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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]

# 1
# Update Recorded Damages
conversion = {"M": 1000000,
              "B": 1000000000}

# test function by updating damages

def updated_damages(damage):
  updated_damage = []
  conversion = {"M": 1000000,
              "B": 1000000000}
  for items in damage:
    if items == "Damages not recorded":
      updated_damage.append(items)
    elif items[-1] == "M":
      updated_damage.append(float(items[:-1]) * conversion["M"])
    elif items[-1] == "B":
        updated_damage.append(float(items[:-1]) * conversion["B"])
    
  return updated_damage

damages_total = updated_damages(damages)

# 2 
# Create a Table

def list_of_hurricanes(names, months, years, max_sustained_winds, areas_affected, damages, deaths):
  list_hurricanes = {}
  for i in range(0, len(names)):
    list_hurricanes[names[i]] = {"Name": names[i], "Month": months[i], "Year": years[i], "Max Sustained Wind": max_sustained_winds[i], "Areas Affected": areas_affected[i], "Damage": damages[i], "Death": deaths[i]}
  return list_hurricanes

hurricans_dictionary = list_of_hurricanes(names, months, years, max_sustained_winds, areas_affected, damages_total, deaths)

# Create and view the hurricanes dictionary

# 3
# Organizing by Year

# create a new dictionary of hurricanes with year and key

def hurricans_by_year(hurricans):
  hurricans_years = {}
  for key, values in hurricans.items():
    if values["Year"] in hurricans_years:
      hurricans_years[values["Year"]].append(values)
    else:
      hurricans_years[values["Year"]] = [values]
  return hurricans_years


hurricanes_years = hurricans_by_year(hurricans_dictionary)

#print(hurricanes_years)

# 4
# Counting Damaged Areas

# create dictionary of areas to store the number of hurricanes involved in

def often_affected(hurricans):
  count_affected = {}
  for key, value in hurricans.items():
    for value in value["Areas Affected"]:
      if value in count_affected:
        count_affected[value] += 1
      else:
        count_affected[value] = 1
  return count_affected

count_areas_affected = often_affected(hurricans_dictionary)

# 5 
# Calculating Maximum Hurricane Count

# find most frequently affected area and the number of hurricanes involved in

def most_often_hurrican(hurricans):
  max_area = ""
  max_count = 0
  for key in often_affected(hurricans):
    if often_affected(hurricans)[key] > max_count:
      max_area = key
      max_count = often_affected(hurricans)[key]
  return max_area + " " + str(max_count)


#print(most_often_hurrican(hurricans_dictionary))


# 6
# Calculating the Deadliest Hurricane

# find highest mortality hurricane and the number of deaths

def max_deaths(hurricans):
  max_death = 0
  deadly_hurrican = ""
  for key, value in hurricans.items():
    if value["Death"] > max_death:
      max_death = value["Death"]
      deadly_hurrican = key
  death_king = deadly_hurrican + " " + str(max_death)
  return death_king

#print(max_deaths(hurricans_dictionary))


# 7
# Rating Hurricanes by Mortality


# categorize hurricanes in new dictionary with mortality severity as key

def hurricans_by_mortality(hurricans):
  hurricans_mortality = {"1": [], "2": [], "3": [], "4": [], "5": []}
  for key, values in hurricans.items():
    if values["Death"] > 10000:
      hurricans_mortality["5"].append(values)
    elif values["Death"] > 1000:
      hurricans_mortality["4"].append(values)
    elif values["Death"] > 500:
      hurricans_mortality["3"].append(values)  
    elif values["Death"] > 100:
      hurricans_mortality["2"].append(values)  
    elif values["Death"] > 0:
      hurricans_mortality["1"].append(values)    
  return hurricans_mortality

#print(hurricans_by_mortality(hurricans_dictionary))



# 8 Calculating Hurricane Maximum Damage

# find highest damage inducing hurricane and its total cost

def max_cost(hurricans):
  max_cost = 0
  expensive_hurrican = ""
  for key, value in hurricans.items():
    if value["Damage"] == "Damages not recorded":
      continue
    elif value["Damage"] > max_cost:
      max_cost = value["Damage"]
      expensive_hurrican = key
  cost_king = expensive_hurrican + " " + str(max_cost)
  return cost_king

#print(max_cost(hurricans_dictionary))

# 9
# Rating Hurricanes by Damage
damage_scale = {0: 0,
                1: 100000000,
                2: 1000000000,
                3: 10000000000,
                4: 50000000000}
  
# categorize hurricanes in new dictionary with damage severity as key

def hurricans_by_damage(hurricans):
  hurricans_damage = {"0": [], "1": [], "2": [], "3": [], "4": [], "5": []}
  for key, values in hurricans.items():
    if values["Damage"] == "Damages not recorded":
      hurricans_damage["0"].append(values)
    elif values["Damage"] > 50000000000:
      hurricans_damage["5"].append(values)
    elif values["Damage"] > 10000000000:
      hurricans_damage["4"].append(values)
    elif values["Damage"] > 1000000000:
      hurricans_damage["3"].append(values)  
    elif values["Damage"] > 100000000:
      hurricans_damage["2"].append(values)  
    elif values["Damage"] > 0:
      hurricans_damage["1"].append(values)
    elif values["Damage"] == 0:
      hurricans_damage["0"].append(values)    
  return hurricans_damage

print(hurricans_by_damage(hurricans_dictionary))