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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}
updated_damages = []
def conversion_fun():
  for damage in damages:
    if damage == "Damages not recorded":
      updated_damages.append(damage)
    elif "M" in damage:
      number = damage.replace("M", "")
      fl_damage = float(number) * conversion["M"]
      updated_damages.append(fl_damage)
    elif "B" in damage:
      number = damage.replace("B", "")
      fl_damage = float(number) * conversion["B"]
      updated_damages.append(fl_damage)
  return updated_damages



# test function by updating damages
print(conversion_fun())

# 2 
# Create a Table

# Create and view the hurricanes dictionary
list_1 = ("Name", "Month", "Year", "Max Sustained Wind", "Areas Affected", "Damage", "Death") 
data = {}
for x in range(34):
  list_2 = []
  list_2.append(names[x])
  list_2.append(months[x])
  list_2.append(years[x])
  list_2.append(max_sustained_winds[x])
  list_2.append(areas_affected[x])
  list_2.append(updated_damages[x])
  list_2.append(deaths[x])
  data[names[x]]= dict(zip(list_1,list_2))
#print(data)

# 3
# Organizing by Year
dict_by_years = {}
for x in range(34):
  current_year = years[x]
  current_cane = data[names[x]]
  if current_year in dict_by_years:
    list1 = [dict_by_years[current_year]] + [current_cane]
    dict_by_years[current_year] = list1
  else:
    dict_by_years[current_year] = current_cane
#print(dict_by_years)  

   
     
  

# create a new dictionary of hurricanes with year and key


# 4
# Counting Damaged Areas
areas_affected_list = []
for x in range(34):
  areas_affected_list += areas_affected[x]
count_damage_dict = {}
for area in areas_affected_list:
  count = areas_affected_list.count(area)
  count_damage_dict[area] = count
print(count_damage_dict)

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


# 5 
# Calculating Maximum Hurricane Count
max_times = max(count_damage_dict.values())
for area in count_damage_dict.keys():
  if count_damage_dict[area] == max_times:
    max_cane_area = area
print(max_times)
print(max_cane_area)


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



# 6
# Calculating the Deadliest Hurricane
max_death = max(deaths)
max_death_num = 0
for x in range(34):
  if deaths[x] == max_death:
    max_death_num = x
max_death_cane = names[max_death_num]
print(max_death)
print(max_death_cane)



# find highest mortality hurricane and the number of deaths

# 7
# Rating Hurricanes by Mortality
mortality_scale_list = []
for x in range(34):
  if deaths[x] > 0 and deaths[x] <= 100: 
    mortality_scale_list.append(1)
  elif deaths[x] > 100 and deaths[x] <= 500:
    mortality_scale_list.append(2)
  elif deaths[x] > 500  and deaths[x] <= 1000:
    mortality_scale_list.append(3)
  elif deaths[x] > 1000 and deaths[x] <= 10000:
    mortality_scale_list.append(4)
  else:
    mortality_scale_list.append(5)

print(mortality_scale_list)

# categorize hurricanes in new dictionary with mortality severity as key
cane_1 = []
cane_2 = []
cane_3 = []
cane_4 = []
cane_5 = []

for x in range(34):
  if mortality_scale_list[x] == 1:
     cane_1.append(data[names[x]])
  elif mortality_scale_list[x] == 2: 
    cane_2.append(data[names[x]])
  elif mortality_scale_list[x] == 3: 
    cane_3.append(data[names[x]])
  elif mortality_scale_list[x] == 4: 
    cane_4.append(data[names[x]])
  elif mortality_scale_list[x] == 5: 
    cane_5.append(data[names[x]])

mortality_scale_dict = {1: cane_1, 2: cane_2, 3: cane_3, 4:
cane_4, 5: cane_5 }
print(mortality_scale_dict)
  


    







# 8 Calculating Hurricane Maximum Damage
updated_damages_floats = []
for damage in updated_damages:
  if damage == "Damages not recorded":
    updated_damages_floats.append(0)
  else:
    updated_damages_floats.append(damage)
max_damage = max(updated_damages_floats)
print(max_damage)
max_damage_num = 0
for x in range(34):
  if updated_damages_floats[x] == max_damage:
    max_damage_num = x
max_damage_cane = names[max_damage_num]
print(max_damage_cane)

# find highest damage inducing hurricane and its total cost


# 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

damage_scale_list = []
for x in range(34):
  if updated_damages_floats[x] > 0 and updated_damages_floats[x] <= 100000000: 
    damage_scale_list.append(1)
  elif updated_damages_floats[x] > 100000000 and updated_damages_floats[x] <= 1000000000:
    damage_scale_list.append(2)
  elif updated_damages_floats[x] > 1000000000 and updated_damages_floats[x] <= 10000000000:
    damage_scale_list.append(3)
  elif updated_damages_floats[x] > 10000000000 and updated_damages_floats[x] <= 50000000000:
    damage_scale_list.append(4)
  elif updated_damages_floats[x] > 50000000000:
    damage_scale_list.append(5)
  else:
    damage_scale_list.append(0)

print(damage_scale_list)

cane_1_dam = []
cane_2_dam = []
cane_3_dam = []
cane_4_dam = []
cane_5_dam = []

for x in range(34):
  if damage_scale_list[x] == 1:
     cane_1_dam.append(data[names[x]])
  elif damage_scale_list[x] == 2: 
    cane_2_dam.append(data[names[x]])
  elif damage_scale_list[x] == 3: 
    cane_3_dam.append(data[names[x]])
  elif damage_scale_list[x] == 4: 
    cane_4_dam.append(data[names[x]])
  elif damage_scale_list[x] == 5: 
    cane_5_dam.append(data[names[x]])

damage_scale_dict = {1: cane_1_dam, 2: cane_2_dam, 3: cane_3_dam, 4: cane_4_dam, 5: cane_5_dam }
print(damage_scale_dict)