a = [1,2,3,4,5]
b = [1,3,5,6]
c = a and b
print c
actual output: [1,3,5,6]
expected output: [1,3,5]
How can we achieve a boolean AND operation (list intersection) on two lists?
If order is not important and you don't need to worry about duplicates then you can use set intersection:
>>> a = [1,2,3,4,5]
>>> b = [1,3,5,6]
>>> list(set(a) & set(b))
[1, 3, 5]
Using list comprehensions is a pretty obvious one for me. Not sure about performance, but at least things stay lists.
[x for x in a if x in b]
Or "all the x values that are in A, if the X value is in B".
If you convert the larger of the two lists into a set, you can get the intersection of that set with any iterable using intersection():
a = [1,2,3,4,5]
b = [1,3,5,6]
set(a).intersection(b)
Make a set out of the larger one:
_auxset = set(a)
Then,
c = [x for x in b if x in _auxset]
will do what you want (preserving b's ordering, not a's -- can't necessarily preserve both) and do it fast. (Using if x in a as the condition in the list comprehension would also work, and avoid the need to build _auxset, but unfortunately for lists of substantial length it would be a lot slower).
If you want the result to be sorted, rather than preserve either list's ordering, an even neater way might be:
c = sorted(set(a).intersection(b))
Here's some Python 2 / Python 3 code that generates timing information for both list-based and set-based methods of finding the intersection of two lists.
The pure list comprehension algorithms are O(n^2), since in on a list is a linear search. The set-based algorithms are O(n), since set search is O(1), and set creation is O(n) (and converting a set to a list is also O(n)). So for sufficiently large n the set-based algorithms are faster, but for small n the overheads of creating the set(s) make them slower than the pure list comp algorithms.
#!/usr/bin/env python
''' Time list- vs set-based list intersection
See http://stackoverflow.com/q/3697432/4014959
Written by PM 2Ring 2015.10.16
'''
from __future__ import print_function, division
from timeit import Timer
setup = 'from __main__ import a, b'
cmd_lista = '[u for u in a if u in b]'
cmd_listb = '[u for u in b if u in a]'
cmd_lcsa = 'sa=set(a);[u for u in b if u in sa]'
cmd_seta = 'list(set(a).intersection(b))'
cmd_setb = 'list(set(b).intersection(a))'
reps = 3
loops = 50000
def do_timing(heading, cmd, setup):
t = Timer(cmd, setup)
r = t.repeat(reps, loops)
r.sort()
print(heading, r)
return r[0]
m = 10
nums = list(range(6 * m))
for n in range(1, m + 1):
a = nums[:6*n:2]
b = nums[:6*n:3]
print('\nn =', n, len(a), len(b))
#print('\nn = %d\n%s %d\n%s %d' % (n, a, len(a), b, len(b)))
la = do_timing('lista', cmd_lista, setup)
lb = do_timing('listb', cmd_listb, setup)
lc = do_timing('lcsa ', cmd_lcsa, setup)
sa = do_timing('seta ', cmd_seta, setup)
sb = do_timing('setb ', cmd_setb, setup)
print(la/sa, lb/sa, lc/sa, la/sb, lb/sb, lc/sb)
output
n = 1 3 2
lista [0.082171916961669922, 0.082588911056518555, 0.0898590087890625]
listb [0.069530963897705078, 0.070394992828369141, 0.075379848480224609]
lcsa [0.11858987808227539, 0.1188349723815918, 0.12825107574462891]
seta [0.26900982856750488, 0.26902294158935547, 0.27298116683959961]
setb [0.27218389511108398, 0.27459001541137695, 0.34307217597961426]
0.305460649521 0.258469975867 0.440838458259 0.301898526833 0.255455833892 0.435697630214
n = 2 6 4
lista [0.15915989875793457, 0.16000485420227051, 0.16551494598388672]
listb [0.13000702857971191, 0.13060092926025391, 0.13543915748596191]
lcsa [0.18650484085083008, 0.18742108345031738, 0.19513416290283203]
seta [0.33592700958251953, 0.34001994132995605, 0.34146714210510254]
setb [0.29436492919921875, 0.2953648567199707, 0.30039691925048828]
