π€« Secret data types smarter than lists, dicts
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Welcome back to Pandas Daily! Your daily 5-minute boost to becoming confident in Python. β We all know Pythonβs basic container data types β lists, dictionaries, tuples, sets. "Container" is just a data type that holds multiple items instead of single values. β However, many times basics are not enough. Like if you want count of different items in the list you will run a loop like below.
In:
fruits = ["apple", "banana", "apple", "cherry"] counts = {} for item in fruits: counts[item] = counts.get(item, 0) + 1 print(counts)
Out: {'apple': 2, 'banana': 1, 'cherry': 1}
β Can this be done in 1 line? Sure, here comes the collections module. It has specialized containers built for these exact jobs. Today, we explore Counter from collections β Count things right away. β π οΈ Import (load) "Counter" from collections module
In:
from collections import Counter
Out:
β β¨ Count items of each type in a flash
In:
fruits = ["apple", "banana", "apple", "cherry"] count = Counter(fruits) print(count)
Out: Counter({'apple': 2, 'banana': 1, 'cherry': 1})
π‘ looks like a dictionary but its not! Check 'type' β
In:
print(type(count))
Out:
β π Most common element
In:
letters = ["a", "b", "a", "c", "a", "b"] print(Counter(letters).most_common(1))
Out: [('a', 3)]
β π« Convert Counter results to dictionaries
In:
c = Counter("aabccc") print(dict(c))
Out: {'a': 2, 'b': 1, 'c': 3}
β π Update counts on the go
In:
c = Counter() c.update(["x", "y", "x"]) print(c) c.update(["x"]) print(c)
Out:
Counter({'x': 2, 'y': 1}) Counter({'x': 3, 'y': 1}) β π« Subtract counts easily
In:
c = Counter("aaabb") print(c) c.subtract("ab") print(c)
Out:
Counter({'a': 3, 'b': 2}) Counter({'a': 2, 'b': 1}) βπ£ More coming on this tomorrow. That's it for today! If you liked it, please share it with anyone who will find it useful πΌπΌ β |
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