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Created Mar 3, 2021
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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
for i in range(0, len(damages)):
if "B" in damages[i]:
damages[i] = damages[i].replace('B', "")
damages[i] = float(damages[i]) * 1000000000
elif "M" in damages[i]:
damages[i] = damages[i].replace("M", "")
damages[i] = float(damages[i]) * 1000000
#print(damages)
# 2
# Create a Table
hurricane_dict = {}
# Create and view the hurricanes dictionary
def dict_create(a,b,c,d,e,f,g):
for i in range(0, len(a)):
hurricane_dict[a[i]] = [{"Name":a[i]},{"Month":b[i]},{"Year":c[i]},{"Max Sustained Wind":d[i]},{"Areas Affected":e[i]},{"Damage":f[i]},{"Deaths":g[i]}]
dict_create(names,months,years,max_sustained_winds,areas_affected, damages,deaths)
#print(hurricane_dict)
# 3
# Organizing by Year
cane_year_dict = {}
# create a new dictionary of hurricanes with year and key
def cane_by_year(x):
for i in x:
for j in x[i]:
if 'Year' in j:
current_year = j['Year']
if current_year not in cane_year_dict:
cane_year_dict[current_year] = x[i]
elif current_year in cane_year_dict:
cane_year_dict[current_year].append(x[i])
return cane_year_dict
#print(cane_by_year(hurricane_dict))
# 4
# Counting Damaged Areas
hurricount = {}
# create dictionary of areas to store the number of hurricanes involved in
def counting_the_locanetions(x):
for i in x:
for j in x[i]:
if 'Areas Affected' in j:
for q in j['Areas Affected']:
if q not in hurricount:
hurricount[q] = 1
elif q in hurricount:
hurricount[q] += 1
return hurricount
counting_the_locanetions(hurricane_dict)
# 5
# Calculating Maximum Hurricane Count
# find most frequently affected area and the number of hurricanes involved in
def maximum_huricount(x):
ground_0 = 0
for i in x:
if x[i] > ground_0:
ground_0 = x[i]
else:
continue
return ground_0
#print(maximum_huricount(hurricount))
# 6
# Calculating the Deadliest Hurricane
deadliest = 0
# find highest mortality hurricane and the number of deaths
def hurricane_killer(x):
hurricane = ""
deaths = 0
for i in x:
for j in x[i]:
if 'Deaths' in j:
if j['Deaths'] > deaths:
deaths = j['Deaths']
hurricane = x[i][0]['Name']
return (deaths), (hurricane)
deaths, hurricane = hurricane_killer(hurricane_dict)
#print("The Hurricane that caused the most death is hurricane {} at a count of {} people".format(hurricane, deaths))
#print(hurricane_killer(hurricane_dict))
# 7
# Rating Hurricanes by Mortality
def mortality_ratings(x):
rate_my_cane = {0:[], 1:[], 2:[], 3:[], 4:[], 5:[]}
for i in x:
for j in x[i]:
if 'Deaths' in j:
if j['Deaths'] < 1:
rate_my_cane[0].append(x[i][0]['Name'])
elif j['Deaths'] > 1 and j['Deaths'] <= 100:
rate_my_cane[1].append(x[i][0]['Name'])
elif j['Deaths'] > 100 and j['Deaths'] <= 500:
rate_my_cane[2].append(x[i][0]['Name'])
elif j['Deaths'] > 500 and j['Deaths'] <= 1000:
rate_my_cane[3].append(x[i][0]['Name'])
elif j['Deaths'] > 1000 and j['Deaths'] <= 10000:
rate_my_cane[4].append(x[i][0]['Name'])
elif j['Deaths'] > 10000:
rate_my_cane[5].append(x[i][0]['Name'])
return rate_my_cane
#print(mortality_ratings(hurricane_dict))
# categorize hurricanes in new dictionary with mortality severity as key
# 8 Calculating Hurricane Maximum Damage
def thats_alot_of_damage(x):
to_the_max = 0
hurricane = ""
for i in x:
for j in x[i]:
if 'Damage' in j:
if not type(j['Damage']) == float:
break
elif j['Damage'] > to_the_max:
to_the_max = j['Damage']
hurricane = x[i][0]['Name']
return to_the_max, hurricane
print(thats_alot_of_damage(hurricane_dict))
# find highest damage inducing hurricane and its total cost
# 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 how_you_hurt(x):
hurtiness = {0:[], 1:[], 2:[], 3:[], 4:[], 5:[]}
for i in x:
for j in x[i]:
if 'Damage' in j:
if not type(j['Damage']) == float:
hurtiness[0].append(x[i][0]['Name'])
break
elif j['Damage'] < 1:
huriness[0].append(x[i][0]['Name'])
elif j['Damage'] > 1 and j['Damage'] <= 100000000:
hurtiness[1].append(x[i][0]['Name'])
elif j['Damage'] > 100000000 and j['Damage'] <= 1000000000:
hurtiness[2].append(x[i][0]['Name'])
elif j['Damage'] > 1000000000 and j['Damage'] <= 10000000000:
hurtiness[3].append(x[i][0]['Name'])
elif j['Damage'] > 10000000000 and j['Damage'] <= 50000000000:
hurtiness[4].append(x[i][0]['Name'])
elif j['Damage'] > 50000000000:
hurtiness[5].append(x[i][0]['Name'])
return hurtiness
print(how_you_hurt(hurricane_dict))
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