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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} | |
# test function by updating damages | |
def convert_to_num(damages): | |
damages_converted = [] | |
for damage in damages: | |
if(damage == 'Damages not recorded'): | |
damages_converted.append(damage) | |
else: | |
decimal_places = conversion[damage[-1]] | |
damage_num = float(damage[:-1]) * decimal_places | |
damages_converted.append(damage_num) | |
return damages_converted | |
# print(convert_to_num(damages)) | |
# 2 | |
# Create a Table | |
def create_hurricane_table(names, months, years, max_sustained_winds, areas_affected, damages, deaths): | |
hurricane_table = {} | |
zipped_datas = zip(names, months, years, max_sustained_winds, damages, deaths) | |
area_affected = 0 | |
for name, month, year, max_sustained_wind, damage, deaths in zipped_datas: | |
hurricane_table[name] = {'Name': name, 'Month': month, 'Year': year, 'Max Sustained Wind': max_sustained_wind, 'Areas Affected': areas_affected[area_affected], 'Damage': damage, 'Deaths': deaths} | |
area_affected += 1 | |
return hurricane_table | |
hurricane_table = create_hurricane_table(names, months, years, max_sustained_winds, areas_affected, damages, deaths) | |
# Create and view the hurricanes dictionary | |
# print(hurricane_table) | |
# 3 | |
# Organizing by Year | |
def hurricane_by_year(hurricane_table, years): | |
hurricanes_by_year = {} | |
for year in years: | |
hurricanes_by_year[year] = list() | |
for year in years: | |
for hurricane_datas in hurricane_table.values(): | |
if hurricane_datas['Year'] == year: | |
hurricanes_by_year[year].append(hurricane_datas) | |
return hurricanes_by_year | |
# create a new dictionary of hurricanes with year and key | |
hurricanes_by_years = hurricane_by_year(hurricane_table, years) | |
# print(hurricanes_by_years) | |
# 4 | |
# Counting Damaged Areas | |
def frequency_affected_area(hurricane_table, areas_affected): | |
affected_area_count = {} | |
for area_affected in areas_affected: | |
for area in area_affected: | |
affected_area_count[area] = 0 | |
for hurricane_data in hurricane_table.values(): | |
affected_areas = hurricane_data['Areas Affected'] | |
for area in affected_areas: | |
affected_area_count[area] += 1 | |
return affected_area_count | |
# create dictionary of areas to store the number of hurricanes involved in | |
affected_area_count = frequency_affected_area(hurricane_table, areas_affected) | |
# print(affected_area_count) | |
# 5 | |
# Calculating Maximum Hurricane Count | |
def most_affected_area(affected_area_count): | |
pair_area = ['', 0] | |
for area, frequency in affected_area_count.items(): | |
if pair_area[1] <= frequency: | |
pair_area = [area, frequency] | |
return pair_area | |
# find most frequently affected area and the number of hurricanes involved in | |
most_affected = most_affected_area(affected_area_count) | |
# print(most_affected) | |
# 6 | |
# Calculating the Deadliest Hurricane | |
def most_lethal_hurricane(hurricane_table): | |
pair_hurricane = ['', 0] | |
for hurricane_data in hurricane_table.values(): | |
if pair_hurricane[1] <= hurricane_data['Deaths']: | |
pair_hurricane[0] = hurricane_data['Name'] | |
pair_hurricane[1] = hurricane_data['Deaths'] | |
return pair_hurricane | |
# find highest mortality hurricane and the number of deaths | |
most_lethal = most_lethal_hurricane(hurricane_table) | |
# print(most_lethal) | |
# 7 | |
# Rating Hurricanes by Mortality | |
mortality_scale = {0: 0, | |
1: 100, | |
2: 500, | |
3: 1000, | |
4: 10000} | |
def hurricane_by_mortality(hurricane_table, mortality_scale): | |
hurricane_by_mortality = {} | |
for mortality in range(0, 6): | |
hurricane_by_mortality[mortality] = list() | |
for hurricane_data in hurricane_table.values(): | |
if hurricane_data['Deaths'] > 10000: | |
hurricane_by_mortality[5].append(hurricane_data) | |
else: | |
for mortality in mortality_scale.keys(): | |
if hurricane_data['Deaths'] <= mortality_scale[mortality]: | |
hurricane_by_mortality[mortality].append(hurricane_data) | |
break | |
return hurricane_by_mortality | |
# categorize hurricanes in new dictionary with mortality severity as key | |
hurricane_by_mortality = hurricane_by_mortality(hurricane_table, mortality_scale) | |
# print(hurricane_by_mortality) | |
# 8 Calculating Hurricane Maximum Damage | |
def damage_as_num(damage): | |
if(damage == 'Damages not recorded'): | |
return -1 | |
else: | |
decimal_places = conversion[damage[-1]] | |
damage_num = float(damage[:-1]) * decimal_places | |
return damage_num | |
def most_damage_hurricane(hurricane_table): | |
pair_hurricane = ['', 0] | |
for hurricane_data in hurricane_table.values(): | |
damage = damage_as_num(hurricane_data['Damage']) | |
if pair_hurricane[1] <= damage: | |
pair_hurricane[0] = hurricane_data['Name'] | |
pair_hurricane[1] = damage | |
return pair_hurricane | |
# find highest damage inducing hurricane and its total cost | |
damage_hurricane = most_damage_hurricane(hurricane_table) | |
# print(damage_hurricane) | |
# 9 | |
# Rating Hurricanes by Damage | |
damage_scale = {0: 0, | |
1: 100000000, | |
2: 1000000000, | |
3: 10000000000, | |
4: 50000000000} | |
def hurricane_by_damage(hurricane_table, damage_scale): | |
hurricane_by_damage = {} | |
for damage in range(0, 6): | |
hurricane_by_damage[damage] = list() | |
for hurricane_data in hurricane_table.values(): | |
damage_hurricane = damage_as_num(hurricane_data['Damage']) | |
if damage_hurricane > 50000000000: | |
hurricane_by_mortality[5].append(hurricane_data) | |
else: | |
for damage in damage_scale.keys(): | |
if damage_hurricane <= damage_scale[damage]: | |
hurricane_by_damage[damage].append(hurricane_data) | |
break | |
return hurricane_by_damage | |
# categorize hurricanes in new dictionary with damage severity as key | |
hurricanes_by_damage = hurricane_by_damage(hurricane_table, damage_scale) | |
# print(hurricanes_by_damage) | |
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