List comprehension with for loop - python

How can I double the first n odd numbers in a list using list comprehension?
Here is my solution:
>>> n = 2
>>> lst = [1, 2, 3, 4, 5, 6]
>>> lst = [num for num in lst if num % 2 == 1] + [num for num in lst if num % 2 == 0]
>>> lst = [num * 2 for num in lst[:n]] + lst[n:]
>>> print(lst)
[2, 6, 5, 2, 4, 6]
You can see that I can't keep the same order of lst anymore...
More example:
n = 2
lst = [2, 2, 2, 2, 1, 2, 3]
output: lst = [2, 2, 2, 2, 2, 2, 6]

Solution for the original requirement to *“double the first n numbers in a list if it’s odd”:
Since you do not want to remove any items from your original list, you cannot use the filter of the list comprehension syntax (the if after the for). So what you need to do instead is simply transform the item you are putting into the target list.
Your logic is something like this for an element x at index i:
def transform(x, i, n):
if i < n:
if x % 2 == 1:
return x * 2
return x
So you can use that exact function and use it in your list comprehension:
>>> n = 2
>>> lst = [1, 2, 3, 4, 5, 6]
>>> [transform(x, i, n) for i, x in enumerate(lst)]
[2, 2, 3, 4, 5, 6]
And of course, you can put this also inline into the list comprehension:
>>> [x * 2 if i < n and x % 2 == 1 else x for i, x in enumerate(lst)]
[2, 2, 3, 4, 5, 6]
First n odd numbers:
If you want to find the first n odd numbers, you cannot solve this like this. In order to solve this, you need to actually remember how many odd numbers you encountered before while going through the list. This means that you need to have some kind of “memory”. Such a thing is not a good fit for a list comprehension since list comprehensions are supposed to transform one item at a time without having side effects.
So instead, you would simply do this the straightforward way:
n = 2
lst = [2, 2, 2, 2, 1, 2, 3]
result = []
for x in lst:
if x % 2 == 1 and n > 0:
result.append(x * 2)
n -= 1
else:
result.append(x)
print(result) # [2, 2, 2, 2, 2, 2, 6]

For this to work, you'll need to keep count of odd numbers that you've already seen. For example, you could instantiate the itertools.count generator and advance it each time the odd number is encountered:
from itertools import count
def f(l, n):
odd = count()
return [x * 2 if x % 2 and next(odd) < n else x for x in l]
>>> f([1, 2, 3, 4, 5, 6], 2)
[2, 2, 6, 4, 5, 6]
>>> f([2, 2, 2, 2, 1, 2, 3], 2)
[2, 2, 2, 2, 2, 2, 6]

Use the ternary operator.
lst = [1, 2, 3, 4, 5, 6]
lst = [x * 2 if x % 2 == 1 and i <= n else x for i, x in enumerate(lst)]
or
lst[:n] = [x * 2 if x % 2 == 1 else x for x in lst[:n]]
Update: Under the new requirement of doubling first n odd integers:
lst = [1, 2, 3, 4, 5, 6]
class Doubler:
def __init__(self, n):
self.n = n
def proc(self, x):
if self.n > 0 and x % 2:
self.n -= 1
return 2 * x
return x
# Double first 2 odd elements
d = Doubler(n=2)
res = [d.proc(x) for x in lst]
print(res)
# [2, 2, 6, 4, 5, 6]

