collections.Counter()
'Counter' is a subclass of dict that counts the occurrences of elements in an iterable such as a list or string. It is useful for frequency analysis and ranking.
Syntax
from collections import Counter # Create a Counter from an iterable. c = Counter(iterable) # Get the n most common elements. c.most_common(n) # Return an iterator that repeats each element by its count. c.elements() # Arithmetic operations on Counters c1 + c2 # Add counts together. c1 - c2 # Subtract counts (elements with zero or negative counts are excluded). c1 & c2 # Keep the minimum count for each element. c1 | c2 # Keep the maximum count for each element.
Methods and Operators
| Method / Operator | Description |
|---|---|
| Counter(iterable) | Creates a dictionary from an iterable, with each element as a key and its occurrence count as the value. |
| c.most_common(n) | Returns a list of the n most common elements as '[( element, count), ...]', sorted by count descending. Omitting n returns all elements. |
| c.elements() | Returns an iterator that repeats each element by its count. Elements with a count less than one are not included. |
| c.update(iterable) | Adds the counts from a new iterable to the existing Counter. |
| c.subtract(iterable) | Subtracts the counts from a new iterable from the existing Counter. Negative values are preserved. |
| c1 + c2 | Returns a new Counter with counts added together from both Counters. |
| c1 - c2 | Returns a Counter with c2's counts subtracted from c1 (only positive values are kept). |
Sample Code
from collections import Counter
# Count the elements in a list.
fruits = ['apple', 'banana', 'apple', 'cherry', 'banana', 'apple']
c = Counter(fruits)
print(c) # Outputs: Counter({'apple': 3, 'banana': 2, 'cherry': 1})
# Access the count for each element like a dictionary.
print(c['apple']) # Outputs: 3
print(c['grape']) # Returns 0 for a missing key (no KeyError).
# Use most_common() to get the top n most frequent elements.
print(c.most_common(2)) # Outputs: [('apple', 3), ('banana', 2)]
# Count character frequencies in a string.
text = 'programming'
char_count = Counter(text)
print(char_count.most_common(3))
# Outputs the 3 most frequent characters (e.g., [('g', 2), ('r', 2), ('m', 2)]).
# Use update() to add more counts.
more_fruits = ['apple', 'grape', 'grape']
c.update(more_fruits)
print(c['apple']) # Outputs: 4
print(c['grape']) # Outputs: 2
# Arithmetic operations on Counters
c1 = Counter({'a': 3, 'b': 2})
c2 = Counter({'a': 1, 'c': 4})
print(c1 + c2) # Outputs: Counter({'c': 4, 'a': 4, 'b': 2})
print(c1 - c2) # Outputs: Counter({'a': 2, 'b': 2}) (positive values only)
print(c1 & c2) # Outputs: Counter({'a': 1}) (minimum counts)
print(c1 | c2) # Outputs: Counter({'c': 4, 'a': 3, 'b': 2}) (maximum counts)
# Use elements() to expand elements by their counts.
print(sorted(c1.elements())) # Outputs: ['a', 'a', 'a', 'b', 'b']
Notes
Since 'Counter' is a subclass of dict, you can use all standard dictionary methods ('keys()', 'values()', 'items()', etc.) directly. Unlike a regular dictionary, accessing a missing key returns '0' instead of raising a 'KeyError'.
Counter makes it straightforward to write code that answers "how many times does each element appear?" — useful for survey tallying, text analysis, and log frequency analysis.
The subtraction operator ('-') between Counters excludes elements with zero or negative results, whereas the 'subtract()' method preserves negative values. Use whichever fits your needs.
For a dictionary with default values, see 'collections.defaultdict()'.
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