In collections.Counter
, the method most_common(n)
returns only the n most frequent items in a list. I need exactly that but I need to include the equal counts as well.
from collections import Counter
test = Counter(["A","A","A","B","B","C","C","D","D","E","F","G","H"])
-->Counter({'A': 3, 'C': 2, 'B': 2, 'D': 2, 'E': 1, 'G': 1, 'F': 1, 'H': 1})
test.most_common(2)
-->[('A', 3), ('C', 2)
I would need [('A', 3), ('B', 2), ('C', 2), ('D', 2)]
since they have the same count as n=2 for this case. My real data is on DNA code and could be quite large. I need it to be somewhat efficient.
You can do something like this:
from itertools import takewhile
def get_items_upto_count(dct, n):
data = dct.most_common()
val = data[n-1][1] #get the value of n-1th item
#Now collect all items whose value is greater than or equal to `val`.
return list(takewhile(lambda x: x[1] >= val, data))
test = Counter(["A","A","A","B","B","C","C","D","D","E","F","G","H"])
print get_items_upto_count(test, 2)
#[('A', 3), ('C', 2), ('B', 2), ('D', 2)]
For smaller sets, just write a simple generator:
>>> test = Counter(["A","A","A","B","B","C","C","D","D","E","F","G","H"])
>>> g=(e for e in test.most_common() if e[1]>=2)
>>> list(g)
[('A', 3), ('D', 2), ('C', 2), ('B', 2)]
For larger set, use ifilter (or just use filter
on Python 3):
>>> list(ifilter(lambda t: t[1]>=2, test.most_common()))
[('A', 3), ('C', 2), ('B', 2), ('D', 2)]
Or, since most_common
are already ordered, just use a for loop and break on the desired condition in a generator:
def fc(d, f):
for t in d.most_common():
if not f(t[1]):
break
yield t
>>> list(fc(test, lambda e: e>=2))
[('A', 3), ('B', 2), ('C', 2), ('D', 2)]