0.473793098554 0.387009751735 0.555194537893 0.540689066428 0.441652573672 0.633583767462
n = 3 9 6
lista [0.27657914161682129, 0.28098297119140625, 0.28311991691589355]
listb [0.21585917472839355, 0.21679902076721191, 0.22272896766662598]
lcsa [0.22559309005737305, 0.2271728515625, 0.2323150634765625]
seta [0.36382699012756348, 0.36453008651733398, 0.36750602722167969]
setb [0.34979605674743652, 0.35533690452575684, 0.36164689064025879]
0.760194128313 0.59330170819 0.62005595016 0.790686848184 0.61710008036 0.644927481902
n = 4 12 8
lista [0.39616990089416504, 0.39746403694152832, 0.41129183769226074]
listb [0.33485794067382812, 0.33914685249328613, 0.37850618362426758]
lcsa [0.27405810356140137, 0.2745978832244873, 0.28249192237854004]
seta [0.39211201667785645, 0.39234519004821777, 0.39317893981933594]
setb [0.36988520622253418, 0.37011313438415527, 0.37571001052856445]
1.01034878821 0.85398540833 0.698928091731 1.07106176249 0.905302334456 0.740927452493
n = 5 15 10
lista [0.56792402267456055, 0.57422614097595215, 0.57740211486816406]
listb [0.47309303283691406, 0.47619009017944336, 0.47628307342529297]
lcsa [0.32805585861206055, 0.32813096046447754, 0.3349759578704834]
seta [0.40036201477050781, 0.40322518348693848, 0.40548801422119141]
setb [0.39103078842163086, 0.39722800254821777, 0.43811702728271484]
1.41852623806 1.18166313332 0.819398061028 1.45237674242 1.20986133789 0.838951479847
n = 6 18 12
lista [0.77897095680236816, 0.78187918663024902, 0.78467702865600586]
listb [0.629547119140625, 0.63210701942443848, 0.63321495056152344]
lcsa [0.36563992500305176, 0.36638498306274414, 0.38175487518310547]
seta [0.46695613861083984, 0.46992206573486328, 0.47583580017089844]
setb [0.47616910934448242, 0.47661614418029785, 0.4850609302520752]
1.66818870637 1.34819326075 0.783028414812 1.63591241329 1.32210827369 0.767878297495
n = 7 21 14
lista [0.9703209400177002, 0.9734041690826416, 1.0182771682739258]
listb [0.82394003868103027, 0.82625699043273926, 0.82796716690063477]
lcsa [0.40975093841552734, 0.41210508346557617, 0.42286920547485352]
seta [0.5086359977722168, 0.50968098640441895, 0.51014018058776855]
setb [0.48688101768493652, 0.4879908561706543, 0.49204087257385254]
1.90769222837 1.61990115188 0.805587768483 1.99293236904 1.69228211566 0.841583309951
n = 8 24 16
lista [1.204819917678833, 1.2206029891967773, 1.258256196975708]
listb [1.014998197555542, 1.0206191539764404, 1.0343101024627686]
lcsa [0.50966787338256836, 0.51018595695495605, 0.51319599151611328]
seta [0.50310111045837402, 0.50556015968322754, 0.51335406303405762]
setb [0.51472997665405273, 0.51948785781860352, 0.52113485336303711]
2.39478683834 2.01748351664 1.01305257092 2.34068341135 1.97190418975 0.990165516871
n = 9 27 18
lista [1.511646032333374, 1.5133969783782959, 1.5639569759368896]
listb [1.2461750507354736, 1.254518985748291, 1.2613379955291748]
lcsa [0.5565330982208252, 0.56119203567504883, 0.56451296806335449]
seta [0.5966339111328125, 0.60275578498840332, 0.64791703224182129]
setb [0.54694414138793945, 0.5508568286895752, 0.55375313758850098]
2.53362406013 2.08867620074 0.932788243907 2.76380331728 2.27843203069 1.01753187594
n = 10 30 20
lista [1.7777848243713379, 2.1453688144683838, 2.4085969924926758]
listb [1.5070111751556396, 1.5202279090881348, 1.5779800415039062]
lcsa [0.5954139232635498, 0.59703707695007324, 0.60746097564697266]
seta [0.61563014984130859, 0.62125110626220703, 0.62354087829589844]
setb [0.56723213195800781, 0.57257509231567383, 0.57460403442382812]
2.88774814689 2.44791645689 0.967161734066 3.13413984189 2.6567803378 1.04968299523
Generated using a 2GHz single core machine with 2GB of RAM running Python 2.6.6 on a Debian flavour of Linux (with Firefox running in the background).
