IT102Gists · October 24, 2018 17:44
diff --git a/pet_license_analyzer.py b/pet_license_analyzer.py
 # pet license csv file available at:
 # https://data.seattle.gov/Community/Seattle-Pet-Licenses/jguv-t9rb
 # data provided by City of Seattle Department of Finance and 
 # Administrative Services

 import csv

 # row 0 = license date
 # row 1 = license num
 # row 2 = name
 # row 3 = species
 # row 4 = primary breed
 # row 5 = secondary breed
 # row 6 = zip code

 def analyze_pet_names(filename):
    """reads csv file to analyze and count frequency of pet names"""  
    pet_names = {} # empty dict

    with open(filename, "r", encoding="utf-8") as f:
        csv_reader = csv.reader(f)
        headers = next(csv_reader)
        for row in csv_reader:
            # ignores empty fields
            if row[2] != "":
                pet_names[row[2]] = pet_names.get(row[2], 0) + 1

    # sort pet_names dict into a list of tuples by value
    # practice with list comprehensions!
    sorted_pet_names = [(k, pet_names[k])
                         for k in sorted(pet_names, key=pet_names.get, reverse=True)]
    top_name = sorted_pet_names[0]
    
    # fstrings require Python 3.6+
    print(f"The most common pet name in Seattle is '{top_name[0]}' "\
          f"which was listed on {top_name[1]} license applications.")
        
                        
 def analyze_pet_zips(filename):
    """reads csv file to analyze and count frequency of pet zip codes"""  
    pet_zips = {} # empty dict

    with open(filename, "r", encoding="utf-8") as f:
        csv_reader = csv.reader(f)
        headers = next(csv_reader)
        for row in csv_reader:
            pet_zips[row[6]] = pet_zips.get(row[6], 0) + 1

    # sort pet_zips dict into a list of tuples by value
    # more practice with list comprehensions!
    sorted_pet_zips = [(k, pet_zips[k])
                         for k in sorted(pet_zips, key=pet_zips.get, reverse=True)]
    top_zip = sorted_pet_zips[0]

    # fstrings require Python 3.6+
    print(f"The most common pet zip code in Seattle is {top_zip[0]} "\
          f"which was listed on {top_zip[1]} license applications.")


 def analyze_pet_species(filename):
    """reads csv file to analyze and count frequency of pet species"""  
    pet_species = {} # empty dict

    with open(filename, "r", encoding="utf-8") as f:
        csv_reader = csv.reader(f)
        headers = next(csv_reader)
        for row in csv_reader:
            pet_species[row[3]] = pet_species.get(row[3], 0) + 1

    # sort pet_species dict into a list of tuples by value
    # more practice with list comprehensions!
    sorted_pet_species = [(k, pet_species[k])
                         for k in sorted(pet_species, key=pet_species.get, reverse=True)]
    
    # fstrings require Python 3.6+
    for species, count in sorted_pet_species:
        print(f"{species} was listed on {count} license applications.")


 def analyze_dog_breeds(filename):
    """reads csv file to analyze and count frequency primary breed for all dogs"""  
    dog_breeds = {} # empty dict

    with open(filename, "r", encoding="utf-8") as f:
        csv_reader = csv.reader(f)
        headers = next(csv_reader)
        for row in csv_reader:
            dog_breeds[row[4]] = dog_breeds.get(row[4], 0) + 1

    # sort dog_breeds dict into a list of tuples by value
    # more practice with list comprehensions!
    sorted_dog_breeds = [(k, dog_breeds[k])
                         for k in sorted(dog_breeds, key=dog_breeds.get, reverse=True)]

    print("TOP 5 most popular dog breeds include:\n")
    for breed, count in sorted_dog_breeds[0:5]:
        print(breed, "=", count)

