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Python: using range of indexes of an array in conditions

Python newbie here.
Let's say we have an array which contains 10 random integers.
I want to check if each value of the integers is 0<= x <= 9.
So for example somehow like this:
if 0 <= n[:11] <=9:
print('correct')
'n[:10]' is treated like a list so I can't compare it with 0 and 9.
Is there an elegant way to check the range of items in that array?
I don't want to code something like:
if 0 <= n[0] and n[1] and ... n[9] <=9:
thanks for your help

Check this out:
This returns True if and only if ALL of the numbers in the list n are at least 0 and at most 9, (in range(0, 10))
all(i in range(0, 10) for i in n)

if 0 <= min(n) <= max(n) <= 9:
Could use and instead of <= in the middle, not sure which I like better.

What you want is the check the equality for every elements:
all(0 <= item <= 9 for item in n)

If you first sort the list you only have to check the first and last value, like this:
sorted_n = sorted(n)
if sorted_n[0] > 0 and sorted_n[-1] < 10: # returns True or False for whole list

Python code for printing out the second largest number number given a list [duplicate]

I'm learning Python and the simple ways to handle lists is presented as an advantage. Sometimes it is, but look at this:
>>> numbers = [20,67,3,2.6,7,74,2.8,90.8,52.8,4,3,2,5,7]
>>> numbers.remove(max(numbers))
>>> max(numbers)
74
A very easy, quick way of obtaining the second largest number from a list. Except that the easy list processing helps write a program that runs through the list twice over, to find the largest and then the 2nd largest. It's also destructive - I need two copies of the data if I wanted to keep the original. We need:
>>> numbers = [20,67,3,2.6,7,74,2.8,90.8,52.8,4,3,2,5,7]
>>> if numbers[0]>numbers[1]):
... m, m2 = numbers[0], numbers[1]
... else:
... m, m2 = numbers[1], numbers[0]
...
>>> for x in numbers[2:]:
... if x>m2:
... if x>m:
... m2, m = m, x
... else:
... m2 = x
...
>>> m2
74
Which runs through the list just once, but isn't terse and clear like the previous solution.
So: is there a way, in cases like this, to have both? The clarity of the first version, but the single run through of the second?

You could use the heapq module:
>>> el = [20,67,3,2.6,7,74,2.8,90.8,52.8,4,3,2,5,7]
>>> import heapq
>>> heapq.nlargest(2, el)
[90.8, 74]
And go from there...

Since #OscarLopez and I have different opinions on what the second largest means, I'll post the code according to my interpretation and in line with the first algorithm provided by the questioner.
def second_largest(numbers):
count = 0
m1 = m2 = float('-inf')
for x in numbers:
count += 1
if x > m2:
if x >= m1:
m1, m2 = x, m1
else:
m2 = x
return m2 if count >= 2 else None
(Note: Negative infinity is used here instead of None since None has different sorting behavior in Python 2 and 3 – see Python - Find second smallest number; a check for the number of elements in numbers makes sure that negative infinity won't be returned when the actual answer is undefined.)
If the maximum occurs multiple times, it may be the second largest as well. Another thing about this approach is that it works correctly if there are less than two elements; then there is no second largest.
Running the same tests:
second_largest([20,67,3,2.6,7,74,2.8,90.8,52.8,4,3,2,5,7])
=> 74
second_largest([1,1,1,1,1,2])
=> 1
second_largest([2,2,2,2,2,1])
=> 2
second_largest([10,7,10])
=> 10
second_largest([1,1,1,1,1,1])
=> 1
second_largest([1])
=> None
second_largest([])
=> None
Update
I restructured the conditionals to drastically improve performance; almost by a 100% in my testing on random numbers. The reason for this is that in the original version, the elif was always evaluated in the likely event that the next number is not the largest in the list. In other words, for practically every number in the list, two comparisons were made, whereas one comparison mostly suffices – if the number is not larger than the second largest, it's not larger than the largest either.