These figures are only a rough guide, since the actual speeds of the various algorithms are affected differently by the proportion of elements that are in both source lists.
A functional way can be achieved using filter and lambda operator.
list1 = [1,2,3,4,5,6]
list2 = [2,4,6,9,10]
>>> list(filter(lambda x:x in list1, list2))
[2, 4, 6]
Edit: It filters out x that exists in both list1 and list, set difference can also be achieved using:
>>> list(filter(lambda x:x not in list1, list2))
[9,10]
Edit2: python3 filter returns a filter object, encapsulating it with list returns the output list.
a = [1,2,3,4,5]
b = [1,3,5,6]
c = list(set(a).intersection(set(b)))
Should work like a dream. And, if you can, use sets instead of lists to avoid all this type changing!
You can also use numpy.intersect1d(ar1, ar2).
It return the unique and sorted values that are in both of two arrays.
This way you get the intersection of two lists and also get the common duplicates.
>>> from collections import Counter
>>> a = Counter([1,2,3,4,5])
>>> b = Counter([1,3,5,6])
>>> a &= b
>>> list(a.elements())
[1, 3, 5]
This is an example when you need Each element in the result should appear as many times as it shows in both arrays.
def intersection(nums1, nums2):
#example:
#nums1 = [1,2,2,1]
#nums2 = [2,2]
#output = [2,2]
#find first 2 and remove from target, continue iterating
target, iterate = [nums1, nums2] if len(nums2) >= len(nums1) else [nums2, nums1] #iterate will look into target
if len(target) == 0:
return []
i = 0
store = []
while i < len(iterate):
element = iterate[i]
if element in target:
store.append(element)
target.remove(element)
i += 1
return store
In the case you have a list of lists map comes handy:
>>> lists = [[1, 2, 3], [2, 3, 4], [2, 3, 5]]
>>> set(lists.pop()).intersection(*map(set, lists))
{2, 3}
would work for similar iterables:
>>> lists = ['ash', 'nazg']
>>> set(lists.pop()).intersection(*map(set, lists))
{'a'}
pop will blow if the list is empty so you may want to wrap in a function:
def intersect_lists(lists):
try:
return set(lists.pop()).intersection(*map(set, lists))
except IndexError: # pop from empty list
return set()
It might be late but I just thought I should share for the case where you are required to do it manually (show working - haha) OR when you need all elements to appear as many times as possible or when you also need it to be unique.
Kindly note that tests have also been written for it.
from nose.tools import assert_equal
'''
Given two lists, print out the list of overlapping elements
'''
def overlap(l_a, l_b):
'''
compare the two lists l_a and l_b and return the overlapping
elements (intersecting) between the two
'''
#edge case is when they are the same lists
if l_a == l_b:
return [] #no overlapping elements
output = []
if len(l_a) == len(l_b):
for i in range(l_a): #same length so either one applies
if l_a[i] in l_b:
output.append(l_a[i])
#found all by now
#return output #if repetition does not matter
return list(set(output))
else:
#find the smallest and largest lists and go with that
sm = l_a if len(l_a) len(l_b) else l_b
for i in range(len(sm)):
if sm[i] in lg:
output.append(sm[i])
#return output #if repetition does not matter
return list(set(output))
## Test the Above Implementation
a = [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
b = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]
exp = [1, 2, 3, 5, 8, 13]
c = [4, 4, 5, 6]
d = [5, 7, 4, 8 ,6 ] #assuming it is not ordered
exp2 = [4, 5, 6]
class TestOverlap(object):
def test(self, sol):
t = sol(a, b)
assert_equal(t, exp)
print('Comparing the two lists produces')
print(t)
t = sol(c, d)
assert_equal(t, exp2)
print('Comparing the two lists produces')
print(t)
print('All Tests Passed!!')
t = TestOverlap()
t.test(overlap)
Most of the solutions here don't take the order of elements in the list into account and treat lists like sets. If on the other hand you want to find one of the longest subsequences contained in both lists, you can try the following code.
def intersect(a, b):
if a == [] or b == []:
return []
inter_1 = intersect(a[1:], b)
if a[0] in b:
idx = b.index(a[0])
inter_2 = [a[0]] + intersect(a[1:], b[idx+1:])
if len(inter_1) <= len(inter_2):
return inter_2
return inter_1
For a=[1,2,3] and b=[3,1,4,2] this returns [1,2] rather than [1,2,3]. Note that such a subsequence is not unique as [1], [2], [3] are all solutions for a=[1,2,3] and b=[3,2,1].
