Hurricane analysis challenge - Python (Codecademy)

.py

names = ['Cuba I', 'San Felipe II Okeechobee', 'Bahamas', 'Cuba II', 'CubaBrownsville', 'Tampico', 'Labor Day', 'New England', 'Carol', 'Janet', 'Carla', 'Hattie', 'Beulah', 'Camille', 'Edith', 'Anita', 'David', 'Allen', 'Gilbert', 'Hugo', 'Andrew', 'Mitch', 'Isabel', 'Ivan', 'Emily', 'Katrina', 'Rita', 'Wilma', 'Dean', 'Felix', 'Matthew', 'Irma', 'Maria', 'Michael']
months = ['October', 'September', 'September', 'November', 'August', 'September', 'September', 'September', 'September', 'September', 'September', 'October', 'September', 'August', 'September', 'September', 'August', 'August', 'September', 'September', 'August', 'October', 'September', 'September', 'July', 'August', 'September', 'October', 'August', 'September', 'October', 'September', 'September', 'October']
years = [1924, 1928, 1932, 1932, 1933, 1933, 1935, 1938, 1953, 1955, 1961, 1961, 1967, 1969, 1971, 1977, 1979, 1980, 1988, 1989, 1992, 1998, 2003, 2004, 2005, 2005, 2005, 2005, 2007, 2007, 2016, 2017, 2017, 2018]
max_sustained_winds = [165, 160, 160, 175, 160, 160, 185, 160, 160, 175, 175, 160, 160, 175, 160, 175, 175, 190, 185, 160, 175, 180, 165, 165, 160, 175, 180, 185, 175, 175, 165, 180, 175, 160]
areas_affected = [['Central America', 'Mexico', 'Cuba', 'Florida', 'The Bahamas'], ['Lesser Antilles', 'The Bahamas', 'United States East Coast', 'Atlantic Canada'], ['The Bahamas', 'Northeastern United States'], ['Lesser Antilles', 'Jamaica', 'Cayman Islands', 'Cuba', 'The Bahamas', 'Bermuda'], ['The Bahamas', 'Cuba', 'Florida', 'Texas', 'Tamaulipas'], ['Jamaica', 'Yucatn Peninsula'], ['The Bahamas', 'Florida', 'Georgia', 'The Carolinas', 'Virginia'], ['Southeastern United States', 'Northeastern United States', 'Southwestern Quebec'], ['Bermuda', 'New England', 'Atlantic Canada'], ['Lesser Antilles', 'Central America'], ['Texas', 'Louisiana', 'Midwestern United States'], ['Central America'], ['The Caribbean', 'Mexico', 'Texas'], ['Cuba', 'United States Gulf Coast'], ['The Caribbean', 'Central America', 'Mexico', 'United States Gulf Coast'], ['Mexico'], ['The Caribbean', 'United States East coast'], ['The Caribbean', 'Yucatn Peninsula', 'Mexico', 'South Texas'], ['Jamaica', 'Venezuela', 'Central America', 'Hispaniola', 'Mexico'], ['The Caribbean', 'United States East Coast'], ['The Bahamas', 'Florida', 'United States Gulf Coast'], ['Central America', 'Yucatn Peninsula', 'South Florida'], ['Greater Antilles', 'Bahamas', 'Eastern United States', 'Ontario'], ['The Caribbean', 'Venezuela', 'United States Gulf Coast'], ['Windward Islands', 'Jamaica', 'Mexico', 'Texas'], ['Bahamas', 'United States Gulf Coast'], ['Cuba', 'United States Gulf Coast'], ['Greater Antilles', 'Central America', 'Florida'], ['The Caribbean', 'Central America'], ['Nicaragua', 'Honduras'], ['Antilles', 'Venezuela', 'Colombia', 'United States East Coast', 'Atlantic Canada'], ['Cape Verde', 'The Caribbean', 'British Virgin Islands', 'U.S. Virgin Islands', 'Cuba', 'Florida'], ['Lesser Antilles', 'Virgin Islands', 'Puerto Rico', 'Dominican Republic', 'Turks and Caicos Islands'], ['Central America', 'United States Gulf Coast (especially Florida Panhandle)']]
damages = ['Damages not recorded', '100M', 'Damages not recorded', '40M', '27.9M', '5M', 'Damages not recorded', '306M', '2M', '65.8M', '326M', '60.3M', '208M', '1.42B', '25.4M', 'Damages not recorded', '1.54B', '1.24B', '7.1B', '10B', '26.5B', '6.2B', '5.37B', '23.3B', '1.01B', '125B', '12B', '29.4B', '1.76B', '720M', '15.1B', '64.8B', '91.6B', '25.1B']
deaths = [90,4000,16,3103,179,184,408,682,5,1023,43,319,688,259,37,11,2068,269,318,107,65,19325,51,124,17,1836,125,87,45,133,603,138,3057,74]

