I have a list that will consist of 1s and 0s. An example is: [1,1,1,1,1,0,1,0,1,0,0,0,0,0,1,1,1]
I am trying to print the number of times there were consecutive 1s. The desired output is 2. What I have so far:
def span(test_list):
res = []
for idx in range(0, len(test_list) - 1):
# getting Consecutive elements
if test_list[idx] == test_list[idx + 1]:
if test_list[idx]!=0:
res.append(test_list[idx])
# getting count of unique elements
res = len(list(set(res)))
# printing result
print("Consecutive identical elements count : " + str(res))
This however returns 1, where as I need the answer to be 2. Any help will be appreciated.
Just for fun... a solution using itertools.groupby:
test_list = [1,1,1,1,1,0,1,0,1,0,0,0,0,0,1,1,1]
sum(g[0] == 1 and len(g) > 1 for g in [list(g) for _, g in groupby(test_list)])
Output:
2
This works by grouping the consecutive identical values in the list which yields:
[1, 1, 1, 1, 1]
[0]
[1]
[0]
[1]
[0, 0, 0, 0, 0]
[1, 1, 1]
We then sum all the cases where the first element in the group is 1 and the length of the group is > 1.
#JonClements came up with an interesting way of doing this using itertools.islice which avoids the list conversion:
sum(next(islice(g, 1, None), 0) for k, g in groupby(test_list))
This works by taking a slice of the resultant group starting at the second element (islice(g, 1, None)) and then attempts to read that element (next(..., 0)) returning 0 if there isn't one. Thus next(islice(g, 1, None), 0) will only return 1 if the group is at least two 1's long.
Inspired by #JonClements' comment, I also came up with:
sum(next(g) & next(g, 0) for _, g in groupby(test_list))
This works by bitwise and'ing the first and second (or 0 if there isn't a second) elements in each grouped list, so only produces a 1 value if the grouped list contains more than one 1.
Timing wise, on my computer this is the fastest solution, with #JonClements about 20% slower and my original solution another 20% slower again.
Your problem here is that you are trying to add to your result list the sequences of consecutive ones, but there will be nothing to separate and distinguish the different sequences. So your result will look something like this:
[1,1,1,1,1,1]
Which will be reduce to just 1 when you convert it to a set.
My proposition is to track only the beginning of each consecutive sequence of ones, and to sum it like this:
def span(test_list):
res = []
started = False
for idx in range(0, len(test_list) - 1):
if test_list[idx] == test_list[idx + 1]:
if test_list[idx]!=0 and not started:
started = True
res.append(test_list[idx])
else:
started = False
res = sum(res)
print("Consecutive identical elements count : " + str(res))
test_liste = [1,1,1,1,1,0,1,0,1,0,0,0,0,0,1,1,1]
span(test_liste)
Why don't you use a counter that you increment each time list(n+1) == list(n)?
It will be easier than having to add each time an element to a list and then at the end to get the length of your list.
Apart from that, the problem you have is a logic problem. When you check that element n+1 is similar to your element n and that your element n is 1, you add only one element to your list (initially empty) while you checked that you had two similar elements.
My advice is to first check that the first element you read is a 1.
If it is not, then you go to the next one.
If it is, then you increment your counter by 1 and check the next one. If the next one is 1 then you increment your counter by 1. And so on.
What about it ? :
def span(test_list):
res = 0
for idx in range(0, len(test_list) - 1):
# check that you have two consecutive 1
if test_list[idx] == 1 and test_list[idx + 1] == 1:
res += 1;
# As long as the following values are 1, idx is incremented without incrementing res
while test_list[idx +1] == 1: //
idx += 1;
print("Consecutive identical elements count : " + str(res))
Related
First, I want to find the highest number in the list which is the second number in the list, then split it in two parts. The first part contains the 2nd highest number, while the second part contains the number from the list that sums to the highest number. Then, return the list
eg: input: [4,9,6,3,2], expected output:[4,6,3,6,3,2] 6+3 sums to 9 which is the highest number in the list
Please code it without itertools.
python
def length(s):
val=max(s)
s.remove(val)
for j in s:
if j + j == val:
s.append(j)
s.append(j)
return s
Here's what I have but it doesn't return what the description states.
Any help would be appreciated as I spent DAYS on this.
Thanks,
The main issue in your code seems to be that you are editing the list s whilst iterating through it, which can cause issues with the compiler and is generally just something you want to avoid doing in programming. A solution to this could be iterating through a copy of the original list.
The second problem is that your program doesn't actually find the second biggest value in the list, just a value which doubles to give you the biggest value.
The final problem (which I unfortunately only noticed after uploading what I thought was a solution) is that the split values are appended to the end of the list rather than to the position where originally the largest value was.
