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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. fix damages

def fix_damage_func(data):
  damages = []
  for i in data:
    if i == 'Damages not recorded':
      damages.append(i)
    elif i[-1] == 'M':
      num = float(i[:-1])
      damages.append(num*1000000)
    elif i[-1] == 'B':
      num = float(i[:-1])
      damages.append(num*1000000000)
    else:
      print("else")
  return damages

fixed_damages = fix_damage_func(damages)
#print(fixed_damages)

#----------------------------------------------------------------
# 3. Create hurricane dict

def hurricane_dict(n,m,y,ma,a,f,d):
  hurr_name = {}
  for i in range(len(n)):
    hurr_name[n[i]] = {"Name": n[i], "Month": m[i], "Year": y[i],"Max Sustained Winds":ma[i],"Area's Affected": a[i],"Damages":f[i], "Deaths":d[i]}
  return hurr_name

hurricanes_by_name = hurricane_dict(names,months,years,max_sustained_winds,areas_affected,fixed_damages,deaths)
#print(hurricanes_by_name.get("Katrina"))
#print(hurricanes_by_name.get("Irma"))
#print(hurricanes_by_name.get("Maria"))

#----------------------------------------------------------------
# 4. Create hurricane by year dic

def hurricane_years(data):
  hurr_year = {}
  hurr_list = []
  current_year = 0
  for i in data:
    if data[i]["Year"] != current_year:
      current_year = data[i]["Year"]
      hurr_list = []
    elif data[i]["Year"] == current_year:
      hurr_list.append(data[i])
      hurr_year[data[i]["Year"]] = hurr_list

  return hurr_year

hurricanes_by_year = hurricane_years(hurricanes_by_name)
#print(hurricanes_by_year)

#----------------------------------------------------------------
# 5. Areas Affeceted Count

def affected_count(data):
  area_dict = {}
  hurr_name = ''
  count = 0
  for hur in data:
    for i in data[hur]["Area's Affected"]:
      if i != hurr_name:
        hurr_name = i
      if i == hurr_name:
        count += 1
        area_dict[hurr_name] = count
  return area_dict

areas_affected = affected_count(hurricanes_by_name)
#print(areas_affected)

#----------------------------------------------------------------
# 6. Most affected area

def most_affected_func(data):
  count = 0
  hurricane = ''
  hur = list(data.keys())
  num = list(data.values())

  for i in range(len(data)):
    if num[i] > count:
      count = num[i]
      hurricane = hur[i]
  return hurricane, count

most_affected = most_affected_func(areas_affected)
#print(most_affected)

#----------------------------------------------------------------
# 7. Most deaths func

def most_deaths_func(data):
  count = 0
  hurricane = ''
  num = []
  hur = []
  for i in data:
    num.append(data[i]["Deaths"])
    hur.append(data[i]["Name"])
  for i in range(len(num)):
    if num[i] > count:
      count = num[i]
      hurricane = hur[i]
  return hurricane, count

most_deaths = most_deaths_func(hurricanes_by_name)
#print(most_deaths)\
#----------------------------------------------------------------
# 8. Hurricanes by mortality rate

def hurricanes_by_mortality(data):
  mort_scale = {0: 0, 1: 100, 2: 500, 3: 1000, 4: 10000}
  hurr_mort_dict = {1:[],2:[],3:[],4:[], 5:[]}
  for i in data:
    if data[i]["Deaths"] <= mort_scale[1]:
      hurr_mort_dict[1].append(i)
    elif data[i]["Deaths"] <= mort_scale[2]:
      hurr_mort_dict[2].append(i)
    elif data[i]["Deaths"] <= mort_scale[3]:
      hurr_mort_dict[3].append(i)
    elif data[i]["Deaths"] <= mort_scale[4]:
      hurr_mort_dict[4].append(i)
    else:
      hurr_mort_dict[5].append(i)
  return hurr_mort_dict

hurricane_mortality_rating = hurricanes_by_mortality(hurricanes_by_name)
#print(hurricane_mortality_rating)
#---------------------------------------------------------------
# 9. Most Damage

def most_damage_price(data):
  hur = ''
  damage = 0
  hurr_list = []
  damage_list = []

  for i in data:
    if data[i]["Damages"] != "Damages not recorded":
      hurr_list.append(data[i]["Name"])
      damage_list.append(int(data[i]["Damages"]))

  for i in range(len(damage_list)):
    if damage_list[i] > damage:
      hur = hurr_list[i]
      damage = damage_list[i]
  return hur, damage

most_costly = most_damage_price(hurricanes_by_name)
#print(most_costly)

#---------------------------------------------------------------
# 10 Hurricanes by damage

def damage_scale_func(data):
  damage_scale = {0: 0, 1: 100000000, 2: 1000000000,3: 10000000000, 4: 50000000000}
  damage_dict = {1:[], 2:[], 3:[], 4:[], 5:[]}
  for i in data:
    if data[i]["Damages"] != "Damages not recorded":
        if data[i]["Damages"] < damage_scale[1]:
          damage_dict[1].append(i)
        elif data[i]["Damages"] < damage_scale[2]:
          damage_dict[2].append(i)
        elif data[i]["Damages"] < damage_scale[3]:
          damage_dict[3].append(i)
        elif data[i]["Damages"] < damage_scale[4]:
          damage_dict[4].append(i)
        else:
          damage_dict[5].append(i)
   return damage_dict

damage_scale = damage_scale_func(hurricanes_by_name)
#print(damage_scale)
#---------------------------------------------------------------
# Nicholas Cece