If, by Boolean AND, you mean items that appear in both lists, e.g. intersection, then you should look at Python's set and frozenset types.
You can also use a counter! It doesn't preserve the order, but it'll consider the duplicates:
>>> from collections import Counter
>>> a = [1,2,3,4,5]
>>> b = [1,3,5,6]
>>> d1, d2 = Counter(a), Counter(b)
>>> c = [n for n in d1.keys() & d2.keys() for _ in range(min(d1[n], d2[n]))]
>>> print(c)
[1,3,5]
when we used tuple and we want to intersection
a=([1,2,3,4,5,20], [8,3,9,5,1,4,20])
for i in range(len(a)):
b=set(a[i-1]).intersection(a[i])
print(b)
{1, 3, 4, 5, 20}
Related
I have two lists
a = [1,2,3]
b = []
I want to move an element from list a, if it meets a certain condition.
a = [1,3]
b = [2]
The below code shows an example, however, I would like to do this inside of a single loop. How do I do this more efficiently?
a = [1,2,3]
b = []
pop_list = []
for i in range(len(a)):
if a[i] == 2:
print("pop:", a[i])
pop_list.append(i)
for i in range(len(pop_list)):
b.append(a.pop(pop_list[i]))
# Reset pop_list
pop_list=[]
Ideally, I would not generate a new list b.
A pair of list comprehensions would do the job: one to select the desired elements for b, the other to remove them from a
b = [i for i in a if i == 2]
a = [i for i in a if i != 2]
You can use filter and itertools.filterfalse and use the same filtering function for both:
from itertools import filterfalse
a = [1,2,3]
b = []
list(filterfalse(lambda x: x == 2, a))
list(filter (lambda x: x == 2, a))
[1, 3]
[2]
Here is the itertools.filterfalse docs.
If the element x exists you could just remove it from b and append it to a.
a = [1, 2, 3]
b = []
x = 2
def remove_append(a, b, x):
if x in a:
a.remove(x)
b.append(x)
remove_append(a, b, x)
print(a)
print(b)
Output:
[1, 3]
[2]
We must pass through all elements, however, you can apply this trick to add to the appropriate list in one loop:
(Appending to a loop is more efficient than deleting an element at arbitrary position)
a = [1,2,3]
condition_false, condition_true = [], []
for v in a:
# Add to the right list
(condition_false, condition_true)[v == 2].append(v)
# [1, 3]
print(condition_false)
# [2]
print(condition_true)
Here is a single loop way that's similar to your initial method:
length = len(a)
popped = 0
for i in range(length):
if i == length - popped:
break
if a[i] == 2:
b.append(a.pop(i))
popped += 1
If we keep track of how many elements we pop from a, we can just stop our loop that many elements early since there are fewer elements left in a.
I am trying to find an efficient solution to subsequent problem:
I have a number of x lists (number unknown) with each having different but also overlapping elements. I would like to find the elements unique to each list and output them separately.
For example if I have 3 lists:
a = [1,2,3,4]
b = [2,5,6,7]
c = [3,6,8,9]
This would result in an output of (I am not trying to find the unique elements only):
a --> [1,4]
b --> [5,7]
c --> [8,9]
Assuming that one list gets generated sequentially. I was thinking of using sets but believe that this can be solved when each list gets generated.
Here is a simple solution in O(N) where N is the total number of elements.
