I am trying to generate a list that combines elements of two other lists, one is a value and one is not.
I've tried having two separate lists with and using the join function and append function to combine the two elements together at the certain stage.
To match the length of list d to list a I've used a while loop as a counter.
a=7*[1]
b=[1,2,3,4,5]
c=['a','b','c']
d=[]
The outcome i'm trying to achieve is such that:
list d becomes the length of list a
& is a combination of list b and list c
d=[1a,1b,1c,2a,2b,2c,3a]
Can think of a Naive solution for now
def create(bk, ck, len_required):
dk = []
for bitem in bk:
for citem in ck:
dk.append(str(bitem) + citem)
if len(dk) == len_required:
return dk
len_required = len(a)
b = [1, 2, 3, 4, 5]
c = ['a', 'b', 'c']
d = create(b, c, len_required)
result = [str(b[int(i / len(c)) % len(b)]) + str(c[i % len(c)]) for i in range(len(a))]
This iterates i from 0 to len(a) and concatenates b[int(i / len(c)) % len(b)] and c[i % len(c)] in the output.
You could do it with a list comprehension:
d = [str(v)+L for v in b*len(a) for L in c][:len(a)]
or, if you're allowed to use itertools:
from itertools import cycle
cycleA = cycle(str(v)+L for v in b for L in c)
d = [ next(cycleA) for _ in a ]
Related
I have list of lists such as :
my_list_of_list=[['A','B','C','E'],['A','B','C','E','F'],['D','G','A'],['X','Z'],['D','M'],['B','G'],['X','Z']]
as you can see, the list 1 and 2 share the most elements (4). So, I keep a list within my_list_of_list only if the 4 shared elements (A,B,C or E) are present within that list.
Here I then save within the list_shared_number[], only the lists 1,2,3 and 6 since the other does not contain (A,B,C or E).
Expected output:
print(list_shared_number)
[0,1,2,5]
Probably sub optimal because I need to iterate 3 times over lists but it's the expect result:
from itertools import combinations
from functools import reduce
common_elements = [set(i).intersection(j)
for i, j in combinations(my_list_of_list, r=2)]
common_element = reduce(lambda i, j: i if len(i) >= len(j) else j, common_elements)
list_shared_number = [idx for idx, l in enumerate(my_list_of_list)
if common_element.intersection(l)]
print(list_shared_number)
# Output
[0, 1, 2, 5]
Alternative with 2 iterations:
common_element = {}
for i, j in combinations(my_list_of_list, r=2):
c = set(i).intersection(j)
common_element = c if len(c) > len(common_element) else common_element
list_shared_number = [idx for idx, l in enumerate(my_list_of_list)
if common_element.intersection(l)]
print(list_shared_number)
# Output
[0, 1, 2, 5]
You can find shared elements by using list comprehension. Checking if index 0 and index 1:
share = [x for x in my_list_of_list[0] if x in my_list_of_list[1]]
print(share)
Assume j is each item so [j for j in x if j in share] can find shared inner elements. if the length of this array is more than 0 so it should include in the output.
So final code is like this:
share = [x for x in my_list_of_list[0] if x in my_list_of_list[1]]
my_list = [i for i, x in enumerate(my_list_of_list) if len([j for j in x if j in share]) > 0]
print(my_list)
You can use itertools.combinations and set operations.
In the first line, you find the intersection that is the longest among pairs of lists. In the second line, you iterate over my_list_of_list to identify the lists that contain elements from the set you found in the first line.
from itertools import combinations
comparison = max(map(lambda x: (len(set(x[0]).intersection(x[1])), set(x[0]).intersection(x[1])), combinations(my_list_of_list, 2)))[1]
out = [i for i, lst in enumerate(my_list_of_list) if comparison - set(lst) != comparison]
Output:
[0, 1, 2, 5]
Oh boy, so mine is a bit messy, however I did not use any imports AND I included the initial "finding" of the two lists which have the most in common with one another. This can easily be optimised but it does do exactly what you wanted.