You could always use sorted
>>> sorted(numbers)[-2]
74

Try the solution below, it's O(n) and it will store and return the second greatest number in the second variable. UPDATE: I've adjusted the code to work with Python 3, because now arithmetic comparisons against None are invalid.
Notice that if all elements in numbers are equal, or if numbers is empty or if it contains a single element, the variable second will end up with a value of None - this is correct, as in those cases there isn't a "second greatest" element.
Beware: this finds the "second maximum" value, if there's more than one value that is "first maximum", they will all be treated as the same maximum - in my definition, in a list such as this: [10, 7, 10] the correct answer is 7.
def second_largest(numbers):
minimum = float('-inf')
first, second = minimum, minimum
for n in numbers:
if n > first:
first, second = n, first
elif first > n > second:
second = n
return second if second != minimum else None
Here are some tests:
second_largest([20, 67, 3, 2.6, 7, 74, 2.8, 90.8, 52.8, 4, 3, 2, 5, 7])
=> 74
second_largest([1, 1, 1, 1, 1, 2])
=> 1
second_largest([2, 2, 2, 2, 2, 1])
=> 1
second_largest([10, 7, 10])
=> 7
second_largest( [1, 3, 10, 16])
=> 10
second_largest([1, 1, 1, 1, 1, 1])
=> None
second_largest([1])
=> None
second_largest([])
=> None

Why to complicate the scenario? Its very simple and straight forward
Convert list to set - removes duplicates
Convert set to list again - which gives list in ascending order
Here is a code
mlist = [2, 3, 6, 6, 5]
mlist = list(set(mlist))
print mlist[-2]

You can find the 2nd largest by any of the following ways:
Option 1:
numbers = set(numbers)
numbers.remove(max(numbers))
max(numbers)
Option 2:
sorted(set(numbers))[-2]

The quickselect algorithm, O(n) cousin to quicksort, will do what you want. Quickselect has average performance O(n). Worst case performance is O(n^2) just like quicksort but that's rare, and modifications to quickselect reduce the worst case performance to O(n).
The idea of quickselect is to use the same pivot, lower, higher idea of quicksort, but to then ignore the lower part and to further order just the higher part.

This is one of the Simple Way
def find_second_largest(arr):
first, second = 0, 0
for number in arr:
if number > first:
second = first
first = number
elif number > second and number < first:
second = number
return second

If you do not mind using numpy (import numpy as np):
np.partition(numbers, -2)[-2]
gives you the 2nd largest element of the list with a guaranteed worst-case O(n) running time.
The partition(a, kth) methods returns an array where the kth element is the same it would be in a sorted array, all elements before are smaller, and all behind are larger.

there are some good answers here for type([]), in case someone needed the same thing on a type({}) here it is,
def secondLargest(D):
def second_largest(L):
if(len(L)<2):
raise Exception("Second_Of_One")
KFL=None #KeyForLargest
KFS=None #KeyForSecondLargest
n = 0
for k in L:
if(KFL == None or k>=L[KFL]):
KFS = KFL
KFL = n
elif(KFS == None or k>=L[KFS]):
KFS = n
n+=1
return (KFS)
KFL=None #KeyForLargest
KFS=None #KeyForSecondLargest
if(len(D)<2):
raise Exception("Second_Of_One")
if(type(D)!=type({})):
if(type(D)==type([])):
return(second_largest(D))
else:
raise Exception("TypeError")
else:
for k in D:
if(KFL == None or D[k]>=D[KFL]):
KFS = KFL
KFL = k
elif(KFS == None or D[k] >= D[KFS]):
KFS = k
return(KFS)
a = {'one':1 , 'two': 2 , 'thirty':30}
b = [30,1,2]
print(a[secondLargest(a)])
print(b[secondLargest(b)])
Just for fun I tried to make it user friendly xD

>>> l = [19, 1, 2, 3, 4, 20, 20]
>>> sorted(set(l))[-2]
19

O(n): Time Complexity of a loop is considered as O(n) if the loop variables is incremented / decremented by a constant amount. For example following functions have O(n) time complexity.
// Here c is a positive integer constant
for (int i = 1; i <= n; i += c) {
// some O(1) expressions
}
To find the second largest number i used the below method to find the largest number first and then search the list if thats in there or not
x = [1,2,3]
A = list(map(int, x))
y = max(A)
k1 = list()
for values in range(len(A)):
if y !=A[values]:
k.append(A[values])
z = max(k1)
print z

