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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 update_damage_prices(lst): | |
updated_damages = [] | |
for cost in lst: | |
if cost.find("M") != -1: | |
cost_no_m = cost[:-1] | |
updated_cost = float(cost_no_m)*conversion["M"] | |
updated_damages.append(updated_cost) | |
elif cost.find("B") != -1: | |
cost_no_m = cost[:-1] | |
updated_cost = float(cost_no_m)*conversion["B"] | |
updated_damages.append(updated_cost) | |
else: | |
updated_damages.append(cost) | |
return updated_damages | |
updated_damages = update_damage_prices(damages) | |
# 2 | |
# Create a Table | |
# Create and view the hurricanes dictionary | |
def make_name_dict(names, months, years, max_winds, areas, damages, deaths): | |
name_list = [] | |
mini_dict_list = [] | |
key_list = ["Name", "Month", "Year", "Max Sustained Wind", "Areas Affected", "Damage", "Death"] | |
for i in range(len(names)): | |
value_list = [names[i], months[i], years[i], max_winds[i], areas[i], damages[i], deaths[i]] | |
mini_dict = {key:value for key, value in zip(key_list, value_list)} | |
mini_dict_list.append(mini_dict) | |
name_list.append(names[i]) | |
dictionary = {key:value for key, value in zip(name_list, mini_dict_list)} | |
return dictionary, mini_dict_list | |
name_dict, mini_dict_list = make_name_dict(names, months, years, max_sustained_winds, areas_affected, updated_damages, deaths) | |
# 3 | |
# Organizing by Year | |
# create a new dictionary of hurricanes with year and key | |
def make_year_dict(dicts, years): | |
years_list = [] | |
for i in years: | |
if i not in years_list: | |
years_list.append(i) | |
year_dict = {} | |
for year in years_list: | |
for cane in dicts: | |
if year == cane["Year"]: | |
if year not in year_dict.keys(): | |
year_dict[year] = [cane] | |
else: | |
year_dict[year].append(cane) | |
return year_dict | |
year_dict = make_year_dict(mini_dict_list, years) | |
# 4 | |
# Counting Damaged Areas | |
# create dictionary of areas to store the number of hurricanes involved in | |
def get_area_count(areas): | |
areas_list = [] | |
count_list = [] | |
for lst in areas: | |
for place in lst: | |
if place not in areas_list: | |
areas_list.append(place) | |
for area in areas_list: | |
count = 0 | |
for lst in areas: | |
for place in lst: | |
if place == area: | |
count += 1 | |
count_list.append(count) | |
new_dict = {key:value for key, value in zip(areas_list, count_list)} | |
return new_dict | |
area_count_dict = get_area_count(areas_affected) | |
# 5 | |
# Calculating Maximum Hurricane Count | |
# find most frequently affected area and the number of hurricanes involved in | |
def get_most_affected_area(area_count): | |
count = 0 | |
for i in area_count: | |
if area_count[i] > count: | |
count = area_count[i] | |
for area, hit in area_count.items(): | |
if hit == count: | |
return area | |
most_affected_area = get_most_affected_area(area_count_dict) | |
# 6 | |
# Calculating the Deadliest Hurricane | |
# find highest mortality hurricane and the number of deaths | |
def get_most_deaths(cane_dict): | |
count = 0 | |
for i in cane_dict: | |
if cane_dict[i]["Death"] > count: | |
count = cane_dict[i]["Death"] | |
for i in cane_dict: | |
if cane_dict[i]["Death"] == count: | |
return cane_dict[i]["Name"], count | |
most_deaths = get_most_deaths(name_dict) | |
# 7 | |
# Rating Hurricanes by Mortality | |
def get_mortality_rating(cane_dict): | |
mortality_dict = {0: [], 1: [], 2: [], 3: [], 4: []} | |
for i in cane_dict: | |
if cane_dict[i]["Death"] <= 100: | |
mortality_dict[0].append(cane_dict[i]) | |
elif cane_dict[i]["Death"] <= 500: | |
mortality_dict[1].append(cane_dict[i]) | |
elif cane_dict[i]["Death"] <= 1000: | |
mortality_dict[2].append(cane_dict[i]) | |
elif cane_dict[i]["Death"] <= 10000: | |
mortality_dict[3].append(cane_dict[i]) | |
else: | |
mortality_dict[4].append(cane_dict[i]) | |
return mortality_dict | |
mort_ratings = get_mortality_rating(name_dict) | |
# categorize hurricanes in new dictionary with mortality severity as key | |
# 8 Calculating Hurricane Maximum Damage | |
# find highest damage inducing hurricane and its total cost | |
def get_most_damage(cane_dict): | |
count = 0 | |
for i in cane_dict: | |
if cane_dict[i]["Damage"] != "Damages not recorded": | |
if int(cane_dict[i]["Damage"]) > count: | |
count = cane_dict[i]["Damage"] | |
for i in cane_dict: | |
if cane_dict[i]["Damage"] == count: | |
return cane_dict[i]["Name"], count | |
most_damaging_cane = get_most_damage(name_dict) | |
#print("The most financially damaging was hurricane {}, with ${}.".format(most_damaging_cane[0], most_damaging_cane[1])) | |
# 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 get_damage_rating(cane_dict): | |
damage_dict = {0: [], 1: [], 2: [], 3: [], 4: [], 5: []} | |
for i in cane_dict: | |
if cane_dict[i]["Damage"] != "Damages not recorded": | |
if cane_dict[i]["Damage"] <= damage_scale[1]: | |
damage_dict[0].append(cane_dict[i]) | |
elif cane_dict[i]["Damage"] <= damage_scale[2]: | |
damage_dict[1].append(cane_dict[i]) | |
elif cane_dict[i]["Damage"] <= damage_scale[3]: | |
damage_dict[2].append(cane_dict[i]) | |
elif cane_dict[i]["Damage"] <= damage_scale[4]: | |
damage_dict[3].append(cane_dict[i]) | |
else: | |
damage_dict[4].append(cane_dict[i]) | |
return damage_dict | |
damage_ratings = get_damage_rating(name_dict) | |
print(damage_ratings) | |
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