The key idea is to count for each elements how many times it appears in all the lists. Then you can filter each list by keeping only elements that appear once.
from collections import Counter
a = [1,2,3,4]
b = [2,5,6,7]
c = [3,6,8,9]
# Count how many times each elements appear.
counter = Counter()
for l in [a,b,c]:
counter.update(l)
print(counter)
# If an element appears only once, it is an unique element !
for l in [a,b,c]:
print(*filter(lambda x: counter[x]==1, l))
And the output is:
Counter({2: 2, 3: 2, 6: 2, 1: 1, 4: 1, 5: 1, 7: 1, 8: 1, 9: 1})
1 4
5 7
8 9
Use
set.difference() - Return a set that contains the items that only exist in set x, and not in set y:
Ex.
a = [1,2,3,4]
b = [2,5,6,7]
c = [3,6,8,9]
abc = list(set(a).difference(b).difference(c))
bca = list(set(b).difference(c).difference(a))
cab = list(set(c).difference(a).difference(b))
print(abc)
print(bca)
print(cab)
O/P:
[1, 4]
[5, 7]
[8, 9]
You can use a dict that stores the number of times each number is seen and use that to generate a set that lists are compared against. With the dict it means that you don't then need to compare every new list to all other lists again (but duplicate_numbers will need to be redefined).
tracker_dict = dict()
duplicate_numbers = set()
a = [1,2,3,4]
b = [2,5,6,7]
c = [3,6,8,9]
# Get count of all numbers in all lists
all_lists = [a, b, c]
for l in all_lists:
for item in l:
tracker_dict[item] = tracker_dict.get(item, 0) + 1
# Store all duplicate numbers in a set
duplicate_numbers = set([num for num in tracker_dict if tracker_dict[num] > 1])
# Get new lists
new_a = [i for i in a if i not in duplicate_numbers]
# With a new list that is defined afterwards
d = [1, 4, 5, 1]
# Update the tracker_dict and duplicate_numbers set
for item in d:
tracker_dict[item] = tracker_dict.get(item, 0) + 1
duplicate_numbers = set([num for num in tracker_dict if tracker_dict[num] > 1])
new_d = [i for i in a if i not in duplicate_numbers]
# This does not affect previously processed lists however
What I want to do is to choose one item in list A and another one in list B, pair them like:
A[0]+B[n], A[1]+B[n-1],.....,A[n]+B[1]
I use two for loops but it doesn't work:
class Solution(object):
def plusOne(self, digits):
sum=0
for j in range(len(digits)-1,0,-1) :
for i in range(0,len(digits),1):
sum=sum+digits[i]*pow(10,j)
return sum+1
I inputted [1,2,3] and what I want to get is 124,
but I got 661.
Edit:
Sorry, the example I gave above is not so clear.
Let us think about A[1,2,3] and B[6,5,4].
I want output [5,7,9], because 5 is 1+4, 7 is 2+5, 9 is 3+6
What you are trying to do is turn a list of digits into the according number (and add 1). You can enumerate the reversed list in order to pair a digit with its appropriate power of 10:
digits = [1, 2, 3]
sum(10**i * y for i, y in enumerate(digits[::-1])) + 1
# 124
You can apply that to your other example as follows, using zip:
A = [1,2,3]
B = [6,5,4]
sum(10**i * (x+y) for i, (x, y) in enumerate(zip(B, A[::-1])))
# 579
You can do this without a loop:
A = [1,2,3]
B = [6,5,4]
C = list(map(sum,zip(A,B[::-1]) ))
print(C)
zip() - creates pairs of all elements of iterables, you feed it A and B reversed (via slicing). Then you sum up each pair and create a list from those sums.
map( function, iterable) - applies the function to each element of the iterable
zip() works when both list have the same length, else you would need to leverage itertools.zip_longest() with a defaultvalue of 0.
K = [1,2,3,4,5,6]
P = list(map(sum, zip_longest(K,C,fillvalue=0)))
print(P)
Output:
[5, 7, 9] # zip of 2 same length lists A and B reversed
[6, 9, 12, 4, 5, 6] # ziplongest for no matter what length lists
You only need one loop if you want to search in same list back and forth or different list with same length (i and len(lst)-1-i).
Try not use build-ins such as sum, list, tuple, str, int as variable names, it will give you some nasty result in some case.
class Solution(object):
def plusOne(self, digits):
sum_val = 0
for i in range(len(digits)):
sum_val += digits[i]*pow(10, len(digits)-1-i)
return sum_val+1
sol = Solution()
dig = [1, 2, 3]
print(sol.plusOne(dig))
Output:
124
for A = [1, 2, 3] and B = [6, 5, 4].
