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Python possesses a module named collections which has different types of containers. A container is a python object which consists different objects and implements a way to retrieve those objects and iterate over them.

In this tutorial, we would be exploring different types of containers implemented by the collections module.

• Counters
• OrderedDict
• DefaultDict
• ChainMap
• NamedTuple
• DeQue

Counters

Counters are dict subclass which is used to keep the count of the elements present in an iterable in an unordered dictionary where the key represents the element and value represents the count of the element in the iterable

In order to initialize a counter object, we use the counter () function which can be called in the following ways 

from collections import Counter

1) Using sequence of items

counter = Counter(['D','C','C','E','E','E','A','A','X'])
print(counter)

Output:

Counter({'D': 1, 'C': 2, 'E': 3, 'A': 2, 'X': 1})

2) Using Dictionary

counter = Counter({'X':3,'Y':2,'Z':1})
print(counter)

Output:

Counter({'X': 3, 'Y': 2, 'Z': 1})

3) Using keyword arguments

counter = Counter(X=3,Y=2,Z=1)
print(counter)

Output:

Counter({'X': 3, 'Y': 2, 'Z': 1})

OrderedDict

An orderedDict are dict subclass but not like dictionary, they remember the order in which the keys are inserted

from collections import OrderedDict

orderdict = OrderedDict()
orderdict["x"] = 2
orderdict["y"] = 3
orderdict["z"] = 4

print(orderdict)

Output:

OrderedDict([('x', 2), ('y', 3), ('z', 4)])

1) When inserting new items in an existing ordered dictionary the new item is attached at the end of the dictionary hence maintaining the order of dictionary

orderdict["v"] = 5
print(orderdict)

Output:

OrderedDict([('x', 2), ('y', 3), ('z', 4), ('v', 5)])

2) When deleting an item from an existing ordered dictionary and inserting the same item again then that particular item is inserted at the end of the dictionary 

del orderdict["x"]

print(orderdict)

Output:

OrderedDict([('y', 3), ('z', 4), ('v', 5)])

orderdict["x"] = 2
print(orderdict)

Output:

OrderedDict([('y', 3), ('z', 4), ('v', 5), ('x', 2)])

3) When reassigning or updating the value of an existing key – value pair in an OrderedDict object, the position of the key is maintained but the key gets a new value

orderdict.update(z = "four")
print(orderdict)

Output:

OrderedDict([('y', 3), ('z', 'four'), ('v', 5), ('x', 2)]

DefaultDict

A DefaultDict is a dict subclass which provides default values for a key which never exists hence never raising a keyError

from collections import defaultdict

1) Using list as a defaultdict

dftdict = defaultdict(list)

for i in range(3):
    dftdict[i].append(i)

print(dftdict)

Output:

defaultdict(list, {0: [0], 1: [1], 2: [2]})

2) Using int as a defaultdict

intdict = defaultdict(int)

X = [1,2,3,4,5,1,1,3,4,5]

for i in X:

#The default value is 0 so there is no need to enter the key first

intdict[i] += 1

print(intdict)

Output:

defaultdict(int, {1: 3, 2: 1, 3: 2, 4: 2, 5: 2})

ChainMap

ChainMap are used to combine more than one dictionaries into a single unit hence returning a list of dictionaries

from collections import ChainMap

x1 = {'a': 0, 'b': 1}
x2 = {'c':2,'d':3}
x3 = {'e':4,'f':5}

chainmap = ChainMap(x1,x2,x3)

print(chainmap)

Output:

ChainMap({'a': 0, 'b': 1}, {'c': 2, 'd': 3}, {'e': 4, 'f': 5})

1) Accessing Values using key name

print(chainmap['a'])

Output:

0

2) Accessing Values 

print(chainmap.values())

Output:

ValuesView(ChainMap({'a': 0, 'b': 1}, {'c': 2, 'd': 3}, {'e': 4, 'f': 5}))

3) Accessing Keys

print(chainmap.keys())

Output:

KeysView(ChainMap({'a': 0, 'b': 1}, {'c': 2, 'd': 3}, {'e': 4, 'f': 5}))

4) Inserting new dictionary

A new dictionary is inserted at the beginning of the ChainMap by using the new_child() method

chainmap1 = chainmap.new_child({'g':6,'h':7})
print(chainmap1)

Output: 

ChainMap({'g': 6, 'h': 7}, {'a': 0, 'b': 1}, {'c': 2, 'd': 3}, {'e': 4, 'f': 5})

NamedTuple

A NamedTuple is a tuple object having names for every position 

from collections import namedtuple

1) Declaring the namedtuple

band = namedtuple('Country',['name','capital','famousband'])

2) Inserting values to the namedtuple

val = band("south korea","Seoul","BTS")
print(val)

Output:

Country(name='south korea', capital='Seoul', famousband='BTS')

3) Accessing the value using index

print(val[0])

Output:

'south korea'

4) Accessing the value using name

print(val.name)

Output:

'south korea'

Deque

A deque is a list for implementing append and pop operations on both sides of the container

from collections import deque

1) Declaring deque

queue = deque([4,5,6])
print(queue)

Output:

deque([4, 5, 6])

2) Using append to insert element at the right which is the end of deque

queue.append(7)
print(queue)

Output:

deque([4, 5, 6, 7])

3) Using append to insert element at the left which is the beginning of deque

queue.appendleft(3)

print(queue)

Output:

deque([3, 4, 5, 6, 7])

4) Using pop to delete element from the right which is the end of deque

queue.pop()
print(queue)

Output:

deque([3, 4, 5, 6])

5) Using popleft to delete element from the left which is the beginning of deque

queue.popleft()
print(queue)

Output:

deque([4, 5, 6])

 
Priya Sengar (Medium, Github) is a Data Scientist with Old Dominion University. Priya is passionate about solving problems in data and converting them into solutions.