Name things with specificity, and the logic is exposed.
How can I double the first n odd numbers in a list using list comprehension?
We have odd numbers: v for v in l if n%2. This is a filter.
We can take the first n of them using islice(odds, n). We call this a slice, other languages might call it "take". And doubling them is a per item operation, so a map. Join these operations and we arrive at one answer to your question:
[v*2 for v in islice((v for v in l if n%2), n)]
However, that isn't what you wanted. The issue is specificity; your question doesn't say what to do with other items than the first n odd ones, so I have just ignored them.
So what do do if we want a replication of all the items your question did not mention? This means we have three groups: early odds, late odds, and evens, all processed distinctly. The latter may be mixed in arbitrarily, while we know late odds come after early odds. It's impractical to split them in individual streams, as you've shown, since that doesn't preserve their relative order.
I'll apply a few more itertools functions to solve this problem.
from itertools import repeat, chain
oddfactors = chain(repeat(2, n), repeat(1))
outlist = [v*next(oddfactors) if v%2 else v
for v in inlist]
Note that the iterator oddfactors is read for each odd item, not even items, because the if-else expression doesn't evaluate the expression if it's not being used. The iterator is consumed and you need to create another to perform the work again.
It is possible to place the oddfactors iterator's creation (and entire scope) within the list comprehension, but the first way I can think of is incredibly ugly:
from itertools import repeat, chain
outlist = [v*next(oddfactors) if v%2 else v
for v,oddfactors in zip(
inlist,
repeat(chain(repeat(2, n), repeat(1)))
)]
The trick here is to ensure we create the chained iterator only once, then feed it into each mapping operation. This exercise sure didn't help readability or performance. Using a nested comprehension would make it a bit cleaner but there's still only the one iterator, so it's a misleading hack.
outlist = [v*next(oddfactors) if v%2 else v
for oddfactors in [chain(repeat(2, n), repeat(1))]
for v in inlist]

How about this?
n = 2
lst = [1, 2, 3, 4, 5, 6]
for i in range(n):
lst[i]= lst[i]*2

[num if num%2 else 2*num for num in list]. num if a if b else c will return a if b is true, otherwise c.

Related

Python: Replace duplicate values in a list with the same values

I have a list and would like to convert all duplicates values to 3 without changing the order and without importing any packages
X = [1, 2, 2, 5, 4, 8, 6]
Desired output:
X = [1, 3, 3, 5, 4, 8, 6]
This code automatically replace all duplicate items with 3
my_list = [1, 2, 2, 5, 4, 8, 6]
new = []
for item in my_list:
if my_list.count(item) > 1:
new.append(3)
else:
new.append(item)
print(new)
Among the fastest
fr = {x:0 for x in X}
for n in X:
fr[n] += 1
Y = [3 if fr[n]>1 else n for n in X]
You iterate over the list and add one to the dictionary counter for that number.
Then you create a list with list comprehension: you change the value to 3 if it is repeated more than once.
Little bit slower and little bit shorter
xi = {x:i for i, x in enumerate(X)}
dp = {x: xi[x]>i for i, x in reversed(list(enumerate(X)))}
Y = [3 if dp[x] else x for x in X]
You iterate over X and keep the lastest index of each value. Then you iterate again but in reverse order, and ask if there is another index for that value. Then with that info you create the desired output. All using list/dict comprehension. This is more of a functional approach.
Not sure why another user deleted their answer but that was a pretty simple one and uses basic list comprehension. So I am bringing the same to you. Please refer the code below for same:
X = [1, 2, 2, 5, 4, 8, 6]
print([3 if e==2 else e for e in X])
You should be able to use a for loop for this
my_list = [1, 2, 2, 5, 4, 8, 6]
new_list = []
for i in range(len(my_list)):
if my_list[i] in new_list:
new_list.append(3)
else:
new_list.append(my_list[i])
print(new_list)
Output:
[1, 3, 3, 5, 4, 8, 6]
Maybe something like this:
X = [t if t not in X[:i] + X[i+1:] else 3 for i, t in enumerate(X)]