Hopefully this helps:
def length(array):
val = max(array)
idx = array.index(val) # gets the position of the highest value in the array (val)
array.remove(val)
for i in array.copy(): # creates a copy of the original list which we can iterate through without causing buggy behaviour
if max(array) + i == val:
array = array[:idx] + [max(array), i] + array[idx:]
# Redefines the list by placing inside of it: all values in the list upto the previous highest values, the 2 values we got from splitting the highest value, and all values which previously went after the highest value.
return array
This will return None if there is no value which can be added to the second highest value to get the highest value in the given array.
Input:
print(length([1,2,3,4,5]))
print(length([4,8,4,3,2]))
print(length([11,17,3,2,20]))
print(length([11,17,3,2,21]))
Output:
[1, 2, 3, 4, 4, 1]
[4, 4, 4, 4, 3, 2]
[11, 17, 3, 2, 17, 3]
None
Here are the docs on list slicing (which are impossible to understand) and a handy tutorial.
when you say "The first part contains the 2nd highest number" does that mean second highest number from the list or the larger of the two numbers that add up the largest number from list?
Here I assume you just wanted the larger of the two numbers that add up to the largest number to come first.
def length(s:list):
#start by finding the largest value and it's position in the list:
largest_pos = 0
for i in range(len(s)):
if s[i] > s[largest_pos]:
largest_pos = i
# find two numbers that add up to the largest number in the s
for trail in range(len(s)):
for lead in range(trail, len(s)):
if (s[trail] + s[lead]) == s[largest_pos]:
if s[trail] > s[lead]:
s[largest_pos] = s[trail]
s.insert(largest_pos +1, s[lead])
else:
s[largest_pos] = s[lead]
s.insert(largest_pos + 1, s[trail])
return s
# if no two numbers add up to the largest number. return s
return s
Since you are limited to 2 numbers, a simple nested loop works.
def length(s):
val = max(s)
idx = s.index(val)
s.remove(val)
for i in range(len(s) - 1):
for j in range(i + 1, len(s)):
if s[i] + s[j] == val:
s = s[:idx] + [s[i], s[j]] + s[idx:]
return s
print(length([4,9,6,3,2]))
Output:
[4, 6, 3, 6, 3, 2]
I used deque library
first to find the highest element or elements then remove all of them and replace them with second high value and rest like : 9 replace with 6 and 3 in example:
from collections import deque
l = [4, 9, 6, 3, 2]
a = deque(l)
e = a.copy()
s = max(a)
while s in a:
a.remove(s) # remove all highest elements
s2 = max(a) # find second high value
c = s - s2
for i in l:
if i == s:
w = e.index(i) # find index of high values
e.remove(max(e))
e.insert(w, s2)
e.insert(w+1, c)
print(list(e))
Let's say I want to get the the number of jumps of each consecutive 1's in a binary string of say, 169, which is 10101001.
The answer then it'd be 3, 2, 2 because when the algorithm starts at the most right digit of the binary number needs to move thrice to the left to reach the next 1, twice to get the next 1 and so on.
So the algorithm should have a counter that starts at 0, increments in one while finds 0's and reset each time it reaches a 1.
I need the output to be in form of a list using list comprehesion.
This is what I got so far:
number = 169
list = []
c = 1
for i in bin(number>>1)[:1:-1]:
if i == '1':
list.append(c)
c = 0
c += 1
The algorithm indeed works but the idea is to transform it into one line code using list compreshesion. I think that there should be one way to do it using enumerate().
Just like:
n = 169
list = [i for i, c in enumerate(bin(number>>1)[:1:-1], 1) if c == '1']
The problem is that the output will be [3, 5, 7] instead of [3, 2, 2] because the i (index variable) didn't reset.
I'm looking for an asnwer that isn't just straight list[a+1] - list[a] but more elegant and efficient solution.
Here's a one-liner for this problem that's most probably not readable.
s = "10101001"
result = [p - q for p, q in zip([index for index, a in enumerate(s[::-1]) if a == "1"][1:], [index for index, b in enumerate(s[::-1]) if b == "1"][:s.count("1")-1])]
You can use groupby here:
bs = "10101001"
result = [
sum(1 for _ in g) + 1 # this can also be something like len(list(g)) + 1
for k, g in groupby(reversed(bs))
if k == "0"
]
You cannot really do this easily with just the list comprehension, because what you want cannot be expressed with just mapping/filtering (in any straightforward way I can think of), but once you have a grouping iterator, it simply becomes suming the length of "0" runs.
you can easily do this with a regex pattern
import re
out = [len(i) for i in re.findall("0*1", num)]
output
print(out)
>>> [3, 2, 2]
t = [1, 2, 3]
def cumsum(t):
t2 = []
total = 0
i = 0
while i < len(t):
total += t[i]
t2[i].append(total)
i += 1
return t2
cumsum(t)
This code takes the sum of the first two list integers and appends it to another list.
