Container data type Counter

ref: Reference for Counter datatypes

Counter datatype

It keeps track of how many times equivalent values are added.

Initialization

It supports 3 types of initialization --

import collections

1. print collections.Counter(['a', 'b', 'c', 'a', 'b', 'b'])

2. print collections.Counter({'a':2, 'b':3, 'c':1})

3. print collections.Counter(a=2, b=3, c=1)

---

An empty Counter can be constructed with no arguments and populated via the update() method.

import collections

c = collections.Counter()

print 'Initial :', c

1. c.update('abcdaab')

print 'Sequence:', c

2. c.update({'a':1, 'd':5})

print 'Dict :', c

---

$ python collections_counter_update.py

Initial : Counter()

Sequence: Counter({'a': 3, 'b': 2, 'c': 1, 'd': 1})

Dict : Counter({'d': 6, 'a': 4, 'b': 2, 'c': 1})

---

Accessing counts

1. Once a Counter is populated, its values can be retrieved using the dictionary API.

import collections

c = collections.Counter('abcdaab')

for letter in 'abcde':

print '%s : %d' % (letter, c[letter])

2. elements()

The elements() method returns an iterator that produces all of the items known to the Counter.

Example: import collections

c = collections.Counter('extremely')

c['z'] = 0

print(c)

print(list(c.elements()))

output --

$ python collections_counter_elements.py

Counter({'e': 3, 'm': 1, 'l': 1, 'r': 1, 't': 1, 'y': 1, 'x': 1, 'z': 0})

['e', 'e', 'e', 'm', 'l', 'r', 't', 'y', 'x']

3. Use most_common() to produce a sequence of the n most frequently encountered input values and their respective counts.

Example: import collections

c = collections.Counter()

with open('/usr/share/dict/words', 'rt') as f:

`for line in f:`

    `c.update(line.rstrip().lower())`

print 'Most common:'

for letter, count in c.most_common(3):

`print '%s: %7d' % (letter, count)`

This example counts the letters appearing in all of the words in the system dictionary to produce a frequency distribution, then prints the three most common letters. Leaving out the argument to most_common() produces a list of all the items, in order of frequency.

$ python collections_counter_most_common.py

Most common:

e: 235331

i: 201032

a: 199554

Must read: All the necessary tools of python