Hurricane Analysis Challenge Project (Python)

This is my code, very good exercise. I hope your recommendations


My solution for the exercise.

Good exercise!

Hi guys here’s my code. I tried to use the dictionary we were asked to create in the beginning but not sure if that made things more difficult for myself. Regardless, if anyone has any tips on how to make my code cleaner or even wants to just connect let met know!

# 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 updated_damages(damages):
  updated_damages = []
  for damage in damages: 
    if damage == "Damages not recorded": 
      if damage[-1] == "M":
        updated_damages.append(float(damage.strip("M"))* conversion["M"])
      if damage[-1] == "B": 
        updated_damages.append(float(damage.strip("B")) * conversion["B"])
  return updated_damages
updated_damages = updated_damages(damages)
# print(updated_damages)

# 2 
# Create a Table
def dictionary(name, month, year, max_wind_sustained, areas_affected, updated_damages, death):
  dictionary = {}
  for i in range(len(damages)):
    dictionary[name[i]] = {
      "Name": name[i],
      "Month": month[i],
      "Year": year[i],
      "Max Sustained Wind": max_wind_sustained[i],
      "Areas affected": areas_affected[i],
      "Damage": updated_damages[i],
      "Deaths": deaths[i]
# Create and view the hurricanes dictionary
dictionary = dictionary(names, months, years, max_sustained_winds, areas_affected, updated_damages, deaths)
# print(dictionary)

# 3
# Organizing by Year
def year_dictionary(dictionary):
  year_dictionary = {}
  for key, value in dictionary.items():
    current_year = dictionary[key]["Year"]
    if current_year not in year_dictionary: 
      year_dictionary[current_year] = [value]
  return year_dictionary
# print(year_dictionary(dictionary))

#4 Counting Damaged Areas
def damaged_areas_count(dictionary):
  damage_area_count = {}
  for key,value in dictionary.items():
    for area in dictionary[key]["Areas affected"]: 
      if area not in damage_area_count:
        damage_area_count[area] = 1
        damage_area_count[area] +=1
  return damage_area_count

affected_area_dictionary = damaged_areas_count(dictionary)
# print(damaged_areas_count(dictionary))

# 5 
# Calculating Maximum Hurricane Count
def most_affected(affected_area_dict):
  hurricane_count = 0
  hurricane_area = ""
  for key, value in affected_area_dict.items():
    if value > hurricane_count: 
      hurricane_count = value 
      hurricane_area = key
  print(f"The most affected area is {hurricane_area} with a hurricane count of {hurricane_count}.")
# most_affected(affected_area_dictionary)
# find most frequently affected area and the number of hurricanes involved in

# Calculating the Deadliest Hurricane
# find highest mortality hurricane and the number of deaths
def deadliest_hurricane(dictionary):
  name_deadliest_hurricane = ''
  deaths_deadliest_hurricane = 0
  for key, value in dictionary.items():
    if dictionary[key]["Deaths"] > deaths_deadliest_hurricane:
      deaths_deadliest_hurricane  = dictionary[key]["Deaths"]
      name_deadliest_hurricane = key
  print(f"The deadliest hurricane is hurricane {name_deadliest_hurricane} with a total of {deaths_deadliest_hurricane} deaths.")
# deadliest_hurricane(dictionary)

# 7
# Rating Hurricanes by Mortality
# categorize hurricanes in new dictionary with mortality severity as key
def mortality_scaling(dictionary):
  mortality_scale_dictionary = {0: [] , 1: [], 2: [], 3: [], 4: []}
  mortality_scale = {0: 0,
                   1: 100,
                   2: 500,
                   3: 1000,
                   4: 10000}

  for key, value in dictionary.items():
    if dictionary[key]["Deaths"] == mortality_scale[0]:
    elif dictionary[key]["Deaths"] <= mortality_scale[1]:
    elif dictionary[key]["Deaths"] <= mortality_scale[2]:
    elif dictionary[key]["Deaths"] <= mortality_scale[3]:
  return mortality_scale_dictionary
# print(mortality_scaling(dictionary))

# 8 Calculating Hurricane Maximum Damage
# find highest damage inducing hurricane and its total cost
def max_damage_cost(dictionary):
  most_damage_cost = 0 
  hurricane_name = ""
  for key,values in dictionary.items(): 
    if dictionary[key]["Damage"] != "Damages not recorded" and float(dictionary[key]["Damage"]) > most_damage_cost:
      most_damage_cost = float(dictionary[key]["Damage"])
      hurricane_name = key
  print(f"The hurricane that induced the most damage was Hurricane {hurricane_name} at a total cost of {most_damage_cost}.")
# max_damage_cost(dictionary)

# 9
# Rating Hurricanes by Damage
damage_scale = {0: 0,
                1: 100000000,
                2: 1000000000,
                3: 10000000000,
                4: 50000000000}

def hurricane_damage_scaling(dictionary):
  hurricane_damage_scale = {
    0:[], 1:[], 2:[], 3:[], 4:[]
  for key,value in dictionary.items():
    if dictionary[key]["Damage"] == "Damages not recorded":
      if float(dictionary[key]["Damage"]) == damage_scale[0]:
      elif float(dictionary[key]["Damage"]) <= damage_scale[1]:
      elif float(dictionary[key]["Damage"]) <= damage_scale[2]:
      elif float(dictionary[key]["Damage"]) <= damage_scale[3]:
  return hurricane_damage_scale
# print(hurricane_damage_scaling(dictionary))
# categorize hurricanes in new dictionary with damage severity as key

Hi Everyone,

I just completed the Hurricane Analysis project.

I am pasting my gists below.

I find this project kinda hard to do; however, I was able to finish.

I appreciate any feedback

Here is my code!

Here’s my solution

Absolutely Love this challenge, learn a lot while completing it! :blush:
Here is my code:

Here is my code! I had quite a bit of trouble with syntax. I’m hoping to make my code look more organized in my next project.

Hi, I really enjoyed while working on this programming challenge. I share my code in Github:

Great exercise! would love feedback

1 Like

Here’s my completed project! I could feel my brain growing with this one lol. I added in extra code on step 5 to take care of an improper capitalization I saw in the area_affected list, so that’s what the extra functions are for.

Hi guys,

After some days of struggle I finally completed this challenge and I’m sharing my code via GitHub. I am happy to say I only had to rely on the solution for step 4, but this challenge allowed me to learn a LOT.

Any feedback on my code is greatly appreciated:

Here is my code!

Hi everyone! Here’s my soluntion: Codecademy export · GitHub

Being honest, it made me tired (in positive way). All the questions of algorithms, the better name to variables and the debugging hit me and I learned a lot!

I am a bit confused by part of the given solution, specifically in the portion for creating the year dictionary.

Here’s the code, for reference:

> hurricanes_by_year= dict() > for cane in hurricanes: > current_year = hurricanes[cane]['Year'] > current_cane = hurricanes[cane] > if current_year not in hurricanes_by_year: > hurricanes_by_year[current_year] = [current_cane] > else: > hurricanes_by_year[current_year].append(current_cane) > return hurricanes_by_year

In the sixth line above, why does current_cane need to be in brackets? If current_cane is defined as the output of hurricanes[cane], wouldn’t that be the whole sub-dictionary related to the specific hurricane? Why does it need to be placed in brackets, then, when defining it as the value for the key?

Here’s my go at this project.

Hi folks, very excited to share my first Python project!