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Check if list contains alternating primes and perfect squares

I am just getting started in Python Programming. I had a problem on checking if a given list contains alternating sequence of primes and perfect squares. The list can start with either a prime or a perfect square. I came up with a solution but it's not efficient as it generates unwanted lists. Is this possible with more efficient Python code?
First I'm creating functions to generate a list of primes as well as perfect squares up to the max value of testing list. Functions squaretest() and primecheck():
def squaretest(num):
sqlist=[]
i=1
while i**2 <= num:
sqlist.append(i**2)
i+=1
return sqlist
def primecheck(num):
primelist=[]
for i in range(2,num + 1):
for p in range(2,i):
if (i % p) == 0:
break
else:
primelist.append(i)
return primelist
Then I am dividing the given list into lists of even index and odd index elements and checking all elements of them against the primelist and the squarelist:
def primesquare(l):
if len(l)==1:
primelist = primecheck(l[0])
sqlist = squaretest(l[0])
return (l[0] in primelist) or (l[0] in sqlist)
else:
ol=[]
el=[]
for i in range(0,len(l),2):
ol.append(l[i])
for p in range (1, len(l),2):
el.append(l[p])
primelist = primecheck(max(l))
sqlist = squaretest (max(l))
return((all(x in primelist for x in el)) == True and (all(y in sqlist for y in ol)) == True) or ((all(x in primelist for x in ol)) == True and (all(y in sqlist for y in el)) == True)
It works.
Any suggestions will be really helpful.

You can use sets to check if all members of a list are in another list.
def primesquare(l):
if len(l) == 0:
return True
primelist = set(primecheck(max(l)))
sqlist = set(squaretest(max(l)))
ol = set(l[::2])
el = set(l[1::2])
odds_are_primes = ol.issubset(primelist)
odds_are_squares = ol.issubset(sqlist)
evens_are_primes = el.issubset(primelist)
evens_are_squares = el.issubset(sqlist)
return (odds_are_primes and evens_are_squares) or (odds_are_squares and evens_are_primes)

I came up with a solution but it's not efficient as it generates
unwanted lists.
Assuming the unwanted lists are the two lists representing the even and odd elements, then we can fix that. (Eliminating the primes and squares list is a whole 'nother problem.) Below is my rework of your code -- we don't create addtional lists but rather with a couple of reusable ranges which are objects that produce integer sequences as needed, but not stored in memory.
Your any() design is efficient in that the arguments are generator expressions, not lists, which are computed as needed. As soon as a flaw is found in the array, the whole thing stops and returns False--it doesn't need to process the rest:
def squares(number):
return {x * x for x in range(int(number ** 0.5) + 1)}
def primes(number):
prime_set = set()
for i in range(2, number + 1):
for p in range(2, int(i ** 0.5) + 1):
if (i % p) == 0:
break
else: # no break
prime_set.add(i)
return prime_set
def primesquare(array):
if not array:
return True # define as the problem demands
length, maximum = len(array), max(array)
odd, even = range(0, length, 2), range(1, length, 2)
prime_set, square_set = primes(maximum), squares(maximum)
return all(array[i] in prime_set for i in even) and all(array[i] in square_set for i in odd) or all(array[i] in prime_set for i in odd) and all(array[i] in square_set for i in even)
I admire #AndreySemakin's set-based solution (+1), and use sets above, but his solution generates the same lists you want to eliminate (just in the form of sets).

I came up with this solution:
def primesquare(lst):
# checking if the first element is either perfect square or a prime
if not lst or (not checksquare(lst[0]) and not checkprime(lst[0])):
return False
length = len(lst)
if length == 1:
return True
if checksquare(lst[0]):
# if first element is square then make s(quare)=2 and p(rime)=1
s, p = 2, 1
else:
# if first element is prime then make s=1 and p=2
s, p = 1, 2
# running perfect square loop from s to len-1 with gap of 2 and checking condition
for i in range(s, length, 2):
if not checksquare(lst[i]):
return False
# running prime loop from p to len-1 with gap of 2
for i in range(p, length, 2):
if not checkprime(lst[i]):
return False
return True
def checksquare(n): # function to check perfect square
if n < 0:
return False
if 0 <= n <= 1:
return True
for i in range(int(n ** 0.5) + 1):
if i * i == n:
return True
return False
def checkprime(n): # function to check prime
if n < 2:
return False
if n % 2 == 0:
return n == 2
for i in range(3, int(n ** 0.5) + 1, 2):
if n % i == 0:
return False
return True

How to see if the list contains consecutive numbers

I want to test if a list contains consecutive integers and no repetition of numbers.
For example, if I have
l = [1, 3, 5, 2, 4, 6]
It should return True.
How should I check if the list contains up to n consecutive numbers without modifying the original list?
I thought about copying the list and removing each number that appears in the original list and if the list is empty then it will return True.
Is there a better way to do this?

