Codecademy export

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]

# 1
# Update Recorded Damages
conversion = {"M": 1000000,
              "B": 1000000000}

# test function by updating damages
def float_damages(damages):
  conversion = {"M": 1000000,
              "B": 1000000000}
  updated_damages=[]
  for damage in damages:
    if damage == "Damages not recorded":
      updated_damages.append(damage)
    elif damage[-1] == 'M':
      damage1 = float(damage.strip('M'))*conversion["M"]
      updated_damages.append(damage1)
    elif damage[-1] == 'B':
      damage2 = float(damage.strip('B'))*conversion["B"]
      updated_damages.append(damage2)
  return updated_damages

updated_damages = float_damages(damages)

# 2 
# Create a Table

# Create and view the hurricanes dictionary
def hurricane_dict(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
hurricanes_dict = hurricane_dict(names, months, years, max_sustained_winds, areas_affected, updated_damages, deaths)

#print(hurricanes_dict)

# 3
# Organizing by Year

# create a new dictionary of hurricanes with year and key
def hurricanes_by_year(hurricanes_dict):
    hurricanes_by_year = {}
    for name in hurricanes_dict.values():
        year = name['Year']
        if year not in hurricanes_by_year:
            year_list = []
            for cane in hurricanes_dict.values():
                if cane['Year'] == year:
                    year_list.append(cane)
            hurricanes_by_year[year] = year_list
    return hurricanes_by_year

hurricanes_by_year = hurricanes_by_year(hurricanes_dict)
#print(hurricanes_by_year)

# 4
# Counting Damaged Areas

# create dictionary of areas to store the number of hurricanes involved in
def count_canes_by_area(hurricanes_dict):
  hurricanes_by_area = {}
  for name in hurricanes_dict.values():
    for area in name['Areas Affected']:
      if area in hurricanes_by_area:
        hurricanes_by_area[area] += 1
      else:
        hurricanes_by_area[area] = 1
  return hurricanes_by_area

hurricanes_by_area = count_canes_by_area(hurricanes_dict)
#print(hurricanes_by_area)

# 5 
# Calculating Maximum Hurricane Count

# find most frequently affected area and the number of hurricanes involved in
def most_affected_area(hurricanes_by_area):
  max_hit_area = ''
  max_hits_per_area = 0
  for k,v in hurricanes_by_area.items():
        if v > max_hits_per_area:
            max_hits_per_area = v
            max_hit_area = k
  return (max_hit_area, max_hits_per_area)

most_affected_area = most_affected_area(hurricanes_by_area)
#print(most_affected_area)

# 6
# Calculating the Deadliest Hurricane

# find highest mortality hurricane and the number of deaths
def most_lethal_hurricane(hurricanes_dict):
  most_lethal_hurricane = ''
  num_of_deaths = 0
  for name in hurricanes_dict.values():
    if name['Deaths'] > num_of_deaths:
      most_lethal_hurricane = name['Name']
      num_of_deaths = name['Deaths']
  return most_lethal_hurricane, num_of_deaths

most_lethal_hurricane = most_lethal_hurricane(hurricanes_dict)
#print(most_lethal_hurricane)

# 7
# Rating Hurricanes by Mortality
mortality_scale = {0: 0,
                   1: 100,
                   2: 500,
                   3: 1000,
                   4: 10000}
# categorize hurricanes in new dictionary with mortality severity as key
def hurricanes_mortality_rating(hurricanes_dict):
  hurricanes_by_mortality = {}
  for i in mortality_scale.keys():
    hurricanes_by_mortality.update({i:[]})
  for name in hurricanes_dict.values():
    if name['Deaths'] == mortality_scale[0]:
      hurricanes_by_mortality[0].append(name['Name'])
    elif name['Deaths'] > mortality_scale[0] and name['Deaths']<= mortality_scale[1]:
      hurricanes_by_mortality[1].append(name['Name'])
    elif name['Deaths'] > mortality_scale[1] and name['Deaths']<= mortality_scale[2]:
      hurricanes_by_mortality[2].append(name['Name'])
    elif name['Deaths'] > mortality_scale[2] and name['Deaths']<= mortality_scale[3]:
      hurricanes_by_mortality[3].append(name['Name'])
    elif name['Deaths'] > mortality_scale[3] and name['Deaths']<= mortality_scale[4]:
      hurricanes_by_mortality[4].append(name['Name'])
  return hurricanes_by_mortality

hurricanes_by_mortality = hurricanes_mortality_rating(hurricanes_dict)
#print(hurricanes_by_mortality)

# 8 Calculating Hurricane Maximum Damage

# find highest damage inducing hurricane and its total cost
def highest_damage_hurricane(hurricanes_dict):
  max_damage_cost = 0
  max_damage_cane = ''
  for k,v in hurricanes_dict.items():
        if v['Damage'] == 'Damages not recorded':
          pass
        elif v['Damage'] > max_damage_cost:
            max_damage_cost = v['Damage']
            max_damage_cane = k
  return (max_damage_cane, max_damage_cost)

most_damaging = highest_damage_hurricane(hurricanes_dict)
#print(most_damaging)

# 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 hurricanes_damage_rating(hurricanes_dict):
  hurricanes_by_damage = {}
  for i in damage_scale.keys():
    hurricanes_by_damage.update({i:[]})
  for name in hurricanes_dict.values():
    if name['Damage'] == "Damages not recorded":
      hurricanes_by_damage[0].append(name)
    elif name['Damage'] > damage_scale[0] and name['Damage']<= damage_scale[1]:
      hurricanes_by_damage[1].append(name)
    elif name['Damage'] > damage_scale[1] and name['Damage']<= damage_scale[2]:
      hurricanes_by_damage[2].append(name)
    elif name['Damage'] > damage_scale[2] and name['Damage']<= damage_scale[3]:
      hurricanes_by_damage[3].append(name)
    elif name['Damage'] > damage_scale[3] and name['Damage']<= damage_scale[4]:
      hurricanes_by_damage[4].append(name)
  return hurricanes_by_damage

hurricanes_by_damage = hurricanes_damage_rating(hurricanes_dict)
#print(hurricanes_by_damage)