I feel like this should logically work and I don't understand why it is producing an index error if i < len(t) when len(t)= 3. So ideally t2 =[1, 3, 6]
while the iterator is less than len(t) (which is 3) add the list item to the total variable then append the total to the new list then iterate.
Because you are using index i to access t2 list that is empty. To append an element to a list you should use <list>.append(<element>), that is t2.append(total) in your case.
I am trying to solve a problem where:
Given an array of n integers nums and a target, find the number of
index triplets i, j, k with 0 <= i < j < k < n that satisfy the
condition nums[i] + nums[j] + nums[k] < target.
For example, given nums = [-2, 0, 1, 3], and target = 2.
Return 2. Because there are two triplets which sums are less than 2:
[-2, 0, 1] [-2, 0, 3]
My algorithm: Remove a single element from the list, set target = target - number_1, search for doublets such that number_1 + number _2 < target - number_1. Problem solved.
The problem link is https://leetcode.com/problems/3sum-smaller/description/ .
My solution is:
def threeSumSmaller(nums, target):
"""
:type nums: List[int]
:type target: int
:rtype: int
"""
nums = sorted(nums)
smaller = 0
for i in range(len(nums)):
# Create temp array excluding a number
if i!=len(nums)-1:
temp = nums[:i] + nums[i+1:]
else:
temp = nums[:len(nums)-1]
# Sort the temp array and set new target to target - the excluded number
l, r = 0, len(temp) -1
t = target - nums[i]
while(l<r):
if temp[l] + temp[r] >= t:
r = r - 1
else:
smaller += 1
l = l + 1
return smaller
My solution fails:
Input:
[1,1,-2]
1
Output:
3
Expected:
1
I am not getting why is the error there as my solution passes more than 30 test cases.
Thanks for your help.
One main point is that when you sort the elements in the first line, you also lose the indexes. This means that, despite having found a triplet, you'll never be sure whether your (i, j, k) will satisfy condition 1, because those (i, j, k) do not come from the original list, but from the new one.
Additionally: everytime you pluck an element from the middle of the array, the remaining part of the array is also iterated (although in an irregular way, it still starts from the first of the remaining elements in tmp). This should not be the case! I'm expanding details:
The example iterates 3 times over the list (which is, again, sorted and thus you lose the true i, j, and k indexes):
First iteration (i = 0, tmp = [1, -2], t = 0).
When you sum temp[l] + temp[r] (l, r are 0, 1) it will be -1.
It satisfies being lower than t. smaller will increase.
The second iteration will be like the first, but with i = 1.
Again it will increase.
The third one will increase as well, because t = 3 and the sum will be 2 now.
So you'll count the value three times (despite only one tuple can be formed in order of indexes) because you are iterating through the permutations of indexes instead of combinations of them. So those two things you did not take care about:
Preserving indexes while sorting.
Ensuring you iterate the indexes in a forward-fashion only.
Try like this better:
def find(elements, upper_bound):
result = 0
for i in range(0, len(elements) - 2):
upper_bound2 = upper_bound - elements[i]
for j in range(i+1, len(elements) - 1):
upper_bound3 = upper_bound2 - elements[j]
for k in range(j+1, len(elements)):
upper_bound4 = upper_bound3 - elements[k]
if upper_bound4 > 0:
result += 1
return result
Seems like you're counting the same triplet more than once...
In the first iteration of the loop, you omit the first 1 in the list, and then increase smaller by 1. Then you omit the second 1 in the list and increase smaller again by 1. And finally you omit the third element in the list, -2, and of course increase smaller by 1, because -- well -- in all these three cases you were in fact considering the same triplet {1,1,-2}.
p.s. It seems like you care more about correctness than performance. In that case, consider maintaining a set of the solution triplets, to ensure you're not counting the same triplet twice.
There are already good answers , Apart that , If you want to check your algorithm result then you can take help of this in-built funtion :
import itertools
def find_(vector_,target):
result=[]
for i in itertools.combinations(vector_, r=3):
if sum(i)<target:
result.append(i)
return result
output:
print(find_([-2, 0, 1, 3],2))
output:
[(-2, 0, 1), (-2, 0, 3)]
if you want only count then:
print(len(find_([-2, 0, 1, 3],2)))
output:
2
I'd like to count how many times a big list contains elements in specific order. So for example if i have elements [1,2,3,4,5,1,2,3,4,5,1,2,3,4,5,1,2,3,4,5] and i'd like to know how many times [1,2,3] are next to each other (answer is 4 in this case).