Objective: To find the second largest number from input.
Input : 5
2 3 6 6 5
Output: 5
*n = int(raw_input())
arr = map(int, raw_input().split())
print sorted(list(set(arr)))[-2]*

def SecondLargest(x):
largest = max(x[0],x[1])
largest2 = min(x[0],x[1])
for item in x:
if item > largest:
largest2 = largest
largest = item
elif largest2 < item and item < largest:
largest2 = item
return largest2
SecondLargest([20,67,3,2.6,7,74,2.8,90.8,52.8,4,3,2,5,7])

list_nums = [1, 2, 6, 6, 5]
minimum = float('-inf')
max, min = minimum, minimum
for num in list_nums:
if num > max:
max, min = num, max
elif max > num > min:
min = num
print(min if min != minimum else None)
Output
5

Initialize with -inf. This code generalizes for all cases to find the second largest element.
max1= float("-inf")
max2=max1
for item in arr:
if max1<item:
max2,max1=max1,item
elif item>max2 and item!=max1:
max2=item
print(max2)

Using reduce from functools should be a linear-time functional-style alternative:
from functools import reduce
def update_largest_two(largest_two, x):
m1, m2 = largest_two
return (m1, m2) if m2 >= x else (m1, x) if m1 >= x else (x, m1)
def second_largest(numbers):
if len(numbers) < 2:
return None
largest_two = sorted(numbers[:2], reverse=True)
rest = numbers[2:]
m1, m2 = reduce(update_largest_two, rest, largest_two)
return m2
... or in a very concise style:
from functools import reduce
def second_largest(n):
update_largest_two = lambda a, x: a if a[1] >= x else (a[0], x) if a[0] >= x else (x, a[0])
return None if len(n) < 2 else (reduce(update_largest_two, n[2:], sorted(n[:2], reverse=True)))[1]

This can be done in [N + log(N) - 2] time, which is slightly better than the loose upper bound of 2N (which can be thought of O(N) too).
The trick is to use binary recursive calls and "tennis tournament" algorithm. The winner (the largest number) will emerge after all the 'matches' (takes N-1 time), but if we record the 'players' of all the matches, and among them, group all the players that the winner has beaten, the second largest number will be the largest number in this group, i.e. the 'losers' group.
The size of this 'losers' group is log(N), and again, we can revoke the binary recursive calls to find the largest among the losers, which will take [log(N) - 1] time. Actually, we can just linearly scan the losers group to get the answer too, the time budget is the same.
Below is a sample python code:
def largest(L):
global paris
if len(L) == 1:
return L[0]
else:
left = largest(L[:len(L)//2])
right = largest(L[len(L)//2:])
pairs.append((left, right))
return max(left, right)
def second_largest(L):
global pairs
biggest = largest(L)
second_L = [min(item) for item in pairs if biggest in item]
return biggest, largest(second_L)
if __name__ == "__main__":
pairs = []
# test array
L = [2,-2,10,5,4,3,1,2,90,-98,53,45,23,56,432]
if len(L) == 0:
first, second = None, None
elif len(L) == 1:
first, second = L[0], None
else:
first, second = second_largest(L)
print('The largest number is: ' + str(first))
print('The 2nd largest number is: ' + str(second))

You can also try this:
>>> list=[20, 20, 19, 4, 3, 2, 1,100,200,100]
>>> sorted(set(list), key=int, reverse=True)[1]
100

A simple way :
n=int(input())
arr = set(map(int, input().split()))
arr.remove(max(arr))
print (max(arr))

use defalut sort() method to get second largest number in the list.
sort is in built method you do not need to import module for this.
lis = [11,52,63,85,14]
lis.sort()
print(lis[len(lis)-2])