Combining array elements in a particular way, and recording it

I am given a 1D array of numbers.
I need to go through the array adding each consecutive element to form a sum. Once this sum reaches a certain value, it forms the first element of a new array. The sum is then reset and the process repeats, thus iterating over the whole array.
For example if given:
[1, 3, 4, 5, 2, 5, 3]
and requiring the minimum sum to be 5,
the new array would be:
[8, 5, 7]
Explicity: [1 + 3 + 4, 5, 2 + 5]
I then also need to keep a record of the way the elements were combined for that particular array: I need to be to take a different array of the same length and combine the elements in the same way as above.
e.g. give the array
[1, 2, 1, 1, 3, 2, 1]
I require the output
[4, 1, 5]
Explicity: [1 + 2 + 1, 1, 3 + 2]
I have accomplished this with i loops and increment counters, but it is very ugly. The array named "record" contains the number of old elements summed to make each element of the new array i.e. [3, 1, 2]
import numpy as np
def bin(array, min_sum):
num_points = len(array)
# Create empty output.
output = list()
record = list()
i = 0
while i < num_points:
sum = 0
j = 0
while sum < min_sum:
# Break out if it reaches end of data whilst in loop.
if i+j == num_points:
break
sum += array[i+j]
j += 1
output.append(sum)
record.append(j)
i += j
# The final data point does not reach the min sum.
del output[-1]
return output
if __name__ == "__main__":
array = [1, 3, 4, 5, 2, 5, 3]
print bin(array, 5)
I would advice you to simply walk through the list. Add it to an accumulator like the_sum (do not use sum, since it is a builtin), and in case the_sum reaches a number higher than the min_sum, you add it, and reset the_sum to zero. Like:
def bin(array, min_sum):
result = []
the_sum = 0
for elem in array:
the_sum += elem
if the_sum >= min_sum:
result.append(the_sum)
the_sum = 0
return result
The lines where the accumulator is involved, are put in boldface.
I leave combining the other array the same way as an exercise, but as a hint: use an additional accumulator and zip to iterate over both arrays concurrently.
Here is a straightforward solution. which computes a list of boolean values where the value is true when accumulated element equals or exceeds the target value and calc computes an accumulation using this list.
def which(l, s):
w, a = [], 0
for e in l:
a += e
c = (a >= s)
w.append(c)
if c:
a = 0
return w
def calc(l, w):
a = 0
for (e, c) in zip(l, w):
a += e
if c:
yield a
a = 0
here is an interactive demonstration
>>> l1 = [1, 3, 4, 5, 2, 5, 3]
>>> w = which(l1, 5)
>>> w
[False, False, True, True, False, True, False]
>>> list(calc(l1, w))
[8, 5, 7]
>>> l2 = [1, 2, 1, 1, 3, 2, 1]
>>> list(calc(l2, w))
[4, 1, 5]
You can use short solutions I found out after a long struggle with flattening arrays.
For getting bounded sums use:
f = lambda a,x,j,l: 0 if j>=l else [a[i] for i in range(j,l) if sum(a[j:i])<x]
This outputs:
>>> f = lambda a,x,j,l: 0 if j>=l else [a[i] for i in range(j,l) if sum(a[j:i])< x]
>>> a= [1, 3, 4, 5, 2, 5, 3]
>>> f(a,5,0,7)
[1, 3, 4]
>>> sum(f(a,5,0,7))
8
>>> sum(f(a,5,3,7))
5
>>> sum(f(a,5,4,7))
7
>>>
To get your records use the function:
>>> y = lambda a,x,f,j,l: [] if j>=l else list(np.append(j,np.array(y(a,x,f,j+len(f(a,x,j,l)),l))))
From here, you can get both array of records and sums:
>>> listt=y(a,5,f,0,len(a))
>>> listt
[0.0, 3.0, 4.0, 6.0]
>>> [sum(f(a,5,int(listt[u]),len(a))) for u in range(0,len(listt)-1)]
[8, 5, 7]
>>>
Now, the bit of magic you can even use it as an index-conditional boundary for the second vector:
>>> b=[1, 2, 1, 1, 3, 2, 1]
>>> [sum(f(b,5,int(listt[u]),int(listt[u+1]))) for u in range(0,len(listt)-1)]
[4, 1, 5]
>>>