For the whole list, it should just be as simple as
sorted(l) == list(range(min(l), max(l)+1))
This preserves the original list, but making a copy (and then sorting) may be expensive if your list is particularly long.
Note that in Python 2 you could simply use the below because range returned a list object. In 3.x and higher the function has been changed to return a range object, so an explicit conversion to list is needed before comparing to sorted(l)
sorted(l) == range(min(l), max(l)+1))
To check if n entries are consecutive and non-repeating, it gets a little more complicated:
def check(n, l):
subs = [l[i:i+n] for i in range(len(l)) if len(l[i:i+n]) == n]
return any([(sorted(sub) in range(min(l), max(l)+1)) for sub in subs])

The first code removes duplicates but keeps order:
from itertools import groupby, count
l = [1,2,4,5,2,1,5,6,5,3,5,5]
def remove_duplicates(values):
output = []
seen = set()
for value in values:
if value not in seen:
output.append(value)
seen.add(value)
return output
l = remove_duplicates(l) # output = [1, 2, 4, 5, 6, 3]
The next set is to identify which ones are in order, taken from here:
def as_range(iterable):
l = list(iterable)
if len(l) > 1:
return '{0}-{1}'.format(l[0], l[-1])
else:
return '{0}'.format(l[0])
l = ','.join(as_range(g) for _, g in groupby(l, key=lambda n, c=count(): n-next(c)))
l outputs as: 1-2,4-6,3
You can customize the functions depending on your output.

We can use known mathematics formula for checking consecutiveness,
Assuming min number always start from 1
sum of consecutive n numbers 1...n = n * (n+1) /2
def check_is_consecutive(l):
maximum = max(l)
if sum(l) == maximum * (maximum+1) /2 :
return True
return False

Once you verify that the list has no duplicates, just compute the sum of the integers between min(l) and max(l):
def check(l):
total = 0
minimum = float('+inf')
maximum = float('-inf')
seen = set()
for n in l:
if n in seen:
return False
seen.add(n)
if n < minimum:
minimum = n
if n > maximum:
maximum = n
total += n
if 2 * total != maximum * (maximum + 1) - minimum * (minimum - 1):
return False
return True

import numpy as np
import pandas as pd
(sum(np.diff(sorted(l)) == 1) >= n) & (all(pd.Series(l).value_counts() == 1))
We test both conditions, first by finding the iterative difference of the sorted list np.diff(sorted(l)) we can test if there are n consecutive integers. Lastly, we test if the value_counts() are all 1, indicating no repeats.

I split your query into two parts part A "list contains up to n consecutive numbers" this is the first line if len(l) != len(set(l)):
And part b, splits the list into possible shorter lists and checks if they are consecutive.
def example (l, n):
if len(l) != len(set(l)): # part a
return False
for i in range(0, len(l)-n+1): # part b
if l[i:i+3] == sorted(l[i:i+3]):
return True
return False
l = [1, 3, 5, 2, 4, 6]
print example(l, 3)

def solution(A):
counter = [0]*len(A)
limit = len(A)
for element in A:
if not 1 <= element <= limit:
return False
else:
if counter[element-1] != 0:
return False
else:
counter[element-1] = 1
return True

The input to this function is your list.This function returns False if the numbers are repeated.
The below code works even if the list does not start with 1.
def check_is_consecutive(l):
"""
sorts the list and
checks if the elements in the list are consecutive
This function does not handle any exceptions.
returns true if the list contains consecutive numbers, else False
"""
l = list(filter(None,l))
l = sorted(l)
if len(l) > 1:
maximum = l[-1]
minimum = l[0] - 1
if minimum == 0:
if sum(l) == (maximum * (maximum+1) /2):
return True
else:
return False
else:
if sum(l) == (maximum * (maximum+1) /2) - (minimum * (minimum+1) /2) :
return True
else:
return False
else:
return True

1.
l.sort()
2.
for i in range(0,len(l)-1)))
print(all((l[i+1]-l[i]==1)

list must be sorted!
lst = [9,10,11,12,13,14,15,16]
final = True if len( [ True for x in lst[:-1] for y in lst[1:] if x + 1 == y ] ) == len(lst[1:]) else False
i don't know how efficient this is but it should do the trick.

