Alex's Hurricane Analysis Project

hurricane_analysis.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]

# 1
# Update Recorded Damages
conversion = {"M": 1000000,
              "B": 1000000000}
def update_damages(damages):
  updated_damages = []
  for record in damages:
    if ("Damages not recorded" in record) == True:
      updated_damages.append(record)
    elif ("M" in record) == True:
      updated_damages.append(float(record.replace("M", " ")) * conversion["M"])
    else:
      updated_damages.append(float(record.replace("B", " ")) * conversion["B"])
  return updated_damages

# test function by updating damages
new_damages = update_damages(damages)

# 2 
# Create a Table
def hurricane_dictionary(names, months, years, max_sustained_winds, areas_affected, deaths, damages):
  hurricane_dict = {names[i]:
                   {"Name": names[i], "Month": months[i], "Year": years[i], "Max Sustained Wind": max_sustained_winds[i], "Areas Affected": areas_affected[i], "Deaths": deaths[i], "Damage": damages[i]} for i in range(len(years))}
  return hurricane_dict

# Create and view the hurricanes dictionary
hurricanes = hurricane_dictionary(names, months, years, max_sustained_winds, areas_affected, deaths, new_damages)
#print(hurricanes)

# 3
# Organizing by Year
def hurricane_dict_year(current_dict):
  new_hurricane_dict = {}
  years = []
  for cane in current_dict.values():
    if cane["Year"] not in years:
      years.append(cane["Year"])
  new_hurricane_dict = {year: hurricane for year, hurricane in zip(years, current_dict.values())}
  return new_hurricane_dict


# create a new dictionary of hurricanes with year and key
hurricanes_by_year = hurricane_dict_year(hurricanes)
#print(hurricanes_by_year)

# 4
# Counting Damaged Areas
def damaged_areas(current_dict):
  hurricane_area_dict = {}
  area_count = []
  areas_affected = []
  for cane in current_dict.values():
    for area in cane["Areas Affected"]:
      if area not in areas_affected:
        areas_affected.append(area)
        area_count.append(1)
      elif area in areas_affected:
        area_count[areas_affected.index(area)] += 1
  hurricane_area_dict = {area: area_count for area, area_count in zip(areas_affected, area_count)}
  return hurricane_area_dict


# create dictionary of areas to store the number of hurricanes involved in
compiled_areas = damaged_areas(hurricanes)
#print(compiled_areas)

# 5 
# Calculating Maximum Hurricane Count
def most_hit_area(areas):
  hardest_hit_area = " "
  number_of_hits = 0
  for area, count in areas.items():
    if count > number_of_hits:
      number_of_hits = count
      hardest_hit_area = area
  print(hardest_hit_area + " is the worst hit at " + str(number_of_hits) + " hurricanes.")

# find most frequently affected area and the number of hurricanes involved in
#most_hit_area(compiled_areas)


# 6
# Calculating the Deadliest Hurricane
def deadliest_hurricane(hurricanes):
  deadliest_hurricane = " "
  most_deaths = 0
  for hurricane, values in hurricanes.items():
    if values["Deaths"] > most_deaths:
      most_deaths = values["Deaths"]
      deadliest_hurricane = hurricane
  print(deadliest_hurricane + " is the deadliest hurricane at " + str(most_deaths) + " deaths.") 
# find highest mortality hurricane and the number of deaths
#deadliest_hurricane(hurricanes)

# 7
# Rating Hurricanes by Mortality
def mortality_scale(hurricanes):
  deaths = []
  for hurricane, values in hurricanes.items():
    deaths.append(values["Deaths"])
  enumerated_deaths = enumerate(sorted(deaths))
  mortality = dict((num, deaths) for num,deaths in enumerated_deaths)
  return mortality

# categorize hurricanes in new dictionary with mortality severity as key
#print(mortality_scale(hurricanes))

# 8 Calculating Hurricane Maximum Damage

'''Originally my code did not include damages in the greater hurricane dictionary. As a result, the below section references the updated damages calculated from the first step. Can update later.'''

def greatest_cost(hurricanes, damages):
  costliest_hurricane = " "
  most_cost = 0
  for damage in damages:
    if damage == "Damages not recorded":
      pass
    elif float(damage) > most_cost:
      most_cost = float(damage)
      costliest_hurricane = list(hurricanes)[damages.index(most_cost)]
  print("The hurricane with the most damage was " + costliest_hurricane + " at " + str(most_cost) + " in damages.")
  

# find highest damage inducing hurricane and its total cost
#greatest_cost(hurricanes, new_damages)

# 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 hurricane_damage_rating(hurricanes, damage_scale):
  hurricane_damage_scale = {}
  damage_1 = []
  damage_2 = []
  damage_3 = []
  damage_4 = []
  damage_5 = []
  for hurricane, data in hurricanes.items():
    if data["Damage"] == "Damages not recorded":
      pass
    elif (data["Damage"] > damage_scale[0]) and (data["Damage"] <= damage_scale[1]):
      damage_1.append(data)
    elif (data["Damage"] > damage_scale[1]) and (data["Damage"] <= damage_scale[2]):
      damage_2.append(data)
    elif (data["Damage"] > damage_scale[2]) and (data["Damage"] <= damage_scale[3]):
      damage_3.append(data)
    elif (data["Damage"] > damage_scale[3]) and (data["Damage"] <= damage_scale[4]):
      damage_4.append(data)
    elif (data["Damage"] > damage_scale[4]):
      damage_5.append(data)
  hurricane_damage_scale = {1:damage_1, 2:damage_2, 3:damage_3, 4:damage_4, 5:damage_5}
  return hurricane_damage_scale

new_stuff_dict = hurricane_damage_rating(hurricanes, damage_scale)