Rotating a list without using collection.deque

I want to make a script. The program should get some list L with values, and natural number N.
If N>0, the list's objects move N steps to left.
If N<0, the list's objects move abs(N) to the right.
If N=0 the list remain the same...
For example: For N=1 and L=[1,2,3,4,5], the output is [2,3,4,5,1].
For same list and N=-1 the output is [5,1,2,3,4]
I actually did it using collection.deque, but I want to do this with nothing but lists, for loop and 'if'.
I have problem to understand how to make the objects move.
l = input("enter list:")
N = input("enter number of rotations:")
import collections
d = collections.deque(l)
d.rotate(-N)
print d
You can use list slicing:
def rotate(L, N):
if not L or N % len(L) == 0:
return L
return L[N % len(L):] + L[:N % len(L)]
L = [1, 2, 3, 4, 5]
for N in range(-3, 4):
print(rotate(L, N))
Output:
[3, 4, 5, 1, 2]
[4, 5, 1, 2, 3]
[5, 1, 2, 3, 4]
[1, 2, 3, 4, 5]
[2, 3, 4, 5, 1]
[3, 4, 5, 1, 2]
[4, 5, 1, 2, 3]
Note that if you use a list, the time complexity of a rotation is linear to the number of elements in the list in general, since you have to move all existing elements. deque.rotate(), on the other hand, is O(k), with k being the number of steps. Therefore, if you need to rotate more than once deque.rotate() is the way to go.
This works:
result = l[N % len(l):]+l[:N % len(l)]
If using numpy is an option for you, there is a method called roll, which you might want to have a look at:
import numpy as np
array = np.arange(1, 6) # 1 to 5
print array
print np.roll(array, 0)
print np.roll(array, 2)
print np.roll(array, -2)
print np.roll(array, 17)
The result is as expected:
[1 2 3 4 5]
[1 2 3 4 5]
[4 5 1 2 3]
[3 4 5 1 2]
[4 5 1 2 3]
If you're after simple lists here's how you can do it in Python 3 (based on your P2 example).
L = list(map(int, input("Enter numbers: ").split(" ")))
N = int(input("Enter how many rotations to perform: "))
print(L[N:] + L[:N])
If you don't want to create new list, you can try in-place reverse,
def reverse(nums, start, end):
i = start
j = end - 1
while i < j:
tmp = nums[i]
nums[i] = nums[j]
nums[j] = tmp
i += 1
j -= 1
def rotate(nums, n):
if n == 0:
return nums
length = len(nums)
if n < 0:
n = length + n
reverse(nums, 0, n)
reverse(nums, n, length)
reverse(nums, 0, length)
return nums
>>> rotate([1, 2, 3, 4, 5], 1)
[2, 3, 4, 5, 1]
>>> rotate([1, 2, 3, 4, 5], -1)
[5, 1, 2, 3, 4]
thank you all ! :)
your answers are great and very useful for me.
here is my solution for this question (given that I do these scripts for a basic python course for biologists):
L = input('Enter list of numbers, please: ')
N = input('Enter how many places to rotate: ')
L1 = L[N:]
L2 = L[:N]
L = L1 + L2
print L

How to add two nested lists in parallel and append result to a new list in python

I'm trying to add all the elements of two unequal nested lists in parallel and append the result back to another new list, i've written a little hacky code that could add them but there's a lot of things wrong with the code, first i tried to make the pairs equal by appending 0's to the end of the list but the code still runs into the problems since the length of the first pair is 3 and the length of the second pair is 4, i also tried using map but i couldn't add an integer and a NoneType,
import pdb
import itertools
x = [[2,3,3], [5,0,3]]
y = [[0,3], [2,3,3,3]]
for idx, (a, b) in enumerate(itertools.zip_longest(x, y)):
while len(a) < len(b):
x[idx].append(0)
while len(b) < len(a):
y[idx].append(0)
print(x, y)
new_list = list()
for i in zip(x, y):
for idx, j in enumerate(i):
for ind, a in enumerate(j):
val = x[idx][ind] + y[idx][ind]
new_list.append(val)
print(new_list)
the final result should be like this
[2, 6, 3, 7, 3, 6, 3]
You can simply use itertools.zip_longest and fill-in with 0, like this
>>> from itertools import zip_longest as zip
>>> x = [[2, 3, 3], [5, 0, 3]]
>>> y = [[0, 3], [2, 3, 3, 3]]
>>> [k + l for i, j in zip(x, y, fillvalue=[0]) for k, l in zip(i, j, fillvalue=0)]
[2, 6, 3, 7, 3, 6, 3]
This would would work even if x and y have unequal number of elements,
>>> from itertools import zip_longest as zip
>>> x = [[2, 3, 3], [5, 0, 3], [1]]
>>> y = [[0, 3], [2, 3, 3, 3]]
>>> [k + l for i, j in zip(x, y, fillvalue=[0]) for k, l in zip(i, j, fillvalue=0)]
[2, 6, 3, 7, 3, 6, 3, 1]
Note that, when we zip x and y, we use [0] as fillvalue. And when we zip i and j we use 0 as the fillvalue.
So, if the number of lists in x and y are not equal, then [0] will be used fill-in and when the number of elements in i and j are not equal, 0 will be used as the fill-in.
You can use fillvalue=0 in izip_longest to get ride of checking for validations then use map function for sum the zipped items:
from itertools import chain,zip_longest
list(chain.from_iterable(map(sum,zip_longest(i,j,fillvalue=0)) for i,j in zip_longest(x, y)))
[2, 6, 3, 7, 3, 6, 3]
Note that if you want to iterate over the result you don't have to use list (its just for demonstrating the result).
zip_longest is very helpful here:
x = [[2,3,3], [5,0,3]]
y = [[0,3], [2,3,3,3]]
from itertools import zip_longest
res = []
for list1, list2 in zip_longest(x, y, fillvalue=[0]):
for value1, value2 in zip_longest(list1, list2, fillvalue=0):
res.append(value1 + value2)
The fill value pads the list or sublist with the given value. In our case a new list with [0] for the outer loop and 0 for the inner loop.
Writing this a nested list comprehension does the same but may take more time to read and understand the code. Using more lines can make reading and understanding faster. Of course, this depends very much on the person reading the code.
from itertools import zip_longest
new_list = [a + b
for listpair in zip(x, y)
for a, b in zip_longest(*listpair, fillvalue=0)]

