2526_expanded, aes(x = hourly_wage)) +\n",
    "  geom_histogram(binwidth = 0.3, fill = 'cornflowerblue', colour = 'black') +\n",
    "  labs(title = \"Hourly wage distribution for 2025-26 training year\", x = \"Hourly wage (£)\", y = \"Frequency\") +\n",
    "  geom_vline(aes(xintercept = UK_minimum_hourly_wage, color = \"Minimum Wage\"), \n",
    "             linetype = \"dashed\", lwd = 1) +\n",
    "  scale_color_manual(name = \"Legend\", values = c(\"Minimum Wage\" = \"red\")) +\n",
    "  theme_minimal()\n",
    "\n",
    "ggplot(data = OD2425_expanded, aes(x = hourly_wage)) +\n",
    "  geom_histogram(binwidth = 0.3, fill = 'cornflowerblue', colour = 'black') +\n",
    "  labs(title = \"Hourly wage distribution for 2024-25 training year\", x = \"Hourly wage (£)\", y = \"Frequency\") +\n",
    "  geom_vline(aes(xintercept = 10.18, color = \"Minimum Wage\"), \n",
    "             linetype = \"dashed\", lwd = 1) +\n",
    "  scale_color_manual(name = \"Legend\", values = c(\"Minimum Wage\" = \"red\")) +\n",
    "  theme_minimal()\n",
    "\n",
    "\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Region'</li><li>'SubRegion'</li><li>'Sector'</li><li>'ProgramPreference'</li><li>'ProgramTitle'</li><li>'ProgramDescription'</li><li>'AvailableSlots'</li><li>'EmployerType'</li><li>'EmployerName'</li><li>'OrgSizePrimaryCareOnly'</li><li>'HospitalSpecialties'</li><li>'SkilledWorkerVisa'</li><li>'LicenseCount'</li><li>'Salary'</li><li>'TrainingProvider'</li><li>'WeeklyHours'</li><li>'ICBName'</li><li>'PlacementRotationCount'</li><li>'RotationSetting1'</li><li>'RotationSetting2'</li><li>'RotationSetting3'</li><li>'RotationSetting4'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Region'\n",
       "\\item 'SubRegion'\n",
       "\\item 'Sector'\n",
       "\\item 'ProgramPreference'\n",
       "\\item 'ProgramTitle'\n",
       "\\item 'ProgramDescription'\n",
       "\\item 'AvailableSlots'\n",
       "\\item 'EmployerType'\n",
       "\\item 'EmployerName'\n",
       "\\item 'OrgSizePrimaryCareOnly'\n",
       "\\item 'HospitalSpecialties'\n",
       "\\item 'SkilledWorkerVisa'\n",
       "\\item 'LicenseCount'\n",
       "\\item 'Salary'\n",
       "\\item 'TrainingProvider'\n",
       "\\item 'WeeklyHours'\n",
       "\\item 'ICBName'\n",
       "\\item 'PlacementRotationCount'\n",
       "\\item 'RotationSetting1'\n",
       "\\item 'RotationSetting2'\n",
       "\\item 'RotationSetting3'\n",
       "\\item 'RotationSetting4'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Region'\n",
       "2. 'SubRegion'\n",
       "3. 'Sector'\n",
       "4. 'ProgramPreference'\n",
       "5. 'ProgramTitle'\n",
       "6. 'ProgramDescription'\n",
       "7. 'AvailableSlots'\n",
       "8. 'EmployerType'\n",
       "9. 'EmployerName'\n",
       "10. 'OrgSizePrimaryCareOnly'\n",
       "11. 'HospitalSpecialties'\n",
       "12. 'SkilledWorkerVisa'\n",
       "13. 'LicenseCount'\n",
       "14. 'Salary'\n",
       "15. 'TrainingProvider'\n",
       "16. 'WeeklyHours'\n",
       "17. 'ICBName'\n",
       "18. 'PlacementRotationCount'\n",
       "19. 'RotationSetting1'\n",
       "20. 'RotationSetting2'\n",
       "21. 'RotationSetting3'\n",
       "22. 'RotationSetting4'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Region\"                 \"SubRegion\"              \"Sector\"                \n",