 # output results to user
 print("Seattle Pet License Summary\n".upper())
 analyze_pet_zips("Seattle_Pet_Licenses.csv")
 print("\n###\n")
 analyze_pet_names("Seattle_Pet_Licenses.csv")
 print("\n###\n")
 analyze_pet_species("Seattle_Pet_Licenses.csv")
 print("\n###\n")
 analyze_dog_breeds("Seattle_Pet_Licenses.csv")
	# pet license csv file available at:
	# https://data.seattle.gov/Community/Seattle-Pet-Licenses/jguv-t9rb
	# data provided by City of Seattle Department of Finance and
	# Administrative Services

	import csv

	# row 0 = license date
	# row 1 = license num
	# row 2 = name
	# row 3 = species
	# row 4 = primary breed
	# row 5 = secondary breed
	# row 6 = zip code

	def analyze_pet_names(filename):
	"""reads csv file to analyze and count frequency of pet names"""
	pet_names = {} # empty dict

	with open(filename, "r", encoding="utf-8") as f:
	csv_reader = csv.reader(f)
	headers = next(csv_reader)
	for row in csv_reader:
	# ignores empty fields
	if row[2] != "":
	pet_names[row[2]] = pet_names.get(row[2], 0) + 1

	# sort pet_names dict into a list of tuples by value
	# practice with list comprehensions!
	sorted_pet_names = [(k, pet_names[k])
	for k in sorted(pet_names, key=pet_names.get, reverse=True)]
	top_name = sorted_pet_names[0]

	# fstrings require Python 3.6+
	print(f"The most common pet name in Seattle is '{top_name[0]}' "\
	f"which was listed on {top_name[1]} license applications.")


	def analyze_pet_zips(filename):
	"""reads csv file to analyze and count frequency of pet zip codes"""
	pet_zips = {} # empty dict

	with open(filename, "r", encoding="utf-8") as f:
	csv_reader = csv.reader(f)
	headers = next(csv_reader)
	for row in csv_reader:
	pet_zips[row[6]] = pet_zips.get(row[6], 0) + 1

	# sort pet_zips dict into a list of tuples by value
	# more practice with list comprehensions!
	sorted_pet_zips = [(k, pet_zips[k])
	for k in sorted(pet_zips, key=pet_zips.get, reverse=True)]
	top_zip = sorted_pet_zips[0]

	# fstrings require Python 3.6+
	print(f"The most common pet zip code in Seattle is {top_zip[0]} "\
	f"which was listed on {top_zip[1]} license applications.")


	def analyze_pet_species(filename):
	"""reads csv file to analyze and count frequency of pet species"""
	pet_species = {} # empty dict

	with open(filename, "r", encoding="utf-8") as f:
	csv_reader = csv.reader(f)
	headers = next(csv_reader)
	for row in csv_reader:
	pet_species[row[3]] = pet_species.get(row[3], 0) + 1

	# sort pet_species dict into a list of tuples by value
	# more practice with list comprehensions!
	sorted_pet_species = [(k, pet_species[k])
	for k in sorted(pet_species, key=pet_species.get, reverse=True)]

	# fstrings require Python 3.6+
	for species, count in sorted_pet_species:
	print(f"{species} was listed on {count} license applications.")


	def analyze_dog_breeds(filename):
	"""reads csv file to analyze and count frequency primary breed for all dogs"""
	dog_breeds = {} # empty dict

	with open(filename, "r", encoding="utf-8") as f:
	csv_reader = csv.reader(f)
	headers = next(csv_reader)
	for row in csv_reader:
	dog_breeds[row[4]] = dog_breeds.get(row[4], 0) + 1

	# sort dog_breeds dict into a list of tuples by value
	# more practice with list comprehensions!
	sorted_dog_breeds = [(k, dog_breeds[k])
	for k in sorted(dog_breeds, key=dog_breeds.get, reverse=True)]

	print("TOP 5 most popular dog breeds include:\n")
	for breed, count in sorted_dog_breeds[0:5]:
	print(breed, "=", count)

	# output results to user
	print("Seattle Pet License Summary\n".upper())
	analyze_pet_zips("Seattle_Pet_Licenses.csv")
	print("\n###\n")
	analyze_pet_names("Seattle_Pet_Licenses.csv")
	print("\n###\n")
	analyze_pet_species("Seattle_Pet_Licenses.csv")
	print("\n###\n")
	analyze_dog_breeds("Seattle_Pet_Licenses.csv")