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script.py

import numpy as np

# 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]

# write your update damages function here:
def update_damages(damages):
  updated_damages = []
  for damage in damages:
    if damage == "Damages not recorded":
      updated_damages.append(damage)
    elif damage[-1] == 'B':
      damage = float(damage[0:-1])*1000000000
      updated_damages.append(damage)
    elif damage[-1] == 'M':
      damage = float(damage[0:-1])*1000000
      updated_damages.append(damage)
  return updated_damages
updated_damages = update_damages(damages)
# print(updated_damages)

# write your construct hurricane dictionary function here:
def constructCaneDictionary(names, months, years, max_sustained_winds, areas_affected, updated_damages, deaths):
  hurricane_dict = {}
  for i in range(len(names)):
    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],
    'Damage': updated_damages[i],
    'Deaths': deaths[i]}
  return hurricane_dict

hurricane_dict = constructCaneDictionary(names, months, years, max_sustained_winds, areas_affected, updated_damages, deaths)
# print(hurricane_dict)

# write your construct hurricane by year dictionary function here:
def convertToCanesByYear(hurricane_dict):
  # iniitialise empty output dictionary
  year_dict = {}
  # initialise empty year counter as list
  year_list = []
  # loop through input dictionary
  for hurricane, list in hurricane_dict.items():
    # extract current year
    current_year = list['Year']
    # extract current hurricane
    current_cane = list
    # if year is in list already then append
    if current_year in year_list:
      year_dict[str(current_year)].append(current_cane)
    # if not then create new value for key for this year
    else:
      year_dict[str(current_year)] = [current_cane]
    # update year list
    year_list.append(current_year)
  # return dictionary as output
  return year_dict

year_dict = convertToCanesByYear(hurricane_dict)
# print(year_dict)  

# write your count affected areas function here:
def countAffectedAreas(areas_affected):
  areas_count = {}
  areas_list  = []
  for areas in areas_affected:
    for area in areas:
      if area in areas_list:
        areas_count[area] += 1
      else:
        areas_count[area] = 1
    areas_list.append(area)
  return areas_count

areas_count = countAffectedAreas(areas_affected)
# print(areas_count)

# write your find most affected area function here:
def findMostAffecteArea(areas_count):
  current_max = 0
  for area, count in areas_count.items():
    if count > current_max:
      current_max = count
      most_affected_area = area
  return most_affected_area

most_affected_area = findMostAffecteArea(areas_count)
# print(most_affected_area)


# write your greatest number of deaths function here:
def maxDeaths(deaths, names):
  max_deaths = np.max(deaths)
  index = np.argmax(deaths)
  max_deaths_cane = names[index]
  return max_deaths, max_deaths_cane

max_deaths, max_deaths_cane = maxDeaths(deaths, names)
# print(max_deaths_cane)
# print(max_deaths)

# write your catgeorize by mortality function here:
def categoriseByDeaths(hurricane_dict):
  canes_by_deaths = {0:[], 1:[], 2:[], 3:[], 4:[], 5:[]}
  for cane, deets in hurricane_dict.items():
    # print(deets['Deaths'])
    deaths = deets['Deaths']
    if deaths > 10000:
      grade = 5
    if deaths > 1000:
      grade = 4
    elif deaths > 500:
      grade = 3
    elif deaths > 100:
      grade = 2
    elif deaths > 0:
      grade = 1
    else:
      grade = 0
    canes_by_deaths[grade].append(deets['Name'])
  return canes_by_deaths

canes_by_deaths = categoriseByDeaths(hurricane_dict)
# print(canes_by_deaths)


# write your greatest damage function here:

def maxDamages(updated_damages, names):
  updated_updated_damages = []
  for damage in updated_damages:
    if damage == 'Damages not recorded':
      updated_updated_damages.append(0)
    else:
      updated_updated_damages.append(damage)
      max_damage = np.max(updated_updated_damages)
  index = np.argmax(updated_updated_damages)
  max_damage_cane = names[index]
  return max_damage, max_damage_cane

max_damage, max_damage_cane = maxDamages(updated_damages, names)
# print(max_damage_cane)
# print(max_damage)

# print(hurricane_dict)

# write your catgeorize by damage function here:
def createCanesByDamage(hurricane_dict):
  canes_by_damages = {0:[], 1:[], 2:[], 3:[], 4:[], 5:[]}
  for cane, deets in hurricane_dict.items():
    # print(deets['Deaths'])
    damage = deets['Damage']
    # print(damage)
    if damage == "Damages not recorded":
      grade = 0
    elif damage > 50000000000:
      grade = 5
    elif damage > 10000000000:
      grade = 4
    elif damage > 1000000000:
      grade = 3
    elif damage > 100000000:
      grade = 2
    elif damage > 0:
      grade = 1
    else:
      grade = 0
    canes_by_damages[grade].append(deets['Name'])
  return canes_by_damages
canes_by_damages = createCanesByDamage(hurricane_dict)
# print(canes_by_damages)