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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]

# 2. write your update damages function here:
def damages_cost(damages):
	# make a conversion variable(dictionary)
	conversion = {'M': 1000000, 'B': 1000000000}

	damages_list = []
	for damage in damages:
		if damage == 'Damages not recorded':
			damages_list.append(damage)
		elif damage[-1] == 'M':
			damage = float(damage.strip('M')) * conversion['M']
			damages_list.append(damage)
		elif damage[-1] == 'B':
			damage = float(damage.strip('B')) * conversion['B']
			damages_list.append(damage)
	return damages_list

updated_damages = damages_cost(damages)
# print(updated_damages)


# 3. write your construct hurricane dictionary function here:
def hurricanes_by_name(names, months, years, max_sustained_winds, areas_affected, updated_damages, deaths):
	hurricanes = dict()
	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], 'Damage': updated_damages[i], 'Deaths': deaths[i]}

	return hurricanes

# create dictioanary to store the output 
hurricanes = hurricanes_by_name(names, months, years,max_sustained_winds, areas_affected,updated_damages, deaths)
print(hurricanes)


# 4. write your construct hurricane by year dictionary function here:
def hurricanes_by_year(hurricanes):
	hurricanes_year = dict()
	for name in hurricanes:
		# year of hurricanes
		current_year = hurricanes[name]['Year']  # as key
		# hurricane dictionary
		current_cane = hurricanes[name]  # as value
		if current_year not in hurricanes_year:
			# values set as a list so it can be append if find the same key
			hurricanes_year[current_year] = [current_cane]
		else:
			hurricanes_year[current_year].append(current_cane)

	return hurricanes_year

# create a new dictionary based on year it happened
hurricanes_by_year = hurricanes_by_year(hurricanes)
print(hurricanes_by_year)


# 5. write your count affected areas function here:
def count_affected_area(hurricanes):
	areas_affected_count = dict()
	for name in hurricanes:
			for area in hurricanes[name]['Areas Affected']:
					areas_affected_count[area] = areas_affected_count.get(area, 0) + 1
	return areas_affected_count

# create a new dictionary based on the number of hurricanes involved in
areas_affected_count = count_affected_area(hurricanes)
print(areas_affected_count)


# 6. write your find most affected area function here:
def most_affected_area(areas_affected_count):
	# initial guess is element at the first index
	most_affected_area = 'Central America'
	most_affected_area_count = 0
	for area in areas_affected_count:
		if areas_affected_count[area] > most_affected_area_count:
				most_affected_area = area  # key
				most_affected_area_count = areas_affected_count[area]  # value
	
	return most_affected_area, most_affected_area_count

# create two variables to store the output
most_affected_area, most_affected_area_count = most_affected_area(areas_affected_count)
print('The most affected area is: ' + str(most_affected_area) + '. It was hit ' + str(most_affected_area_count) + ' times.')

# 7. write your greatest number of deaths function here:
def greatest_number_of_deaths(hurricanes):
	max_mortality_cane = 'Cuba I'  # initial guess
	max_mortality = 0
	for cane in hurricanes:
		if hurricanes[cane]['Deaths'] > max_mortality:
			max_mortality_cane = cane
			max_mortality = hurricanes[cane]['Deaths']

	return max_mortality_cane, max_mortality 

# create two variables to store the output
max_mortality_cane, max_mortality = greatest_number_of_deaths(hurricanes)
print('The most fatal hurricane is: ' + str(max_mortality_cane) + '. It has caused ' + str(max_mortality) + ' deaths')

# 8. write your catgeorize by mortality function here:
def mortality_rate(hurrianes):
	mortality_scale = {0: 0,
										 1: 100,
										 2: 500,
										 3: 1000,
										 4: 10000, }
	hurricanes_by_mortality = {0: [], 1: [], 2: [], 3: [], 4: [], 5: []}
	for cane in hurricanes:
		death = hurricanes[cane]['Deaths']
		if death <= mortality_scale[0]:
			hurricanes_by_mortality[0].append(hurricanes[cane])
		elif death > mortality_scale[0] and death <= mortality_scale[1]:
			hurricanes_by_mortality[1].append(hurricanes[cane])
		elif death > mortality_scale[1] and death <= mortality_scale[2]:
			hurricanes_by_mortality[2].append(hurricanes[cane])
		elif death > mortality_scale[2] and death <= mortality_scale[3]:
			hurricanes_by_mortality[3].append(hurricanes[cane])
		elif death > mortality_scale[3] and death <= mortality_scale[4]:
			hurricanes_by_mortality[4].append(hurricanes[cane])
		elif death > mortality_scale[4]:
			hurricanes_by_mortality[5].append(hurricanes[cane])

	return hurricanes_by_mortality

# create a new hurricane ditctionary based on mortality rate
hurricanes_by_mortality = mortality_rate(hurricanes)
print(hurricanes_by_mortality[5])

# 9. write your greatest damage function here:
def greatest_damage(hurricanes):
  max_damage_cane = 'Cuba I'
  max_damage = 0
  for cane in hurricanes:
    if hurricanes[cane]['Damage'] == "Damages not recorded":
      pass
    elif hurricanes[cane]['Damage'] > max_damage:
      max_damage_cane = cane
      max_damage = hurricanes[cane]['Damage']

  return max_damage_cane, max_damage

# find highest damage inducing hurricane and its total cost
max_damage_cane, max_damage = greatest_damage(hurricanes)
print('The greatest hurricane damage is : ' + str(max_damage_cane) + '. It has cost ' + str(max_damage) + ' USD')


# 10. write your categorize by damage function here:
def damage_rate(hurricanes):
	# hurricane with 1 damage would have resulted in 0 to 100000000 USDand etc etc
	damage_scale = {0: 0,
									1: 100000000,  # 100 millions usd
									2: 1000000000,  # 1 billion usd
									3: 10000000000,  # 10 billions usd
									4: 50000000000, }  # 50 billions
	hurricanes_by_damage = {0: [], 1: [], 2: [], 3: [], 4: [], 5: []}
	for cane in hurricanes:
		damage = hurricanes[cane]['Damage']
		if damage == 'Damages not recorded':
			hurricanes_by_damage[0].append(hurricanes[cane])				
		elif damage <= damage_scale[0]:
			hurricanes_by_damage[0].append(hurricanes[cane])
		elif damage > damage_scale[0] and damage <= damage_scale[1]:
			hurricanes_by_damage[1].append(hurricanes[cane])
		elif damage > damage_scale[1] and damage <= damage_scale[2]:
			hurricanes_by_damage[2].append(hurricanes[cane])
		elif damage > damage_scale[2] and damage <= damage_scale[3]:
			hurricanes_by_damage[3].append(hurricanes[cane])
		elif damage > damage_scale[3] and damage <= damage_scale[4]:
			hurricanes_by_damage[4].append(hurricanes[cane])
		elif damage > damage_scale[4]:
			hurricanes_by_damage[5].append(hurricanes[cane])

	return hurricanes_by_damage

# create a new hurricanes dictioanary based on damage severity
hurricanes_by_damage = damage_rate(hurricanes)
print(hurricanes_by_damage[5])