my_list_of_list=[['A','B','C','E'],['A','B','C','E','F'],['D','G','A'],['X','Z'],['D','M'],['B','G'],['X','Z']]
my_list_of_list = list(map(set,my_list_of_list))
mostIntersects = [0, (None,)]
for i, IndSet in enumerate(my_list_of_list):
for j in range(i+1,len(my_list_of_list)):
intersects = len(IndSet.intersection(my_list_of_list[j]))
if intersects > mostIntersects[0]: mostIntersects = [intersects, (i,j)]
FinalIntersection = set(my_list_of_list[mostIntersects[1][0]]).intersection(my_list_of_list[mostIntersects[1][1]])
skipIndexes = set(mostIntersects[1])
for i,sub_list in enumerate(my_list_of_list):
[skipIndexes.add(i) for char in sub_list
if i not in skipIndexes and char in FinalIntersection]
print(*map(list,(mostIntersects, FinalIntersection, skipIndexes)), sep = '\n')
The print provides this :
[4, (0, 1)]
['E', 'C', 'B', 'A']
[0, 1, 2, 5]
This works by first converting the lists to sets using the map function (it has to be turned back into a list so i can use len and iterate properly) I then intersect each list with the others in the list of lists and count how many elements are in each. Each time i find one with a larger number, i set mostIntersections equal to the len and the set indexes. Once i go through them all, i get the lists at the two indexes (0 and 1 in this case) and intersect them to give a list of elements [A,B,C,E] (var:finalIntersection). From there, i just iterate over all lists which are not already being used and just check if any of the elements are found in finalIntersection. If one is, the index of the list is appended to skipIndexes. This results in the final list of indexes {indices? idk} that you were after. Technically the result is a set, but to convert it back you can just use list({0,1,2,5}) which will give you the value you were after.
I have N lists, and would like to know which elements are present in strictly X of those lists. I understand that if I have two lists, it's rather straightforward:
lst_a = [1,2,3]
lst_b = [1,2,5]
overlap = list(set(a) & set(b))
What if I have, say, 5 lists, and want to know which elements are in strictly 4 of those?
Merge using counters:
from collections import Counter
lst_a = [1,2,3]
lst_b = [1,2,5]
lsts = [lst_a, lst_b]
counter = Counter()
for lst in lsts:
unique = set(lst)
counter += Counter(unique)
n = 2
print(f"elements in exactly {n} lsts:")
for k, v in counter.items():
if v == n:
print(k)
Similar to #wim's code, but in a more concise manner:
[i for i, c in sum(map(Counter, lsts), Counter()).items() if c == 2]
If the items in the input lists are not unnecessarily unique you can map the lists to sets first:
[i for i, c in sum(map(Counter, map(set, lsts)), Counter()).items() if c == 2]
This returns:
[1, 2]
I am new to python and SO. I want to multiply each element of lists in a list of lists to another list lying in the same list of lists and compare it with a reference value. This will be more clear with an example:
for L = [[1,2,3,4,5,10],[3,2,4,1,5,10]] ##there can be more than 2 lists in this list of lists
I want only those pairs whose product results in 10.
Out: L = [[1,10],[2,5]]
Edit: I prefer a method without any imports, since I am doing this for building logic and my editor doesn't contain any modules to import. Also, if there are more than 2 lists in a list of lists For eg. there are 3 Lists in a list of lists: then I want triplets for that sake. ANd if 4 lists then I need quadruples.
Here's my code attempt as requested.
N = []
J = []
F = []
Z = []
S = []
O = []
num = input("Enter no. of elements in list")
print ('Enter numbers')
prod = 1
for i in range(int(num)):
n = input("num :")
N.append(int(n))
for x in N:
prod = prod*x
print (prod)
k = int(input("Enter no. of splits:"))
##d = [[] for x in xrange(k)]
##var_dict = []
for o in range(1,prod+1):
if prod%o == 0:
J.append(o)
print (J)
for g in range(k):
O.append(J*(k-1))
print (O)
for a in range(len(O)):
for b in range(len(O)):
if O[i]*O[i+1] == prod:
Z.extend(O)
##Z = [[a, b] for a in J for b in F if a*b == prod] ##imp
print (Z)
for e in Z:
if e not in S and sorted(e) not in S:
S.append(e)
print (S)
You can use itertools.product to find groups of numbers and filter them based on their product
>>> from itertools import product
>>> from functools import reduce
>>> lst = [[1,2,3,4,5,10],[3,2,4,1,5,10]]
>>> ans = [p for p in product(*lst) if reduce(lambda x,y:x*y, p) == 10]
>>> # Remove duplicates
>>> ans = list(map(list, set(map(frozenset, ans))))
>>> print (ans)
[[1, 10], [2, 5]]
>>>
In a comment you say you say you want code without any imports. Importing product from itertools and reduce do simplify and speed the code, but the job can be done without imports. Here is a recursive solution. I am not quite satisfied with this code but it seems to work and passes all my tests. I generalized the problem somewhat so that the input can have tuples or other sequences and not just lists.
def prod_is_target(seq_of_seqs, target):
"""Return a list of lists, where each sublist contains one member
of each input subsequence in order, and the product of those
members equals the target value. If there is no such list possible,
return None. If seq_of_seqs is empty, return an empty list if the
target is 1 and return None otherwise.