#2 - Update recorded damages
updated_damages = []
for damage in damages:
  if damage[-1] == "M":
    y = float(damage[:-1])*1000000
  elif damage[-1] == "B":
    y = float(damage[:-1])*1000000000
  else:
    y = damage
  updated_damages.append(y)
#print(updated_damages)
  
#3 - Dictionary of hurricanes
hurricanes = {}
count = 0
for name in names:
  hurricanes[name] = {"Name":name,
                      "Month":months[count],
                      "Year":years[count], 
                      "Max Sustained Wind":max_sustained_winds[count], 
                      "Areas Affected":areas_affected[count], 
                      "Damage":updated_damages[count], 
                      "Deaths":deaths[count]}
  count = count + 1
#print(hurricanes)

#4 - dictionary of hurricanes by year
hurricanes_date = {}
for key,values in hurricanes.items():
  if values["Year"] not in hurricanes_date:
    hurricanes_date[values["Year"]] = []
    hurricanes_date[values["Year"]].append(hurricanes[key])
  elif values["Year"] in hurricanes_date:
    hurricanes_date[values["Year"]].append(hurricanes[key])

#for x in hurricanes_date.items():
#  print("\n",x)

#5 - count of areas affected
areas_affected = {}
for y in hurricanes.keys():
  araf = hurricanes[y]["Areas Affected"]
  for area in araf:
    if area not in areas_affected:
      areas_affected[area] = 1
    elif area in areas_affected:
      areas_affected[area] += 1

#print("\nAreas affected:\n",sorted(areas_affected.items()))

#6.1 - Most affected area
for key, value in areas_affected.items():
  if areas_affected[key] == sorted(areas_affected.values())[-1]:
#    print("\nMost hurricanes:\n"+key,":",value)

#6.2 - Most affected area
nam = []
valdic = 0
for key, value in areas_affected.items():
  if value > valdic:
    valdic = value
    nam = key 
#print("\nMost hurricanes:\n"+nam,":",valdic)

#7 - Most letal hurricane
nam = []
death_dic = 0
for key, values in hurricanes.items():
  if values["Deaths"] > death_dic:
      death_dic = values["Deaths"]
      nam = values["Name"]
#print("\nDeadliest hurricane:\n"+nam,":",death_dic)

#8 - Hurricanes by mortality
for key,values in list(hurricanes.items()):
  nk = values["Deaths"]
  hurricanes[nk] = hurricanes[key]
  del hurricanes[key]

hurricanes_scale = {0:[],1:[],2:[],3:[],4:[],5:[]}
for key in hurricanes:
  if key == 0:
    hurricanes_scale[0].append(hurricanes[key])
  elif key <= 100:
    hurricanes_scale[1].append(hurricanes[key])
  elif key <= 500:
    hurricanes_scale[2].append(hurricanes[key])
  elif key <= 1000:
    hurricanes_scale[3].append(hurricanes[key])
  elif key <= 10000:
    hurricanes_scale[4].append(hurricanes[key])
  else:
    hurricanes_scale[5].append(hurricanes[key])
for key,values in hurricanes_scale.items():
#  print("Categoría {} : {}\n".format(key,values))

damages = {}
for key, value in hurricanes.items():
  nom = value["Name"]
  dam = value["Damage"]
  if nom not in damages and dam != "Damages not recorded":
      damages[nom] = dam

#9 - Most damage caused by hurricane
for k,v in sorted(damages.items(), key=lambda item: item[1]):
  print(k+":",v)
  
#10 - Hurricanes by damages caused
hurricanes_damage = {0:[],1:[],2:[],3:[],4:[],5:[],"Damages not recorded":[]}
for key,values in hurricanes.items():
  if values["Damage"] == "Damages not recorded":
    hurricanes_damage["Damages not recorded"].append(hurricanes[key])
  elif values["Damage"] == 0:
    hurricanes_damage[0].append(hurricanes[key])
  elif values["Damage"] <= 100000000:
    hurricanes_damage[1].append(hurricanes[key])
  elif values["Damage"] <= 1000000000:
    hurricanes_damage[2].append(hurricanes[key])
  elif values["Damage"] <= 10000000000:
    hurricanes_damage[3].append(hurricanes[key])
  elif values["Damage"] <= 50000000000:
    hurricanes_damage[4].append(hurricanes[key])
  elif values["Damage"] > 50000000000:
    hurricanes_damage[5].append(hurricanes[key])

for k,v in hurricanes_damage.items():
  print(k,":",v,"\n")