Just to make the accepted answer more general, the following is the extension to get the kth largest value:
def kth_largest(numbers, k):
largest_ladder = [float('-inf')] * k
count = 0
for x in numbers:
count += 1
ladder_pos = 1
for v in largest_ladder:
if x > v:
ladder_pos += 1
else:
break
if ladder_pos > 1:
largest_ladder = largest_ladder[1:ladder_pos] + [x] + largest_ladder[ladder_pos:]
return largest_ladder[0] if count >= k else None

def secondlarget(passinput):
passinputMax = max(passinput) #find the maximum element from the array
newpassinput = [i for i in passinput if i != passinputMax] #Find the second largest element in the array
#print (newpassinput)
if len(newpassinput) > 0:
return max(newpassinput) #return the second largest
return 0
if __name__ == '__main__':
n = int(input().strip()) # lets say 5
passinput = list(map(int, input().rstrip().split())) # 1 2 2 3 3
result = secondlarget(passinput) #2
print (result) #2

if __name__ == '__main__':
n = int(input())
arr = list(map(float, input().split()))
high = max(arr)
secondhigh = min(arr)
for x in arr:
if x < high and x > secondhigh:
secondhigh = x
print(secondhigh)
The above code is when we are setting the elements value in the list
as per user requirements. And below code is as per the question asked
#list
numbers = [20, 67, 3 ,2.6, 7, 74, 2.8, 90.8, 52.8, 4, 3, 2, 5, 7]
#find the highest element in the list
high = max(numbers)
#find the lowest element in the list
secondhigh = min(numbers)
for x in numbers:
'''
find the second highest element in the list,
it works even when there are duplicates highest element in the list.
It runs through the entire list finding the next lowest element
which is less then highest element but greater than lowest element in
the list set initially. And assign that value to secondhigh variable, so
now this variable will have next lowest element in the list. And by end
of loop it will have the second highest element in the list
'''
if (x<high and x>secondhigh):
secondhigh=x
print(secondhigh)

Max out the value by comparing each one to the max_item. In the first if, every time the value of max_item changes it gives its previous value to second_max. To tightly couple the two second if ensures the boundary
def secondmax(self, list):
max_item = list[0]
second_max = list[1]
for item in list:
if item > max_item:
second_max = max_item
max_item = item
if max_item < second_max:
max_item = second_max
return second_max

you have to compare in between new values, that's the trick, think always in the previous (the 2nd largest) should be between the max and the previous max before, that's the one!!!!
def secondLargest(lista):
max_number = 0
prev_number = 0
for i in range(0, len(lista)):
if lista[i] > max_number:
prev_number = max_number
max_number = lista[i]
elif lista[i] > prev_number and lista[i] < max_number:
prev_number = lista[i]
return prev_number

Most of previous answers are correct but here is another way !
Our strategy is to create a loop with two variables first_highest and second_highest. We loop through the numbers and if our current_value is greater than the first_highest then we set second_highest to be the same as first_highest and then the second_highest to be the current number. If our current number is greater than second_highest then we set second_highest to the same as current number
#!/usr/bin/env python3
import sys
def find_second_highest(numbers):
min_integer = -sys.maxsize -1
first_highest= second_highest = min_integer
for current_number in numbers:
if current_number == first_highest and min_integer != second_highest:
first_highest=current_number
elif current_number > first_highest:
second_highest = first_highest
first_highest = current_number
elif current_number > second_highest:
second_highest = current_number
return second_highest
print(find_second_highest([80,90,100]))
print(find_second_highest([80,80]))
print(find_second_highest([2,3,6,6,5]))

Best solution that my friend Dhanush Kumar came up with:
def second_max(loop):
glo_max = loop[0]
sec_max = float("-inf")
for i in loop:
if i > glo_max:
sec_max = glo_max
glo_max=i
elif sec_max < i < glo_max:
sec_max = i
return sec_max
#print(second_max([-1,-3,-4,-5,-7]))
assert second_max([-1,-3,-4,-5,-7])==-3
assert second_max([5,3,5,1,2]) == 3
assert second_max([1,2,3,4,5,7]) ==5
assert second_max([-3,1,2,5,-2,3,4]) == 4
assert second_max([-3,-2,5,-1,0]) == 0
assert second_max([0,0,0,1,0]) == 0