With sorting
In Python 3, I use this simple solution:
def check(lst):
lst = sorted(lst)
if lst:
return lst == list(range(lst[0], lst[-1] + 1))
else:
return True
Note that, after sorting the list, its minimum and maximum come for free as the first (lst[0]) and the last (lst[-1]) elements.
I'm returning True in case the argument is empty, but this decision is arbitrary. Choose whatever fits best your use case.
In this solution, we first sort the argument and then compare it with another list that we know that is consecutive and has no repetitions.
Without sorting
In one of the answers, the OP commented asking if it would be possible to do the same without sorting the list. This is interesting, and this is my solution:
def check(lst):
if lst:
r = range(min(lst), max(lst) + 1) # *r* is our reference
return (
len(lst) == len(r)
and all(map(lst.__contains__, r))
# alternative: all(x in lst for x in r)
# test if every element of the reference *r* is in *lst*
)
else:
return True
In this solution, we build a reference range r that is a consecutive (and thus non-repeating) sequence of ints. With this, our test is simple: first we check that lst has the correct number of elements (not more, which would indicate repetitions, nor less, which indicates gaps) by comparing it with the reference. Then we check that every element in our reference is also in lst (this is what all(map(lst.__contains__, r)) is doing: it iterates over r and tests if all of its elements are in lts).

l = [1, 3, 5, 2, 4, 6]
from itertools import chain
def check_if_consecutive_and_no_duplicates(my_list=None):
return all(
list(
chain.from_iterable(
[
[a + 1 in sorted(my_list) for a in sorted(my_list)[:-1]],
[sorted(my_list)[-2] + 1 in my_list],
[len(my_list) == len(set(my_list))],
]
)
)
)
Add 1 to any number in the list except for the last number(6) and check if the result is in the list. For the last number (6) which is the greatest one, pick the number before it(5) and add 1 and check if the result(6) is in the list.

Here is a really short easy solution without having to use any imports:
range = range(10)
L = [1,3,5,2,4,6]
L = sorted(L, key = lambda L:L)
range[(L[0]):(len(L)+L[0])] == L
>>True
This works for numerical lists of any length and detects duplicates.
Basically, you are creating a range your list could potentially be in, editing that range to match your list's criteria (length, starting value) and making a snapshot comparison. I came up with this for a card game I am coding where I need to detect straights/runs in a hand and it seems to work pretty well.

Does the sum exist in the given list [duplicate]

I am trying to write a function that will not only determine whether the sum of a subset of a set adds to a desired target number, but also to print the subset that is the solution.
Here is my code for finding whether a subset exists:
def subsetsum(array,num):
if num == 0 or num < 1:
return False
elif len(array) == 0:
return False
else:
if array[0] == num:
return True
else:
return subsetsum(array[1:],(num - array[0])) or subsetsum(array[1:],num)
How can I modify this to record the subset itself so that I can print it? Thanks in advance!

Based on your solution:
def subsetsum(array,num):
if num == 0 or num < 1:
return None
elif len(array) == 0:
return None
else:
if array[0] == num:
return [array[0]]
else:
with_v = subsetsum(array[1:],(num - array[0]))
if with_v:
return [array[0]] + with_v
else:
return subsetsum(array[1:],num)

Modification to also detect duplicates and further solutions when a match happened
def subset(array, num):
result = []
def find(arr, num, path=()):
if not arr:
return
if arr[0] == num:
result.append(path + (arr[0],))
else:
find(arr[1:], num - arr[0], path + (arr[0],))
find(arr[1:], num, path)
find(array, num)
return result

You could change your approach to do that more easily, something like:
def subsetsum(array, num):
if sum(array) == num:
return array
if len(array) > 1:
for subset in (array[:-1], array[1:]):
result = subsetsum(subset, num)
if result is not None:
return result
This will return either a valid subset or None.

