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# 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}
converted_damage = []
def converted_damages():
for item in damages:
if item.find("M") > -1:
converted_damage.append(float(item[0:-1]) * conversion.get("M"))
elif item.find("B") > -1:
converted_damage.append(float(item[0:-1]) * conversion.get("B"))
else:
converted_damage.append("Damages not recorded")
return converted_damage
# test function by updating damages
#print(converted_damages())
# 2
# Create a Table
hurricanes = {}
def hurricane_data():
for i in range(len(names)):
hurricanes[names[i]] = {"Name": names[i], "Month" : months[i], "Year": years[i], "Max Sustained Wind" : max_sustained_winds[i], "Areas Affected": areas_affected[i], "Damages" : list(converted_damages())[i], "Deaths" : deaths[i]}
return hurricanes
# Create and view the hurricanes dictionary
print("*************************")
print("Creating First Dictionary")
print("*************************")
print(hurricane_data())
print("\n")
# 3
# Organizing by Year
hurricane_years = {}
def hurricane_yearly():
for record in hurricanes:
current_hurricane = hurricanes.get(record)
current_year = current_hurricane.get("Year")
if current_year not in hurricane_years:
hurricane_years[current_year] = [current_hurricane]
else:
hurricane_years[current_year].append(current_hurricane)
return hurricane_years
# create a new dictionary of hurricanes with year and key
print("******************")
print("Organizing By Year")
print("******************")
print(hurricane_yearly())
print("\n")
# 4
# Counting Damaged Areas
hurricane_areas = {}
def hurricane_damage():
for record in hurricanes:
current_hurricane = hurricanes.get(record)
area = current_hurricane.get("Areas Affected")
for i in range(len(area)):
if area[i] not in hurricane_areas:
hurricane_areas[area[i]] = 1
else:
hurricane_areas[area[i]] += 1
return hurricane_areas
# create dictionary of areas to store the number of hurricanes involved in
print("*************************")
print("Counting Damaged Areas")
print("*************************")
print(hurricane_damage())
print("\n")
# 5
# Calculating Maximum Hurricane Count
def max_affected_area():
max_area = max(hurricane_areas, key=hurricane_areas.get)
return [max_area, hurricane_areas[max_area]]
# find most frequently affected area and the number of hurricanes involved in
print("**********************************************")
print("Most Affected Area, Times An Area Was Affected")
print("**********************************************")
print(max_affected_area())
print("\n")
# 6
# Calculating the Deadliest Hurricane
hurricane_deaths = {}
def deadliest():
for record in hurricanes:
current_hurricane = hurricanes.get(record)
name = current_hurricane.get("Name")
death = current_hurricane.get("Deaths")
hurricane_deaths[name] = death
max_death = max(hurricane_deaths, key=hurricane_deaths.get)
return [max_death, hurricane_deaths[max_death]]
# find highest mortality hurricane and the number of deaths
print("***************************")
print("Deadliest Hurricane, Deaths")
print("***************************")
print(deadliest())
print("\n")
# 7
# Rating Hurricanes by Mortality
hurricane_morts = {0:[], 1:[], 2:[], 3:[], 4:[], 5:[]}
def mortality_rate():
for record in hurricanes:
current_hurricane = hurricanes.get(record)
name = current_hurricane.get("Name")
death = current_hurricane.get("Deaths")
if death == 0:
hurricane_morts[0].append(current_hurricane)
elif death < 100:
hurricane_morts[1].append(current_hurricane)
elif death < 500:
hurricane_morts[2].append(current_hurricane)
elif death < 1000:
hurricane_morts[3].append(current_hurricane)
elif death < 10000:
hurricane_morts[4].append(current_hurricane)
else:
hurricane_morts[5].append(current_hurricane)
return hurricane_morts
# categorize hurricanes in new dictionary with mortality severity as key
print("******************")
print("Mortality Category")
print("******************")
print(mortality_rate())
print("\n")
# 8 Calculating Hurricane Maximum Damage
hurricane_damages = {}
def highest_damage():
for record in hurricanes:
current_hurricane = hurricanes.get(record)
name = current_hurricane.get("Name")
damage = current_hurricane.get("Damages")
if damage != "Damages not recorded":
hurricane_damages[name] = damage
max_damage = max(hurricane_damages, key=hurricane_damages.get)
return [max_damage, hurricane_damages[max_damage]]
# find highest damage inducing hurricane and its total cost
print("******************************************")
print("Highest Damaging Hurricane, Damage in USD")
print("******************************************")
print(highest_damage())
print("\n")
# 9
# Rating Hurricanes by Damage
damage_scale = {0: 0,
1: 100000000,
2: 1000000000,
3: 10000000000,
4: 50000000000}
hurricane_damage_rates = {0:[], 1:[], 2:[], 3:[], 4:[], 5:[]}
def damage_rate():
for record in hurricanes:
current_hurricane = hurricanes.get(record)
name = current_hurricane.get("Name")
damage = current_hurricane.get("Damages")
if damage != "Damages not recorded":
if damage == 0:
hurricane_damage_rates[0].append(current_hurricane)
elif damage < 100000000:
hurricane_damage_rates[1].append(current_hurricane)
elif damage < 1000000000:
hurricane_damage_rates[2].append(current_hurricane)
elif damage < 10000000000:
hurricane_damage_rates[3].append(current_hurricane)
elif damage < 50000000000:
hurricane_damage_rates[4].append(current_hurricane)
else:
hurricane_damage_rates[5].append(current_hurricane)
return hurricane_damage_rates
# categorize hurricanes in new dictionary with damage severity as key
print("***************************")
print("Hurricane Damage Categories")
print("***************************")
print(damage_rate())
print("\n")
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