I was thinking on checking the indexes of number '3' (so currently it'd return [2,7,12,17]. Then i would iterate over that list, take elements in positions described in the list and check two positions in front of it. If they match '1' and '2' then add 1 to counter and keep looking. I believe this solution isn't really efficient and does not look nice, would there be a better solution?
Here's a generalized solution that works for subsequences of any size and for elements of any type. It's also very space-efficient, as it only operates on iterators.
from itertools import islice
def count(lst, seq):
it = zip(*(islice(lst, i, None) for i in range(len(seq))))
seq = tuple(seq)
return sum(x == seq for x in it)
In [4]: count(l, (1, 2, 3))
Out[4]: 4
The idea is to create a sliding window iterator of width len(seq) over lst, and count the number of tuples equal to tuple(seq). This means that count also counts overlapping matches:
In [5]: count('aaa', 'aa')
Out[5]: 2
For lists of ints, you could convert to strings and then use the count method:
>>> x = [1,2,3,4,5,1,2,3,4,5,1,2,3,4,5,1,2,3,4,5]
>>> y = [1,2,3]
>>> s = ',' + ','.join(str(i) for i in x) + ','
>>> t = ',' + ','.join(str(i) for i in y) + ','
>>> s.count(t)
4
If the items in the list contained strings which contain commas, this method could fail (as #schwobaseggl points out in the comments). You would need to pick a delimiter known not to occur in any of the strings, or adopt an entirely different approach which doesn't reduce to the string count method.
On Edit: I added a fix suggested by #Rawing to address a bug pointed out by #tobias_k . This turns out to be a more subtle problem than it first seems.
x = [1,2,3,4,5,1,2,3,4,5,1,2,3,4,5,1,2,3,4,5]
y = [1,2,3]
count = 0
for i in range(len(x)-len(y)):
if x[i:i+len(y)] == y:
count += 1
print(count)
You could iterate the list and compare sublists:
In [1]: lst = [1,2,3,4,5,1,2,3,4,5,1,2,3,4,5,1,2,3,4,5]
In [2]: sub = [1,2,3]
In [3]: [i for i, _ in enumerate(lst) if lst[i:i+len(sub)] == sub]
Out[3]: [0, 5, 10, 15]
Note, however, that on a very large list and sublist, this is pretty wasteful, as it creates very many slices of the original list to compare against the sublist. In a slightly longer version, you could use all to compare each of the relevant positions of the list with those of the sublist:
In [5]: [i for i, _ in enumerate(lst) if all(lst[i+k] == e for k, e in enumerate(sub))]
Out[5]: [0, 5, 10, 15]
This strikes me as the longest common subsequence problem repeated every time until the sequence returned is an empty list.
I think that the best that you can do in this case for an efficient algorithm is O(n*m) where n is the number of elements in your big list and m is the number of elements in your small list. You of course would have to have an extra step of removing the small sequence from the big sequence and repeating the process.
Here's the algorithm:
Find lcs(bigList, smallList)
Remove the first occurrence of the smallList from the bigList
Repeat until lcs is an empty list
Return the number of iterations
Here is an implementation of lcs that I wrote in python:
def lcs(first, second):
results = dict()
return lcs_mem(first, second, results)
def lcs_mem(first, second, results):
key = ""
if first > second:
key = first + "," + second
else:
key = second + "," + first
if len(first) == 0 or len(second) == 0:
return ''
elif key in results:
return results[key]
elif first[-1] == second[-1]:
result = lcs(first[:-1], second[:-1]) + first[-1]
results[key] = result
return result
else:
lcsLeft = lcs(first[:-1], second)
lcsRight = lcs(first, second[:-1])
if len(lcsLeft) > len(lcsRight):
return lcsLeft
else:
return lcsRight
def main():
pass
if __name__ == '__main__':
main()
Feel free to modify it to the above algorithm.
One can define the efficiency of solution from the complexity. Search more about complexity of algorithm in google.
And in your case, complexity is 2n where n is number of elements.
Here is the solution with the complexity n, cause it traverses the list only once, i.e. n number of times.
def IsSameError(x,y):
if (len(x) != len(y)):
return False
i = 0
while (i < len(y)):
if(x[i] != y[i]):
return False
i += 1
return True
x = [1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5, 1, 2, 3, 4, 5]
y = [1, 2, 3]
xLength = len(x)
yLength = len(y)
cnt = 0
answer = []
while (cnt+3 < xLength):
if(IsSameError([x[cnt], x[cnt+1], x[cnt+2]], y)):
answer.append(x[cnt])
answer.append(x[cnt+1])
answer.append(x[cnt + 2])
cnt = cnt + 3
else:
cnt = cnt + 1
print answer