       " [4] \"ProgramPreference\"      \"ProgramTitle\"           \"ProgramDescription\"    \n",
       " [7] \"AvailableSlots\"         \"EmployerType\"           \"EmployerName\"          \n",
       "[10] \"OrgSizePrimaryCareOnly\" \"HospitalSpecialties\"    \"SkilledWorkerVisa\"     \n",
       "[13] \"LicenseCount\"           \"Salary\"                 \"TrainingProvider\"      \n",
       "[16] \"WeeklyHours\"            \"ICBName\"                \"PlacementRotationCount\"\n",
       "[19] \"RotationSetting1\"       \"RotationSetting2\"       \"RotationSetting3\"      \n",
       "[22] \"RotationSetting4\"      "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "colnames(OD2526_modified)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Current.Assigned.Rank'</li><li>'Preference'</li><li>'Employer.Name'</li><li>'Programme.Title'</li><li>'Programme.Description'</li><li>'Region'</li><li>'Area.Sector.'</li><li>'Employer.Type'</li><li>'Size.of.Organisation'</li><li>'Specialties'</li><li>'Skilled.worker.visa'</li><li>'No.of.Licences'</li><li>'Number.of.Placements'</li><li>'Places.Available'</li><li>'Salary'</li><li>'Training.Provider'</li><li>'Employer.Website'</li><li>'Hours.Per.Week'</li><li>'Setting.1'</li><li>'Length.1'</li><li>'Setting.2'</li><li>'Length.2'</li><li>'Setting.3'</li><li>'Length.3'</li><li>'Setting.4'</li><li>'Length.4'</li><li>'Programme.Name'</li><li>'Programme.Number'</li><li>'Tags'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Current.Assigned.Rank'\n",
       "\\item 'Preference'\n",
       "\\item 'Employer.Name'\n",
       "\\item 'Programme.Title'\n",
       "\\item 'Programme.Description'\n",
       "\\item 'Region'\n",
       "\\item 'Area.Sector.'\n",
       "\\item 'Employer.Type'\n",
       "\\item 'Size.of.Organisation'\n",
       "\\item 'Specialties'\n",
       "\\item 'Skilled.worker.visa'\n",
       "\\item 'No.of.Licences'\n",
       "\\item 'Number.of.Placements'\n",
       "\\item 'Places.Available'\n",
       "\\item 'Salary'\n",
       "\\item 'Training.Provider'\n",
       "\\item 'Employer.Website'\n",
       "\\item 'Hours.Per.Week'\n",
       "\\item 'Setting.1'\n",
       "\\item 'Length.1'\n",
       "\\item 'Setting.2'\n",
       "\\item 'Length.2'\n",
       "\\item 'Setting.3'\n",
       "\\item 'Length.3'\n",
       "\\item 'Setting.4'\n",
       "\\item 'Length.4'\n",
       "\\item 'Programme.Name'\n",
       "\\item 'Programme.Number'\n",
       "\\item 'Tags'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Current.Assigned.Rank'\n",
       "2. 'Preference'\n",
       "3. 'Employer.Name'\n",
       "4. 'Programme.Title'\n",
       "5. 'Programme.Description'\n",
       "6. 'Region'\n",
       "7. 'Area.Sector.'\n",
       "8. 'Employer.Type'\n",
       "9. 'Size.of.Organisation'\n",
       "10. 'Specialties'\n",
       "11. 'Skilled.worker.visa'\n",
       "12. 'No.of.Licences'\n",
       "13. 'Number.of.Placements'\n",
       "14. 'Places.Available'\n",
       "15. 'Salary'\n",
       "16. 'Training.Provider'\n",
       "17. 'Employer.Website'\n",
       "18. 'Hours.Per.Week'\n",
       "19. 'Setting.1'\n",
       "20. 'Length.1'\n",
       "21. 'Setting.2'\n",
       "22. 'Length.2'\n",
       "23. 'Setting.3'\n",
       "24. 'Length.3'\n",
       "25. 'Setting.4'\n",
       "26. 'Length.4'\n",