"""
if not seq_of_seqs: # if is empty sequence
return [] if target == 1 else None
result = []
for val in seq_of_seqs[0]:
if target % val: # skip if target is not a multiple of val
continue
prodlists = prod_is_target(seq_of_seqs[1:], target // val)
if prodlists is None: # skip if failed with later sublists
continue
if not prodlists: # if is empty list
result.append([val])
else:
for prodlist in prodlists:
result.append([val] + prodlist)
return result if result else None
print(prod_is_target([[1,2,3,4,5,10], [3,2,4,1,5,10]], 10))
The printout from that code is
[[1, 10], [2, 5], [5, 2], [10, 1]]
I'll leave it to you to remove what you consider to be duplicates. I can think of situations where you would want this full list, however.
Say I have a list of lists like so:
list = [[1,2,3,4],[4,5,3,2],[7,8,9,2],[5,6,8,9]]
I want to get the indices of the inner lists that contain unique elements. For the example above, the lists at index 2 is the only one that contains 7 and the list at index 3 is the only one that contains 6.
How would one go about implementing this in python?
Here's a solution using Counter. Each inner list is checked for a value that only has a single count, and then the corresponding index is printed (a la enumerate).
from collections import Counter
from itertools import chain
c = Counter(chain.from_iterable(l))
idx = [i for i, x in enumerate(l) if any(c[y] == 1 for y in x)]
print(idx)
[0, 2, 3]
A possible optimisation might include precomputing unique elements in a set to replace the any call with a set.intersection.
c = Counter(chain.from_iterable(l))
u = {k for k in c if c[k] == 1}
idx = [i for i, x in enumerate(l) if u.intersection(x)]
A naive solution:
>>> from collections import Counter
>>> from itertools import chain
>>> my_list = [[1,2,3,4],[4,5,3,2],[7,8,9,2],[5,6,8,9]]
# find out the counts.
>>> counter = Counter(chain(*my_list))
# find the unique numbers
>>> uniques = [element for element,count in counter.items() if count==1]
# find the index of those unique numbers
>>> result = [indx for indx,elements in enumerate(my_list) for e in uniques if e in elements]
>>> result
[0, 2, 3]
using itertools.chain with set.difference(set)
from itertools import chain
l = [[1,2,3,4],[4,5,3,2],[7,8,9,2],[5,6,8,9]]
[i for i in range(len(l)) if set(l[i]).difference(set(chain(*[j for j in l if j!=l[i]])))]
#[0, 2, 3]
I'm looking for a way to make a list containing list (a below) into a single list (b below) with 2 conditions:
The order of the new list (b) is based on the number of times the value has occurred in some of the lists in a.
A value can only appear once
Basically turn a into b:
a = [[1,2,3,4], [2,3,4], [4,5,6]]
# value 4 occurs 3 times in list a and gets first position
# value 2 occurs 2 times in list a and get second position and so on...
b = [4,2,3,1,5,6]
I figure one could do this with set and some list magic. But can't get my head around it when a can contain any number of list. The a list is created based on user input (I guess that it can contain between 1 - 20 list with up 200-300 items in each list).
My trying something along the line with [set(l) for l in a] but don't know how to perform set(l) & set(l).... to get all matched items.
Is possible without have a for loop iterating sublist count * items in sublist times?
I think this is probably the closest you're going to get:
from collections import defaultdict
d = defaultdict(int)
for sub in outer:
for val in sub:
d[val] += 1
print sorted(d.keys(), key=lambda k: d[k], reverse = True)
# Output: [4, 2, 3, 1, 5, 6]
There is an off chance that the order of elements that appear an identical number of times may be indeterminate - the output of d.keys() is not ordered.
import itertools
all_items = set(itertools.chain(*a))
b = sorted(all_items, key = lambda y: -sum(x.count(y) for x in a))
Try this -
a = [[1,2,3,4], [2,3,4], [4,5,6]]
s = set()
for l in a:
s.update(l)
print s
#set([1, 2, 3, 4, 5, 6])
b = list(s)
This will add each list to the set, which will give you a unique set of all elements in all the lists. If that is what you are after.
Edit. To preserve the order of elements in the original list, you can't use sets.
a = [[1,2,3,4], [2,3,4], [4,5,6]]
b = []
for l in a:
for i in l:
if not i in b:
b.append(i)
print b
#[1,2,3,4,5,6] - The same order as the set in this case, since thats the order they appear in the list
import itertools
from collections import defaultdict
def list_by_count(lists):
data_stream = itertools.chain.from_iterable(lists)
counts = defaultdict(int)
for item in data_stream:
counts[item] += 1
return [item for (item, count) in
sorted(counts.items(), key=lambda x: (-x[1], x[0]))]
Having the x[0] in the sort key ensures that items with the same count are in some kind of sequence as well.