Thought I'll throw another solution into the mix.
We can map each selection of a subset of the list to a (0-padded) binary number, where a 0 means not taking the member in the corresponsing position in the list, and 1 means taking it.
So masking [1, 2, 3, 4] with 0101 creates the sub-list [2, 4].
So, by generating all 0-padded binary numbers in the range between 0 and 2^LENGTH_OF_LIST, we can iterate all selections. If we use these sub-list selections as masks and sum the selection - we can know the answer.
This is how it's done:
#!/usr/bin/env python
# use a binary number (represented as string) as a mask
def mask(lst, m):
# pad number to create a valid selection mask
# according to definition in the solution laid out
m = m.zfill(len(lst))
return map(lambda x: x[0], filter(lambda x: x[1] != '0', zip(lst, m)))
def subset_sum(lst, target):
# there are 2^n binary numbers with length of the original list
for i in xrange(2**len(lst)):
# create the pick corresponsing to current number
pick = mask(lst, bin(i)[2:])
if sum(pick) == target:
return pick
return False
print subset_sum([1,2,3,4,5], 7)
Output:
[3, 4]
To return all possibilities we can use a generator instead (the only changes are in subset_sum, using yield instead of return and removing return False guard):
#!/usr/bin/env python
# use a binary number (represented as string) as a mask
def mask(lst, m):
# pad number to create a valid selection mask
# according to definition in the solution laid out
m = m.zfill(len(lst))
return map(lambda x: x[0], filter(lambda x: x[1] != '0', zip(lst, m)))
def subset_sum(lst, target):
# there are 2^n binary numbers with length of the original list
for i in xrange(2**len(lst)):
# create the pick corresponsing to current number
pick = mask(lst, bin(i)[2:])
if sum(pick) == target:
yield pick
# use 'list' to unpack the generator
print list(subset_sum([1,2,3,4,5], 7))
Output:
[[3, 4], [2, 5], [1, 2, 4]]
Note: While not padding the mask with zeros may work as well, as it will simply select members of the original list in a reverse order - I haven't checked it and didn't use it.
I didn't use it since it's less obvious (to me) what's going on with such trenary-like mask (1, 0 or nothing) and I rather have everything well defined.

Slightly updated the below code to return all possible combinations for this problem. Snippet in the thread above will not print all possible combinations when the input is given as subset([4,3,1],4)
def subset(array, num):
result = []
def find(arr, num, path=()):
if not arr:
return
if arr[0] == num:
result.append(path + (arr[0],))
else:
find(arr[1:], num - arr[0], path + (arr[0],))
find(arr[1:], num, path)
find(array, num)
return result

A bit different approach to print all subset through Recursion.
def subsetSumToK(arr,k):
if len(arr)==0:
if k == 0:
return [[]]
else:
return []
output=[]
if arr[0]<=k:
temp2=subsetSumToK(arr[1:],k-arr[0]) #Including the current element
if len(temp2)>0:
for i in range(len(temp2)):
temp2[i].insert(0,arr[0])
output.append(temp2[i])
temp1=subsetSumToK(arr[1:],k) #Excluding the current element
if len(temp1)>0:
for i in range(len(temp1)):
output.append(temp1[i])
return output
arr=[int(i) for i in input().split()]
k=int(input())
sub=subsetSumToK(arr,k)
for i in sub:
for j in range(len(i)):
if j==len(i)-1:
print(i[j])
else:
print(i[j],end=" ")

Rather than using recursion, you could use the iterative approach.
def desiredSum(array, sum):
numberOfItems = len(array)
storage = [[0 for x in range(sum + 1)] for x in range(numberOfItems + 1)]
for i in range(numberOfItems + 1):
for j in range(sum + 1):
value = array[i - 1]
if i is 0: storage[i][j] = 0
if j is 0: storage[i][j] = 1
if value <= j:
noTake = storage[i - 1][j]
take = storage[i - 1][j - value]
storage[i][j] = noTake + take
return storage[numberOfItems][sum]

A recursive function to sort a list of ints

I want to define a recursive function can sort any list of ints:
def sort_l(l):
if l==[]:
return []
else:
if len(l)==1:
return [l[-1]]
elif l[0]<l[1]:
return [l[0]]+sort_l(l[1:])
else:
return sort_l(l[1:])+[l[0]]
Calling this function on a list [3, 1, 2,4,7,5,6,9,8] should give me:
[1,2,3,4,5,6,7,8,9]
But I get:
print(sort_l([3, 1, 2,4,7,5,6,9,8]))--> [1, 2, 4, 5, 6, 8, 9, 7, 3]
Please help me to fix the problem, actual code would be appreciated. Thanks!