       "27. 'Programme.Name'\n",
       "28. 'Programme.Number'\n",
       "29. 'Tags'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Current.Assigned.Rank\" \"Preference\"            \"Employer.Name\"        \n",
       " [4] \"Programme.Title\"       \"Programme.Description\" \"Region\"               \n",
       " [7] \"Area.Sector.\"          \"Employer.Type\"         \"Size.of.Organisation\" \n",
       "[10] \"Specialties\"           \"Skilled.worker.visa\"   \"No.of.Licences\"       \n",
       "[13] \"Number.of.Placements\"  \"Places.Available\"      \"Salary\"               \n",
       "[16] \"Training.Provider\"     \"Employer.Website\"      \"Hours.Per.Week\"       \n",
       "[19] \"Setting.1\"             \"Length.1\"              \"Setting.2\"            \n",
       "[22] \"Length.2\"              \"Setting.3\"             \"Length.3\"             \n",
       "[25] \"Setting.4\"             \"Length.4\"              \"Programme.Name\"       \n",
       "[28] \"Programme.Number\"      \"Tags\"                 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>'Primary Care'</li><li>'Hospital'</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Primary Care'\n",
       "\\item 'Hospital'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Primary Care'\n",
       "2. 'Hospital'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] \"Primary Care\" \"Hospital\"    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "colnames(OD2324)\n",
    "OD2324_modified <- OD2324 %>%\n",
    "    uncount(Places.Available) %>%\n",
    "    mutate(hourly_wage = round(Salary/52/Hours.Per.Week,digits = 2))\n",
    "\n",
    "OD2324_hourly_distribution <- ggplot(data = OD2324_modified, aes(x = hourly_wage)) +\n",
    "  geom_histogram(binwidth = 0.3, fill = 'cornflowerblue', colour = 'black') +\n",
    "  labs(title = \"Hourly wage distribution for 2023-24 training year\", x = \"Hourly wage (£)\", y = \"Frequency\") +\n",
    "  geom_vline(aes(xintercept = 9.3, color = \"Minimum Wage\"), \n",
    "             linetype = \"dashed\", lwd = 1) +\n",
    "  scale_color_manual(name = \"Legend\", values = c(\"Minimum Wage\" = \"red\")) +\n",
    "  theme_minimal()\n",
    "OD2324_hourly_distribution\n",
    "\n",
    "unique(OD2324_modified$Employer.Type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "OD2324_modified <- filter(OD2324_modified, Employer.Type == \"Primary Care\")\n",
    "plot_primary_care <- ggplot(data = OD2324_modified, aes(x = hourly_wage)) +\n",
    "  geom_histogram(binwidth = 0.3, fill = 'cornflowerblue', colour = 'black') +\n",
    "  labs(title = \"Hourly wage distribution for 2023-24 training year in Primary Care\", x = \"Hourly wage (£)\", y = \"Frequency\") +\n",
    "  geom_vline(aes(xintercept = 9.3, color = \"Minimum Wage\"), \n",
    "             linetype = \"dashed\", lwd = 1) +\n",
    "  scale_color_manual(name = \"Legend\", values = c(\"Minimum Wage\" = \"red\")) +\n",
    "  theme_minimal()\n",
    "\n",
    "  plot_primary_care\n",
    "\n",
    "  "
   ]
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      "Installing packages into ‘/opt/homebrew/lib/R/4.4/site-library’\n",
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      "\n",
      "also installing the dependencies ‘pkgcache’, ‘pkgdepends’\n",
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