Hurricane Analysis

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

def update_damages(lst):
  conversion = {"M": 1000000,
              "B": 1000000000}
  new_lst=[]
  for damage in lst:
    if damage=="Damages not recorded":
      calc="Damages not recorded"
      new_lst.append(calc)
    if "B" in damage:
      app=float(damage[:-1])
      calc=app*conversion["B"]
      new_lst.append(calc)
    if "M" in damage:
      app=float(damage[:-1])
      calc=app*conversion["M"]
      new_lst.append(calc)
  return (new_lst)



# test function by updating damages
updated_damages=update_damages(damages)
print(updated_damages)
#print(len(damages))


# 2 
# Create a Table
def hurricanes(names, months, years, max_sustained_winds, areas_affected, updated_damages, deaths):
  dict={}
  for i in range(len(names)):
    values={}
    values["Name"]=names[i]
    values["Month"]=months[i]
    values["Year"]=years[i]
    values["Max_sustained_wind"]=max_sustained_winds[i]
    values["Areas_affected"]=areas_affected[i]
    values["Damage"]=updated_damages[i]
    values["Deaths"]=deaths[i]
    dict[names[i]]=values
  return (dict)

# Create and view the hurricanes dictionary
dict_hurricanes=hurricanes(names, months, years, max_sustained_winds, areas_affected, updated_damages, deaths)
#print(dict_hurricanes)
# 3
# Organizing by Year

# create a new dictionary of hurricanes with year and key
def new_hurricanes(dict):
  new_dict={}
  yrs=[]
  vals=[]
  for hurricane in dict.values():
    key=hurricane['Year']
    if key not in yrs:
      yrs.append(key)
      vals=[]
    vals.append(hurricane)
    new_dict[key]=vals
    """print(key)
    print(hurricane)
    print(yrs)
    print(vals)
    print("\n")"""
  return (new_dict)
new_dict_hurricanes=new_hurricanes(dict_hurricanes)
#print(new_dict_hurricanes )


# 4
# Counting Damaged Areas

# create dictionary of areas to store the number of hurricanes involved in
def count_damaged_areas():
  areas_lst=[]
  for areas in areas_affected:
    #print(areas)
    for area in areas:
      areas_lst.append(area)
  #print("\n")
  #print(areas_lst)
  distinct=[]

  for area in areas_lst:
    if area not in distinct:
      distinct.append(area)
  #print("\n")
  #print(distinct)
  #print(len(distinct))
  dict_area={}
  for area in distinct:
    count=areas_lst.count(area)
    #print(area)
    #print(count)
    dict_area[area]=count
  return(dict_area)
dict_damaged_areas=count_damaged_areas()
#print(dict_damaged_areas)
# 5 
# Calculating Maximum Hurricane Count

# find most frequently affected area and the number of hurricanes involved in

def max_hur_count():
  x=0
  y=""
  for key,value in dict_damaged_areas.items():
    #print(key)
    #print(value)
    if value>x:
      x=value
      y=key
  print("{} is the area affected by the most hurricanes and was hit {} times.".format(y,x))
#max_hur_count()

# 6
# Calculating the Deadliest Hurricane

# find highest mortality hurricane and the number of deaths
def max_mortal():
  death_count=0
  death_count_name=""
  for key,value in dict_hurricanes.items():
    dic=value
    #print(dic)
    #print(dic["Deaths"])
    #print(key)
    #print("\n")
    if dic["Deaths"]>death_count:
      death_count=dic["Deaths"]
      death_count_name=key
  return print(death_count), print(death_count_name)
  #return death_count,death_count_name
#max_mortal()
# 7
# Rating Hurricanes by Mortality

#print(dict_hurricanes)
mortality_scale = {0: 0,
                   1: 100,
                   2: 500,
                   3: 1000,
                   4: 10000}
def hurricanes_by_mortality():
  dict_mortality={}
  lst_hur_0=[]
  lst_hur_1=[]
  lst_hur_2=[]
  lst_hur_3=[]
  lst_hur_4=[]
  for key,value in dict_hurricanes.items():
      
      for a,b in mortality_scale.items():
        mortality=b
        scale=a
        #print(mortality)
        if value["Deaths"] <=mortality:
          hur_mortal=mortality
          mortal_scale=scale
          break
      #print(value)
      #print(value["Deaths"])
      #print(key)
      #print(hur_mortal)
      #print(mortal_scale)
      #print("\n")
      
      if mortal_scale==0:
        lst_hur_0.append(key)
      if mortal_scale==1:
        lst_hur_1.append(key)
      if mortal_scale==2:
        lst_hur_2.append(key)
      if mortal_scale==3:
        lst_hur_3.append(key)
      if mortal_scale==4:
        lst_hur_4.append(key)
      if mortal_scale==5:
        lst_hur_5.append(key)

  dict_mortality[0]=lst_hur_0
  dict_mortality[1]=lst_hur_1
  dict_mortality[2]=lst_hur_2
  dict_mortality[3]=lst_hur_3
  dict_mortality[4]=lst_hur_4
  return dict_mortality

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

# 8 Calculating Hurricane Maximum Damage

# find highest damage inducing hurricane and its total cost

def max_damage():
  damage=0
  damage_key=""
  for key,value in dict_hurricanes.items():
    if type(value["Damage"]) == float and value["Damage"]>damage:
      damage=value["Damage"]
      damage_key=key
      #print("\tCurrent max value")
    
    """
    print(value["Damage"])
    print(type(value["Damage"]))
    print(key)
    print("\n")
    """
  return damage_key, damage

#print(max_damage())
# 9
# Rating Hurricanes by Damage
damage_scale = {0: 0,
                1: 100000000,
                2: 1000000000,
                3: 10000000000,
                4: 50000000000}
def rate_hurricane_by_damage():
  hurricanes_by_damage={}
  scale=0
  lst_nan=[]
  lst_0=[]
  lst_1=[]
  lst_2=[]
  lst_3=[]
  lst_4=[]
  for key,value in dict_hurricanes.items():
    #print(value["Damage"])

    for a,b in damage_scale.items():
      #print(b)
      if type(value["Damage"]) !=float:
        scale = "Not Recorded"
      if type(value["Damage"]) == float:
        if value["Damage"] <= b:
          scale=a
          break
    #print(scale)

    if scale =="Not Recorded":
      lst_nan.append(key)
    if scale ==0:
      lst_0.append(key)
    if scale ==1:
      lst_1.append(key)
    if scale ==2:
      lst_2.append(key)
    if scale ==3:
      lst_3.append(key)
    if scale ==4:
      lst_4.append(key)

    """print("NaN",lst_nan)
    print("Scale0",lst_0)
    print("Scale1",lst_1)
    print("Scale2",lst_2)
    print("Scale3",lst_3)
    print("Scale4",lst_4)
    print("\n")"""

    hurricanes_by_damage["Damages Not Recorded"]=lst_nan
    hurricanes_by_damage[0]=lst_0
    hurricanes_by_damage[1]=lst_1
    hurricanes_by_damage[2]=lst_2
    hurricanes_by_damage[3]=lst_3
    hurricanes_by_damage[4]=lst_4
  return(hurricanes_by_damage)

#print(rate_hurricane_by_damage())


# categorize hurricanes in new dictionary with damage severity as key