The quick sort is recursive and easy to implement in Python:
def quick_sort(l):
if len(l) <= 1:
return l
else:
return quick_sort([e for e in l[1:] if e <= l[0]]) + [l[0]] +\
quick_sort([e for e in l[1:] if e > l[0]])
will give:
>>> quick_sort([3, 1, 2, 4, 7, 5, 6, 9, 8])
[1, 2, 3, 4, 5, 6, 7, 8, 9]

For this you would want to use merge sort. Essentially in a merge sort you recursively split the list in half until you have single elements and than build it back up in the correct order. merge sort on has a complexity of O(n log(n)) and is an extremely stable sorting method.
Here are some good in depth explanations and visuals for merge sorting:
https://www.youtube.com/watch?v=vxENKlcs2Tw
http://www.princeton.edu/~achaney/tmve/wiki100k/docs/Merge_sort.html

def maximum(lis):
if len(lis) == 1:
return lis[0]
return maximum(lis[1:]) if lis[0] < lis[1] else maximum(lis[:1] + lis[2:])
def sorter(lis):
if len(lis) == 1:
return lis
x = maximum(lis)
lis.remove(x)
return sorter(lis) + [x]
with functional programming:
sor = lambda lis: lis if len(lis) == 1 else [lis.pop(lis.index(reduce(lambda x, y: x if x > y else y, lis)))] + sor(lis)

def quicksort(lst):
"Quicksort over a list-like sequence"
if len(lst) == 0:
return lst
pivot = lst[0]
pivots = [x for x in lst if x == pivot]
small = quicksort([x for x in lst if x < pivot])
large = quicksort([x for x in lst if x > pivot])
return small + pivots + large
Above is a more readable recursive implementation of Quick Sort Algorithm. Above piece of code is from book Functional programing in python by O'REILLY.
Above function will produce.
list=[9,8,7,6,5,4]
quicksort(list)
>>[4,5,6,7,8,9]

def sort(array, index = 0, bigNumber = 0):
if len(array) == index:
return array
elif bigNumber > array[index]:
array[index - 1] = array[index]
array[index] = bigNumber
bigNumber = array[0]
index = 0
else:
bigNumber = array[index]
return sort(array, (index + 1), bigNumber)

#sort an int list using recursion
global array
array=[5,3,8,4,2,6,1]
def sort1(array:[])->[]:
if len(array)==1:
return
temp=array[-1]
array.pop()
sort1(array)
sort2(array,temp)
def sort2(array:[],temp):
if len(array)==0 or temp>=array[-1]:
array.append(temp)
return
a=array[-1]
array.pop()
sort2(array,temp)
array.append(a)
sort1(array)
print(array)

Here i am explaining recursive approach to sort a list. we can follow "Induction Base-condition Hypothesis" recursion approach. so basically we consider our hypothesis here sort_l(nums) function which sorts for given list and Base condition will be found when we have singly number list available which is already sorted. Now in induction step, we insert the temp element (last element of list) in the correct position of given list.
example-
sort_l([1,5,0,2]) will make below recursively call
sort_l([1]) <-- 5 (here you need to insert 5 in correct position)
sort_l([1,5]) <-- 0 (here you need to insert 0 in correct position)
sort_l([0,1,5]) <-- 2 (here you need to insert 2 in correct position)
sort_l([0,1,5,2]) Finally it will be in sorted list.
====== Below is working code=======
def insert_element(nums, temp):
if len(nums) == 1:
if nums[0] > temp:
nums.insert(0, temp)
elif nums[0] < temp:
nums.append(temp)
else:
for i in range(len(nums)):
if nums[i] > temp:
nums.insert(i, temp)
break
if nums[-1] < temp:
nums.append(temp)
def sort_l(nums): ## hypothesis
if len(nums)==1: ## base condition
return nums
temp = nums[-1]
nums.pop()
sort_l(nums)
insert_element(nums, temp) ## induction
return nums

This is a complementary answer since both quicksort and complexity are already covered in previous answers. Although, I believe an easy-to-get sort function that covers Python's identity is missing*.
def sort(xs: list) -> list:
if not xs:
return xs
else:
xs.remove(num := min(xs))
return [num] + sort(xs)
[*] Python is a (slow) interpreted language, but it has become famous because of its readability and easiness to learn. It doesn't really "reward" its developers for using immutable objects nor it is a language that should be used for computation intensive applications

