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script.py

# names of hurricanes
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 of hurricanes
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 of hurricanes
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]

# maximum sustained winds (mph) of hurricanes
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 by each hurricane
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 (USD($)) of hurricanes
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 for each hurricane
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]

# write your update damages function here:
def updated_damages(list_of_damages):
  new_damages = []
  for cost in list_of_damages:
    if cost == 'Damages not recorded':
      new_damages.append('Damages not recorded')
    else:
      if cost[-1] == "B":
        new_damages.append(float(cost[0:-1])*1000000000)
      elif cost[-1] == "M":
        new_damages.append(float(cost[0:-1])*1000000)
  return new_damages

damages = updated_damages(damages)
# write your construct hurricane dictionary function here:
def hurricane_dictionary(names, months, years, max_sustained_winds, areas_affected, damages, deaths):
  big_dictionary = {}
  index = 0
  for name in names:
    big_dictionary[name] = {'Name': names[index], 'Month': months[index], 'Year': years[index], 'Max Sustained Wind': max_sustained_winds[index], 'Areas Affected': areas_affected[index], 'Damage': damages[index], 'Deaths': deaths[index]}
    index += 1
  return big_dictionary

hurricanes = hurricane_dictionary(names, months, years, max_sustained_winds, areas_affected, damages, deaths)
# write your construct hurricane by year dictionary function here:
def hurricane_years(hurricanes, years=years):
  hurricane_facts = []
  for info in hurricanes.values():
    hurricane_facts.append(info)
  hurricane_years = {}
  index = 0
  for year in years:
    multiple_hurricanes = []
    if year in hurricane_years.keys():
      multiple_hurricanes.append(hurricane_years[year])
      multiple_hurricanes.append(hurricane_facts[index])
      hurricane_years[year] = multiple_hurricanes
      index += 1
    else: 
      hurricane_years[year] = hurricane_facts[index]
      index += 1  
  return hurricane_years

hurricane_years = (hurricane_years(hurricanes))
#print(hurricane_years)
#Kind of works look at 2005


# write your count affected areas function here:
def hurricane_area_frequency(hurricanes):
  area_frequency = {}
  for hurricane in hurricanes.values():
    for areas in hurricane['Areas Affected']:
      if areas in area_frequency.keys():
        area_frequency[areas] = int(area_frequency[areas]) + 1
      else: 
        area_frequency[areas] = 1
  return area_frequency

affected_areas = (hurricane_area_frequency(hurricanes))

# write your find most affected area function here:
def most_affected(areas_affected):
  num = (int(len(areas_affected.keys())))
  count = 1
  dict_1 = {}
  dict_1["Max_value"] = 0
  for values in areas_affected.values():
    if count < num:
      if values > dict_1["Max_value"]:
        dict_1["Max_value"] = values 
        count += 1
      else:
        count += 1
        continue 
    else:
      for items in areas_affected.items():
        tup = items
        if tup[1] == dict_1["Max_value"]:
          dict_2 = {}
          dict_2[tup[0]] = tup[1]
          return dict_2
        else:
          continue


most_affected = (most_affected(affected_areas))

# write your greatest number of deaths function here:
def most_deaths(hurricanes):
  deaths = {}
  index = 0
  hurricane_names = []
  for hurricane in hurricanes.keys():
    hurricane_names.append(hurricane)
  for hurricane in hurricanes.values():
    deaths[hurricane_names[index]] = hurricane['Deaths']
    index += 1
  num = (int(len(deaths.keys())))
  count = 1
  dict_1 = {}
  dict_1["Max_value"] = 0
  for values in deaths.values():
    if count < num:
      if values > dict_1["Max_value"]:
        dict_1["Max_value"] = values 
        count += 1
      else:
        count += 1
        continue 
    else:
      for items in deaths.items():
        tup = items
        if tup[1] == dict_1["Max_value"]:
          dict_2 = {}
          dict_2[tup[0]] = tup[1]
          return dict_2
        else:
          continue

most_deaths = (most_deaths(hurricanes))




# write your catgeorize by mortality function here:
def mortality(hurricane):
  scale = {}
  scale_0 = []
  scale_1 = []
  scale_2 = []
  scale_3 = []
  scale_4 = []
  scale_5 = []
  deaths = {}
  index = 0
  num = 0
  hurricane_names = []
  for hurricane in hurricanes.keys():
    hurricane_names.append(hurricane)
  for hurricane in hurricanes.values():
    deaths[hurricane_names[index]] = hurricane['Deaths']
    index += 1
  for items in deaths.items():
    if items[1] == 0:
      scale_0.append(items[0])
    if (items[1] > 0) and (items[1] <= 100):
      scale_1.append(items[0])
    elif (items[1] > 100) and (items[1] <= 500):
      scale_2.append(items[0])
    elif (items[1] > 500) and (items[1] <= 1000):
      scale_3.append(items[0])
    elif (items[1] > 1000) and (items[1] <= 10000):
      scale_4.append(items[0])
    elif (items[1] > 10000):
      scale_5.append(items[0])
  scale[0] = scale_0
  scale[1] = scale_1
  scale[2] = scale_2
  scale[3] = scale_3
  scale[4] = scale_4
  scale[5] = scale_5
  return scale

mortality = (mortality(hurricanes))
# write your greatest damage function here:
def most_damages(hurricanes):
  damages = {}
  index = 0
  hurricane_names = []
  for hurricane in hurricanes.keys():
    hurricane_names.append(hurricane)
  for hurricane in hurricanes.values():
    if hurricane['Damage'] == 'Damages not recorded':
      damages[hurricane_names[index]] = 0
    else:
      damages[hurricane_names[index]] = hurricane['Damage']
    index += 1
  num = (int(len(damages.keys())))
  count = 1
  dict_1 = {}
  dict_1["Max_value"] = 0
  for values in damages.values():
    if count < num:
      if values > dict_1["Max_value"]:
        dict_1["Max_value"] = values 
        count += 1
      else:
        count += 1
        continue 
    else:
      for items in damages.items():
        tup = items
        if tup[1] == dict_1["Max_value"]:
          dict_2 = {}
          dict_2[tup[0]] = tup[1]
          return dict_2
        else:
          continue

most_damages = (most_damages(hurricanes))
# write your catgeorize by damage function here:
def damage_scale(hurricane):
  scale = {}
  scale_0 = []
  scale_1 = []
  scale_2 = []
  scale_3 = []
  scale_4 = []
  scale_5 = []
  damages = {}
  index = 0
  hurricane_names = []
  for hurricane in hurricanes.keys():
    hurricane_names.append(hurricane)
  for hurricane in hurricanes.values():
    if hurricane['Damage'] == 'Damages not recorded':
      damages[hurricane_names[index]] = 0
    else:
      damages[hurricane_names[index]] = hurricane['Damage']
    index += 1
  for items in damages.items():
    if items[1] == 0:
      scale_0.append(items[0])
    if (items[1] > 0) and (items[1] <= 100000000):
      scale_1.append(items[0])
    elif (items[1] > 100000000) and (items[1] <= 1000000000):
      scale_2.append(items[0])
    elif (items[1] > 1000000000) and (items[1] <= 10000000000):
      scale_3.append(items[0])
    elif (items[1] > 10000000000) and (items[1] <= 50000000000):
      scale_4.append(items[0])
    elif (items[1] > 50000000000):
      scale_5.append(items[0])
  scale['Damages not recorded'] = scale_0
  scale[1] = scale_1
  scale[2] = scale_2
  scale[3] = scale_3
  scale[4] = scale_4
  scale[5] = scale_5
  return scale

damage_scale = (damage_scale(hurricanes))