Python weave lists

I want to "weave" two numberrows together.
Example:
x = [1,2,3]
y = [4,5,6]
result = [1,4,2,5,3,6]
This is my function, I can't find out why it doesn't work:
def weave(list1,list2):
lijst = []
i = 0
for i <= len(list1):
lijst += [list1[i]]
lijst += [list2[i]]
i + 1
You can use the chain function from itertools module to interleave two lists:
x = [1,2,3]
y = [4,5,6]
from itertools import chain
list(chain.from_iterable(zip(x, y)))
# [1, 4, 2, 5, 3, 6]
Python's for-loops aren't like other languages where you can have a conditional. You need to use a while loop instead or alter your for-loop:
def weave(list1,list2):
lijst = []
i = 0
while i < len(list1):
lijst.append(list1[i])
lijst.append(list2[i])
i += 1
return lijst
I've altered your code in a variety of ways:
Use a while loop if you have a condition you want to loop through
You want the conditional to be less than the length, not less than or equal to. This is because indexing starts at 0, and if you do <=, then it will try to do list1[3] which is out of bounds.
Use list.append to add items to list
You forgot the = in i += 1
Finally, don't forget to return the list!
You could also use zip():
>>> [a for b in zip(x, y) for a in b]
[1, 4, 2, 5, 3, 6]
You can also weave lists by defining the even and odd half-lists of the result list.
x = [1,2,3]
y = [4,5,6]
z = numpy.empty(len(x)+len(y))
z[::2],z[1::2]=x,y
result=z.tolist()
You need to append list item at every iteration so use list.append and in python you don't need to initialise i =0.
try this:-
>>> a = [1,2 ,3]
>>> b = [4, 5, 6]
>>> list(chain.from_iterable(zip(a, b)))
[1, 4, 2, 5, 3, 6]
You can play with this script:
reduce(lambda a, b: a+b, zip([1, 2, 3], [4, 5, 6]), ())
Notes:
zip will make pairs, add will join them;
you can use operator.add instead of lambda;
itertools.izip can be used if lengths of lists are different.
>>> x = [1,2,3]
>>> y = [4,5,6]
>>> z=[]
>>> for i,j in zip(x,y):
... z.extend([i,j])
...
>>> z
[1, 4, 2, 5, 3, 6]
I needed this, but with an arbitrary number of lists of potentially different lengths, which some of the other more elegant answers do not offer. Here is a simple implementation with no dependencies:
def weave_lists(list_of_lists):
max_index = max([len(sublist) for sublist in list_of_lists])
weaved_list = []
for sublist_index in range(max_index):
for sublist in list_of_lists:
if len(sublist) > sublist_index:
weaved_list.append(sublist[sublist_index])
return weaved_list
print(weave_lists([[1,2], [3,4,5], [6,7,8,9]]))
# [1, 3, 6, 2, 4, 7, 5, 8, 9]
x = [1,2,3]
y = [4,5,6]
As mentioned by others (and is the clearest as well as the way I'd do it since it since its the most understandable given the semantics of chain), You can do this by using itertools:
from itertools import chain
list(chain.from_iterable(zip(x, y)))
[1, 4, 2, 5, 3, 6]
However you could also use tuple summing up (concatenation) by:
list(sum(zip(x,y), ()))
[1, 4, 2, 5, 3, 6]

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