CODEWITHSUNDEEP
python-3.x
Kamil Septio Trojnar
Kamil Septio Trojnar

Reputation: 337

How to reduce duplicating data in an array

What's the easiest and most efficient way to reduce the duplication of data?

I tried to make an algorithm, but it started to get way to complicated.

I do have data kept in an array like this: [[data, 'country_code',value],[data, 'country_code',value],[data, 'country_code',value],[data, 'country_code',value]]

For example, I have [[2019-01-23, "GER", 200],[2019-01-23,"USA",300],[2019-01-23,"GER", 301]].

And I need:

[[2019-01-23,"GER", 501],[2019-01-23,"USA",300]]

Upvotes: 2

Views: 53

Answers (2)

Samuel Dion-Girardeau
Samuel Dion-Girardeau

Reputation: 3170

The most idiomatic way to do that is to use a Counter, from the collections library:

>>> from collections import Counter
>>> data = [
...     ['2019-01-23', 'GER', 200],
...     ['2019-01-23', 'USA', 300],
...     ['2019-01-23', 'GER', 301],
... ]
>>> counter = Counter()
>>> for date, country_code, count in data:
...     counter[(date, country_code)] += count
...
>>> counter
Counter({('2019-01-23', 'GER'): 501, ('2019-01-23', 'USA'): 300})
>>> output_data = [[date, country_code, count] for (date, country_code), count in counter.items()]
>>> output_data
[['2019-01-23', 'USA', 300], ['2019-01-23', 'GER', 501]]

Upvotes: 1

wim
wim

Reputation: 362786

Accumulate with a defaultdict, and use a list comprehension to collect results:

>>> from collections import defaultdict
>>> d = defaultdict(int)
>>> for date, code, n in L:
...     d[date, code] += n
...     
>>> [[date, code, n] for [[date, code], n] in d.items()]
[['2019-01-23', 'GER', 501], ['2019-01-23', 'USA', 300]]

Upvotes: 4

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