"""
Counter
A Counter is a dict subclass for counting hashable objects.
It is a collection where elements are stored as dictionary keys and their counts are stored as dictionary values. 
Counter is a subclass of dict that’s specially designed for counting hashable objects in Python
It’s a dictionary that stores objects as keys and counts as values.
"""

word = 'mississippi'
word_counter = {}

for char in word:
    # Here we will check if the character is present in our empty dictionary
    if char not in word_counter:
        # If its not present then add the character to the dictionary and add the initial value to 0
        word_counter[char] = 0
    # If its presnt already then we can assume that we are revisiting the char so increment it by 1
    word_counter[char] += 1

print(word_counter)

# Solving it by using count objects (Using .get method from dict)
counter_next = {}
for char in word:
    counter_next[char] = counter_next.get(char, 0) + 1

print(counter_next)

# Solving it using defaultdict
from collections import defaultdict, Counter

counter_3 = defaultdict(int)

for letter in word:
    counter_3[letter] += 1
print(counter_3)

### Counter ###
"""
Input parameters: Iterable or hashable objects 
Counter internally iterates through the input sequence, counts the number of times a given object occurs, and stores objects as keys and the counts as values.
"""

# Counter iterates over "mississippi" and produces a dictionary with the letters as keys and their frequency as values.
counter_4 = Counter(word)
print(counter_4)

# We can also paas the list as an argument
counter_5 = Counter(list(word))
print(counter_5)

# Creating couter instances with starting values
letters = Counter({"i": 4, "s": 4, "p": 2, "m": 1})

# Updating object counts
# by passing another iterable
letters.update('missouri')
print(letters)
# Counter({'i': 6, 's': 6, 'p': 2, 'm': 2, 'o': 1, 'u': 1, 'r': 1})

# Updating by passing anohter counter
letters.update(Counter({"i": 4, "s": 4, "p": 2, "m": 1}))
print(letters)
# Counter({'i': 10, 's': 10, 'p': 4, 'm': 3, 'o': 1, 'u': 1, 'r': 1})

### Accessing content in the counter ###
"""
    1. Similar to using a dictionary key value pairs
    2. Using .keys() method to access the keys
    3. Using .values() method to access the values
    4. Using .items() method to access the items
"""

new_word = Counter(('intuition'))
print(f'new_word => {new_word}')
for key in new_word.keys():
    print(key)

# Accessing the values
for value in new_word.values():
    print(value)

# Accessing both at the same time
for key, value in new_word.items():
    print(f'key => {key}, value => {value}')

### Finding most common objects ###
"""
If you need to list a group of objects according to their frequency, you can use .most_common(). 
This method returns a list of (object, count) . 
"""

sales = Counter(banana=15, tomato=4, apple=39, orange=30)

print(sales.most_common())
# [('apple', 39), ('orange', 30), ('banana', 15), ('tomato', 4)]

print(sales.most_common(1))
# [('apple', 39)]

print(sales.most_common(10))
# If the provided argument is greater than current counter's length it will return all objects
# [('apple', 39), ('orange', 30), ('banana', 15), ('tomato', 4)]

"""
Counter
A Counter is a dict subclass for counting hashable objects.
It is a collection where elements are stored as dictionary keys and their counts are stored as dictionary values. 
Counter is a subclass of dict that’s specially designed for counting hashable objects in Python
It’s a dictionary that stores objects as keys and counts as values.
"""

word = 'mississippi'
word_counter = {}

for char in word:
    # Here we will check if the character is present in our empty dictionary
    if char not in word_counter:
        # If its not present then add the character to the dictionary and add the initial value to 0
        word_counter[char] = 0
    # If its presnt already then we can assume that we are revisiting the char so increment it by 1
    word_counter[char] += 1

print(word_counter)

# Solving it by using count objects (Using .get method from dict)
counter_next = {}
for char in word:
    counter_next[char] = counter_next.get(char, 0) + 1

print(counter_next)

