[英]How to effciently calculate non-consecutive number of appereances of element in list?
So I'm trying to find out how many times a certain element is non consecutively appearing in a list.所以我试图找出某个元素没有连续出现在列表中的次数。 By that I mean:
我的意思是:
list = [10,10,10,11,12,10,12,14,10,10,10]
element_searched = 10
=> expected_output = 3
So that means that 10 is appearing 3 times in a the list.所以这意味着 10 在列表中出现了 3 次。
My code so far that seems to be working:到目前为止,我的代码似乎有效:
elements = [11, 10, 12]
row = [10,10,10,10,10,10,10,10,10,11,11,11,11,11,10,10,10,10,12,12,12,12,12,11,11,11,11,12,12,12,12,10]
element_on = False
for element in elements:
sequence = 0
for i in range(len(row)):
if element == row[i] and element_on==False:
sequence += 1
element_on = True
elif element==row[i] and element_on==True:
pass
elif element != row[i] and element_on==True:
element_on = False
#
elif element != row[i] and element_on == False:
element_on = False
#
print(f"For element {element} the number ob sequences is: {sequence} ")
I am getting the desired output but I am wondering if there is a more elegant and especially a faster way.我得到了所需的输出,但我想知道是否有更优雅,尤其是更快的方法。
Try this:尝试这个:
row = [10,10,10,10,10,10,10,10,10,11,11,11,11,11,10,10,10,10,12,12,12,12,12,11,11,11,11,12,12,12,12,10]
sr = pd.Series(row, name = "x")
sr[sr.groupby(sr.shift(-1).bfill(0).ne(sr)).transform('cumcount')==1].value_counts()
Output:输出:
10 3
12 2
11 2
First column is x
value, second is number of sequences.第一列是
x
值,第二列是序列数。
More compact and faster way:更紧凑、更快捷的方式:
from itertools import groupby
pd.Series([k for k, g in groupby(row)]).value_counts()
Another solution:另一种解决方案:
np.unique([k for k, g in groupby(row)], return_counts=True)
Result:结果:
(array([10, 11, 12]), array([3, 2, 2], dtype=int64))
Alternatively use np.bincount
:或者使用
np.bincount
:
np.bincount([k for k, g in groupby(row)])
But the output will be slightly different:但输出会略有不同:
array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 2, 2], dtype=int64)
I think this is what you want.我想这就是你想要的。 Groupby the list by similiar elements and then sum the counts
按相似元素对列表进行分组,然后对计数求和
import itertools
element_searched = 10
expected_output = sum([i.count(element_searched) for i in itertools.groupby(list)])
3
I would use a simple dictionary:我会使用一个简单的字典:
row = [10,10,10,10,10,10,10,10,10,11,11,11,11,11,10,10,10,10,12,12,12,12,12,11,11,11,11,12,12,12,12,10]
counter = {}
last_item = None
for item in row:
if last_item != item:
counter[item] = counter.get(item, 0) + 1
last_item = item
print (counter)
A few thoughts which should guide you:一些可以指导您的想法:
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