Summary - Collections

Combine Counter, defaultdict and deque to write a word frequency counter.

Summary - Collections

In this group we covered Counter, defaultdict, OrderedDict, deque and namedtuple. All five come from the collections module and ease different data tasks.

Counter counts, defaultdict produces defaults for missing keys, OrderedDict keeps and reorders, deque does fast two-ended addition, namedtuple gives immutable tuples with named fields. Now we'll write an example that combines a few of them.

Exercise Combined summary example

Start with from collections import Counter, defaultdict. Add the line text = "apple pear apple". Compute word counts with c = Counter(text.split()). Create a defaultdict with d = defaultdict(int) and loop for word in text.split(): with d[word] += 1. Then call print(c["apple"]) and print(d["apple"]).

Show example solution

# Count words with Counter and defaultdict
from collections import Counter, defaultdict

text = "apple pear apple"
c = Counter(text.split())
d = defaultdict(int)
for word in text.split():
    d[word] += 1
print(c["apple"])
print(d["apple"])

Test yourself

Which tool is ideal for counting?
- deque
- Counter
- namedtuple
- OrderedDict
Show answer

Counter — Counter is designed for counting items.
Match the tool and its purpose

Counter

Counting
defaultdict

Default production
deque

Two-ended queue
namedtuple

Named tuple

Import Counter and ...

from collections import Counter, ____

text = "apple pear apple"
c = Counter(text.split())
print(c["apple"])

Show answer

from collections import Counter, defaultdict

text = "apple pear apple"
c = Counter(text.split())
print(c["apple"])

Match the summary example parts

Counter

Fast counting
defaultdict

Loop counting
text.split()

Split words
d[word] += 1

Increment count

Next lesson: chain

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