text: 
  # IMPORTING NEEDED PYTHON PACKAGES
  from PIL import Image, ImageDraw, ImageFont
  import matplotlib.pyplot as plt
  import matplotlib.image as mpimg
  import csv
  import time
  
  
  #*****************************SETUP******************************
  
  images = ["southcamp.jpg","northcamp.png","ridge.png","lifecenter.png","bbhville.png","therest.png"]
  
  #*********************************PREVIEW
  for i in images:
      plt.figure(figsize=(16, 16))
      #select_location = input("Please enter site: ") #include .jpg
      #print (i)
      if i in images:
          index = images.index(i)
      location = mpimg.imread(images[index])
      #imgplot = plt.imshow(location)
  #print(imgplot)
  #***************************************
  
  df = pd.read_excel('METADATA.xlsx')
  
  overlay_drawing = []
  loc_image = []
  
  risk_high = []
  risk_med = []
  risk_low = []
  
  loc_risk =[]
  out = []
  
  data = []
  
  # SETTING COLOR AND TRANSPARENCY
  colorGrn = (0, 255, 0) 
  colorYel = (255, 255, 0) 
  colorOng = (255, 144, 0)
  colorRed = (255, 0, 0)
  colorBlank = (0,0,0)
  
  # HOW TRANSPARENT; 1 MEANING FULLY, 0 MEANING NO TRANSPARENCY
  degree_transparency_grn = .3
  degree_transparency_yel = .5 
  degree_transparency_ong = .5
  degree_transparency_red = .7
  degree_transparency_blank = .0
  
  opacity_grn = int(255 * degree_transparency_grn) # DETERMINING DEGREE OF TRANSPARENCY MASK
  colorGrn = colorGrn + (opacity_grn,)
  opacity_yel = int(255 * degree_transparency_yel) # DETERMINING DEGREE OF TRANSPARENCY MASK
  colorYel = colorYel + (opacity_yel,) # ADDING ALPHA CHANNEL TO SELECTED COLOR
  opacity_ong = int(255 * degree_transparency_yel) # DETERMINING DEGREE OF TRANSPARENCY MASK
  colorOng = colorOng + (opacity_ong,) # ADDING ALPHA CHANNEL TO SELECTED COLOR
  opacity_red = int(255 * degree_transparency_red) # DETERMINING DEGREE OF TRANSPARENCY MASK
  colorRed = colorRed + (opacity_red,)
  opacity_blank = int(255 * degree_transparency_blank) # DETERMINING DEGREE OF TRANSPARENCY MASK
  colorBlank = colorBlank + (opacity_blank,)
  
  # LABELING COORDINATES OF WHERE BUILDINGS ARE LOCATED
  sc_coords = {"Hamilton":(700,1000, 800,1100),"Berman":(980,1130,1080,1230),
                 "Eichenauer":(1080, 1150, 1180, 1250), "Birch":(980,870,1080,970),
                 "Willow":(980,850,1080,950),"Smith":(1070,800,1170,900),
                 "Benson":(1120,870,1220,970),"Forman":(1280, 950, 1380, 1050),
                 "Oak":(1700,1150,1800,1250),"Mulberry":(1790,1220,1890,1320),
              "Sunset North":(1250,0,1400,150),"Sunset South":(1250,0,1400,150),
              "Otis Armstrong":(670,500,770,600),"Four Seasons":(120,830,220,930), 
               "Pine":(1680,1130,1780,1230)}
  
  nc_coords = {"Thyme":(870,220,970,320),"Parsley":(860,270,960,370),
               "Rosemary ":(920,250,1020,350), "Sage":(900,300,1000,400),
              "Rapp R":(1980,750,2080,850), "Rapp West":(1950,890,2050,990)}
  
  ri_coords = {"Ashwood":(300,130,400,230), "Acorn":(400,400,500,500), 
               "Aspen":(220,350,320,450) ,"Balsam ":(280,220,380,320), 
               "Beechnut":(380,330,480,430), "Briarwood":(150,350,250,450), 
               "Cedar":(220,170,320,270), "Chestnut":(300,400,400,500), 
               "Cypress":(220,280,320,380)}
  
  lc_coords = {"Elm":(360,670,460,770),"Evergreen":(250,640,350,740),
               "Redwood":(410,800,510,900),"Spruce":(260,580,360,680),
               "Tulip":(320,760,420,860)}
  
  bh_coords = {"Granite":(520,190,620,290), "Slate":(440,260,540,360), 
               "Stonewall":(110,150,210,250)}
  
  tr_coords = {"Vista":(330,290,430,390),"Wawanda":(1180,450,1280,550)}
  
  ##FOR LOOP TO ITERATE THROUGH EXCEL DATA***************************************************
  for index, row in df.iterrows():
  
  # 
      house = str(row['LOCATION'])
      pos_sta = float(row['ACTIVE'])
      pos_res = float(row['RES, POS, ACTIVE'])
      pend_res = float(row['RES, PEND, ACTIVE'])
      pend_sta = float(row['staff tested, pending'])
      staff_sym = float(row['ACTIVE S&S']) 
      
  
  #HIGH RISK
      if pos_sta > 0:
          risk_high.append(str(house))
      elif pos_res > 0:
          risk_high.append(str(house))
          
  #MEDIUM RISK
      if pend_res > 0:
          risk_med.append(str(house))
          
  #LOW RISK
      if pend_sta > 0:
          risk_low.append(str(house))
  
  
  #******************************************************************************END
  
  for i in images:
      #print("The picture is {}".format(i[0:len(i)-4]))
      index = images.index(i)
      loc_image = Image.open(images[index]).convert("RGBA")
      if i == "southcamp.jpg":
          coords = sc_coords
      elif i == "northcamp.png":
          coords = nc_coords
      elif i == "ridge.png":
          coords = ri_coords
      elif i == "lifecenter.png":
          coords = lc_coords
      elif i == "bbhville.png":
          coords = bh_coords
      elif i == "therest.png":
          coords = tr_coords
  
      overlay = Image.new("RGBA", loc_image.size)
      overlay_drawing = ImageDraw.Draw(overlay)
  #     loc_risk = Image.alpha_composite(loc_image, overlay)
  
      for key, value in coords.items():
          if key in risk_high:
              data = [str(key)]
              overlay_drawing.ellipse(coords[key], fill=colorRed)
              loc_risk = Image.alpha_composite(loc_image, overlay)
          elif key in risk_med: 
              overlay_drawing.ellipse(coords[key], fill=colorOng)
              loc_risk = Image.alpha_composite(loc_image, overlay)
          elif key in risk_low:
              overlay_drawing.ellipse(coords[key], fill=colorYel)
              loc_risk = Image.alpha_composite(loc_image, overlay)
              
      loc_risk.save('{}_risk.png'.format(i[0:len(i)-4]))
      loc_risk.show() 
  # print(data)
  
  
  
  
  
  
  
  
  
  