You can use a list comprehension:
res = [A[i]+B[len(A)-i-1] for i in range(len(A))]
Or the zip() function and a list comprehension:
res = [a+b for (a, b) in zip(A, reversed(B))]
Result:
[5, 7, 9]
I need to make a formula that, given two lists a and b, it returns the common elements in a and b. If the same element appears more than once in both, let's say xa times in a and xb times in b, then x should appear min(xa,xb) times in the results. If it's possible, don't use "import" in the code, please.
For example:
(Supposing my function is called common(a,b))
common([1,3,3,3],[1,3,3,3,3,4])
=> [1,3,3,3]
Thank you for your help!
A simple way is sort the two list first and compare the first element one by one. The code is like this:
def common(a, b):
sorted_a, sorted_b = sorted(a), sorted(b)
numa, numb = len(a), len(b)
rv = []
i, j = 0, 0
while i < numa and j < numb:
if sorted_a[i] == sorted_b[j]:
rv.append(sorted_a[i])
i += 1
j += 1
elif sorted_a[i] < sorted_b[j]:
i += 1
else:
j += 1
return rv
def common(lista=None,listb=None):
result_list=list()
inter_dict=dict()
lista_count=dict()
listb_count=dict()
for i in lista:
lista_count[i]=lista_count.get(i,0)+1 #convert lista to dict with frequency
for i in listb:
listb_count[i]=lista_count.get(i,0)+1 #convert listb to dict with frequency
for key in set(lista_count).intersection(set(listb_count)):
inter_dict[key]=min(lista_count[key],listb_count[key]) # get intersection of two dicts
for k,v in inter_dict.items():
result_list.extend([k]*v) #extend to the output list
return result_list
The output will give you when invoke the function common([1,3,3,3],[1,3,3,3,3,4]):
[1, 3, 3, 3]
def common(l1,l2):
totalElements = l1 + l2
resultList = []
for num in totalElements:
if num in l1 and num in l2:
resultList.append(num)
l1.remove(num)
l2.remove(num)
return resultList
l1 = [1,3,3,3,5]
l2 = [1,3,3,3,5,3,4]
result = common(l1 , l2)
print(result)
[1, 3, 3, 3, 5]
Three steps to resolve this problem:
Find out those elements should be in the final list, which is the intersection of two lists
For each element found in step #1, find out how many times it should be in final list
Generate final list based on the info found by previous two steps
And then translate these 3 steps to three lines of code:
def common(l1, l2):
intersection = [e for e in l1 if e in l2]
elemnts_counters = {e: min(l1.count(e), l2.count(e)) for e in intersection}
return sum([[e] * c for e, c in elemnts_counters.items()], [])
Then
print common([1,3,3,3], [1,3,3,3,3,4])
will give you:
[1, 3, 3, 3]
I have two lists of integers of equal length. I would like to add each element of the first list to its corresponding element of the second list using the line:
complete_list = [first_list[i] + second_list[i] for i in range(len(first_list))]
However, some elements of first_list are special numbers and I would like to exempt them from the above operation whilst having the other elements added to make complete_list. Thanks!
You can stick an if at the end of your listcomp:
>>> first_list = [1,2,3,10]
>>> second_list = [10,20,30,50]
>>> special = {2, 3}
>>> [first_list[i]+second_list[i] for i in range(len(first_list)) if first_list[i] not in special]
[11, 60]
Although I'd probably use zip here:
>>> [a+b for a,b in zip(first_list, second_list) if a not in special]
[11, 60]
If you want a to pass through unadjusted, you could move the if and use the X if Y else Z ternary syntax:
>>> [a+b if a not in special else a for a,b in zip(first_list, second_list)]
[11, 2, 3, 60]
I would tend to write your original example as:
a = [1, 2, 3]
b = [4, 5, 6]
from operator import add
c = map(add, a, b)
# [5, 7, 9]
Then, if you only want elements to "not add" depending on criteria on a, then build a generator over b referencing the corresponding element on a and make it 0 for a no-op.
special = {2}
b2 = (j if a[i] not in special else 0 for i, j in enumerate(b))
map(add, a, b2)
# [5, 2, 9]