This is a recursive solution. For an explanation, refer to this video:
arr = [3,1,2,4,7,5,6,9,8]
def insert_fn(arr, temp): # Hypothesis
if len(arr) == 0 or arr[-1] <= temp: # Base - condition
arr.append(temp)
return arr
# Induction
val = arr[-1]
arr.pop()
insert_fn(arr, temp) # Call function on a smaller input.
arr.append(val) # Induction step
return arr
def sort_fn(arr): # Hypothesis
if len(arr) == 1: # Base - condition
return arr
# Induction
val = arr[-1]
arr.pop()
sort_fn(arr) # Call function on a smaller input.
insert_fn(arr, val) # Induction step
return arr
print(sort_fn(arr))

Divisible by 2: Python [duplicate]

This question already has answers here:
Python Homework - creating a new list
(6 answers)
Closed 9 years ago.
I am trying to write a function called splitList(myList, option) that takes a list and an option which is either 0 or 1 as parameters. If the value of the option is 0 the function returns a list consisting of the elements in myList that are negative and if the value of the option is 1 the function returns a list consisting of the elements in myList that are even (we consider 0 to be an even number, since it is evenly divisible by 2).
For example:
splitList([1,-3,5,7,-9,-11,0,2,-4], 0)
Would return the list:
[-3,-9,-11,-4]
Where as:
splitList([1,-3,5,7,-9,-11,0,2,-4], 1)
Would return the list:
[0,2,-4]
For this problem I must use a for loop.
Here is what I have:
def splitList(myList, option):
negativeValues = []
positiveValues = []
evenValues = []
for i in range(0,len(myList)):
if myList[i] < 0:
negativeValues.append(myList [i])
else:
positiveValues.append(myList [i])
for element in myList:
if option == 1:
myList [i] % 2 == 0
evenValues.append(myList [i])
return evenValues
else:
return negativeValues
The only thing I cannot get it to do is to is sort the list and return all the numbers that are divisible by 2.

Using a loop is a bit redundant here since there's a standard function filter that does what you want: returns a new list with these elements of a list which match a given predicate.
Let's define the predicates first:
def is_even(x):
return x % 2 == 0
def is_negative(x):
return x < 0
Then you can easily define your function in terms of filter:
def splitList(myList, option):
predicate = is_negative if option == 0 else is_even
return filter(predicate, myList)

You can build all your variants from these primitives:
def even_list(numbers):
return [x for x in numbers if not (x & 1)]
def odd_list(numbers):
return [x for x in numbers if x & 1]
def negative_list(numbers):
return [x for x in numbers if x < 0]
def positive_list(numbers):
return [x for x in numbers if x > 0]
Then test:
>>> def test():
... numbers = list(range(-3, 4))
... print even_list(numbers)
... print odd_list(numbers)
... print positive_list(numbers)
... print negative_list(numbers)
...
>>> test()
[-2, 0, 2]
[-3, -1, 1, 3]
[1, 2, 3]
[-3, -2, -1]
Later: so stealing from #Kos, you could write split_list like this:
def split_list(myList, option):
predicate = negative_list if not option else even_list
return predicate(myList)
Or:
def split_list(myList, option):
predicates = [negative_list, even_list]
return predicates[option](myList)
Not sure if it meets your needs if the for-loop is in a list comprehension in a called function.
Also: "Function names should be lowercase, with words separated by underscores as necessary to improve readability."

You return too soon. You first have to complete the foor loop and return after it, not from inside the loop.
Example
for i in range(5):
print i
numbers.append(i)
return numbers //wrong: exit the function on the first pass in the loop.
for i in range(5):
print i
numbers.append(i)
return numbers //right
Besides that why do you calculate the negative valuse list if you don't need it?

def splitList(myList,option):
negative_numbers = [i for i in myList if i < 0]
even_numbers = [i for i in myList if i % 2 == 0]
return sorted(even_numbers) if option else sorted(negative_numbers)

I believe this is what you where trying to achieve:
def splitList(myList,option):
result = []
if option == 0:
for item in myList:
if (item < 0):
result.append(item)
elif option == 1:
for item in myList:
if (item % 2 == 0):
result.append(item)
else:
return "Option Error"
return sorted(result)
print splitList([1,-3,5,7,-9,-11,0,2,-4], 0)
print splitList([1,-3,5,7,-9,-11,0,2,-4], 1)
print splitList([1,-3,5,7,-9,-11,0,2,-4], 2)
Outputs:
[-11, -9, -4, -3]
[-4, 0, 2]
Option Error