# Solving it using defaultdict
from collections import defaultdict, Counter

counter_3 = defaultdict(int)

for letter in word:
    counter_3[letter] += 1
print(counter_3)

### Counter ###
"""
Input parameters: Iterable or hashable objects 
Counter internally iterates through the input sequence, counts the number of times a given object occurs, and stores objects as keys and the counts as values.
"""

# Counter iterates over "mississippi" and produces a dictionary with the letters as keys and their frequency as values.
counter_4 = Counter(word)
print(counter_4)

# We can also paas the list as an argument
counter_5 = Counter(list(word))
print(counter_5)

# Creating couter instances with starting values
letters = Counter({"i": 4, "s": 4, "p": 2, "m": 1})

# Updating object counts
# by passing another iterable
letters.update('missouri')
print(letters)
# Counter({'i': 6, 's': 6, 'p': 2, 'm': 2, 'o': 1, 'u': 1, 'r': 1})

# Updating by passing anohter counter
letters.update(Counter({"i": 4, "s": 4, "p": 2, "m": 1}))
print(letters)
# Counter({'i': 10, 's': 10, 'p': 4, 'm': 3, 'o': 1, 'u': 1, 'r': 1})

### Accessing content in the counter ###
"""
    1. Similar to using a dictionary key value pairs
    2. Using .keys() method to access the keys
    3. Using .values() method to access the values
    4. Using .items() method to access the items
"""

new_word = Counter(('intuition'))
print(f'new_word => {new_word}')
for key in new_word.keys():
    print(key)

# Accessing the values
for value in new_word.values():
    print(value)

# Accessing both at the same time
for key, value in new_word.items():
    print(f'key => {key}, value => {value}')

### Finding most common objects ###
"""
If you need to list a group of objects according to their frequency, you can use .most_common(). 
This method returns a list of (object, count) . 
"""

sales = Counter(banana=15, tomato=4, apple=39, orange=30)

print(sales.most_common())
# [('apple', 39), ('orange', 30), ('banana', 15), ('tomato', 4)]

print(sales.most_common(1))
# [('apple', 39)]

print(sales.most_common(10))
# If the provided argument is greater than current counter's length it will return all objects
# [('apple', 39), ('orange', 30), ('banana', 15), ('tomato', 4)]

Counter A Counter is a dict subclass for counting hashable objects. It is a collection where elements are stored as dictionary keys and their counts are stored as dictionary values.  Counter is a subclass of dict that’s specially designed for counting hashable objects in Python It’s a dictionary that stores objects as keys and counts as values. # Here we will check if the character is present in our empty dictionary # If its not present then add the character to the dictionary and add the initial value to 0 # If its presnt already then we can assume that we are revisiting the char so increment it by 1 # Solving it by using count objects (Using .get method from dict) # Solving it using defaultdict ### Counter ### Input parameters: Iterable or hashable objects  Counter internally iterates through the input sequence, counts the number of times a given object occurs, and stores objects as keys and the counts as values. # Counter iterates over "mississippi" and produces a dictionary with the letters as keys and their frequency as values. # We can also paas the list as an argument # Creating couter instances with starting values # Updating object counts # by passing another iterable # Counter({'i': 6, 's': 6, 'p': 2, 'm': 2, 'o': 1, 'u': 1, 'r': 1}) # Updating by passing anohter counter # Counter({'i': 10, 's': 10, 'p': 4, 'm': 3, 'o': 1, 'u': 1, 'r': 1}) ### Accessing content in the counter ### 1. Similar to using a dictionary key value pairs     2. Using .keys() method to access the keys     3. Using .values() method to access the values     4. Using .items() method to access the items # Accessing the values # Accessing both at the same time ### Finding most common objects ### If you need to list a group of objects according to their frequency, you can use .most_common().  This method returns a list of (object, count) . # [('apple', 39), ('orange', 30), ('banana', 15), ('tomato', 4)] # [('apple', 39)] # If the provided argument is greater than current counter's length it will return all objects # [('apple', 39), ('orange', 30), ('banana', 15), ('tomato', 4)]