Below code will find the max and the second max numbers without the use of max function. I assume that the input will be numeric and the numbers are separated by single space.
myList = input().split()
myList = list(map(eval,myList))
m1 = myList[0]
m2 = myList[0]
for x in myList:
if x > m1:
m2 = m1
m1 = x
elif x > m2:
m2 = x
print ('Max Number: ',m1)
print ('2nd Max Number: ',m2)

Here I tried to come up with an answer.
2nd(Second) maximum element in a list using single loop and without using any inbuilt function.
def secondLargest(lst):
mx = 0
num = 0
sec = 0
for i in lst:
if i > mx:
sec = mx
mx = i
else:
if i > num and num >= sec:
sec = i
num = i
return sec

How to find the majority integer that is divisible by the integer 10?

I'm writing a function "most_of" that takes a list of numbers as a argument. The objective of the function is to take the list, iterate over it and find out if the majority of the list integers are divisible by 10.
So for example, if I had passed the argument:
[1,10,10,50,5]
The output would be:
True
Because 3/5 of the integers are divisible by 10. However, if I had passed:
[1,2,55,77,6]
The output would be:
False
Because 4/5 of the list integers are not divisible by 10.
Here is what I have tried:
def most_of(lst):
for i in lst:
if lst[i] % 10 == 0:
lst == True
else:
lst == False
I'm basically stuck at this point because this doesn't check if the majority of the numbers are divisible by ten, it just divides.
Thanks for the help!

Count how many integers are divisible by ten, and test whether that number is "the majority" - that is, if it's greater than or equal to half the lists' length. Like this:
def most_of(lst):
num = sum(1 for n in lst if n % 10 == 0)
return num >= len(lst) / 2.0
For example:
>>> most_of([1,10,10,50,5])
True
>>> most_of([1,2,55,77,6])
False

The objective of the function is to take the list, iterate over it and
find out if the majority of the list integers are divisible by 10.
Your list will contain two kind of integers: those that are divisible by 10 and those that aren't. You need to find the number of integers in each of the two categories, compare those numbers and return True or False accordingly. So, your function would look like this:
def most_of(lst):
divisible_counter = 0
non_divisible_counter = 0
for element in lst:
if element % 10 == 0:
divisible_counter +=1
else:
non_divisible_counter += 1
if divisible_counter > non_divisible_counter:
return True
else:
return False
Of course, all the above code could be reduced a lot. But I wanted to show an algorithm that would be easier to understand for Python beginners.

A slight modification of the answer by Oscar:
def most_of(lst):
return sum(1 if n % 10 == 0 else -1 for n in lst) >= 0
with the same results of course
lst1 = [1,10,10,50,5]
lst2 = [1,2,55,77,6]
print(most_of(lst1)) # True
print(most_of(lst2)) # False

you assign your list a bool after you test your first number, but you have to count all numbers which can divide by ten without rest and all other numbers and then compare this counters:
def most_of(lst):
divideByTen = 0
otherNumbers = 0
for i in lst:
if i % 10 == 0:
divideByTen+=1
else:
otherNumbers+=1
if(divideByTen > otherNumbers):
return True
else:
return False
a = [1,10,10,50,5]
b = [1,2,55,77,6]
print(most_of(a))
print(most_of(b))

Using a loop to describe multiple conditions

In the following code, I am trying to extract numbers from a list in which all digits are divisible by 2. The following code works.
l = range(100,401)
n=[]
for i in l:
s =str(i)
if all([int(s[0])%2==0,int(s[1])%2==0,int(s[2])%2==0]):
n.append(s)
print(",".join(n))
I was trying to insert a for loop to avoid writing all three conditions explicitly.
l = range(100,401)
n=[]
ss=[]
for i in l:
s =str(i)
ss.append(s)
for element in ss:
for j in range(3):
if int(element[j])%2==0:
n.append(element)
print(n)
I can't get the desired output. Not only that, the elements of output list 'n' at even index are printed twice. I am unable to figure out WHY?
Thanks.

Generator expression checking if all() elements evaluate to True comes to your rescue:
l = range(100,401)
n=[]
for i in l:
s = str(i)
if all(int(ch) % 2 == 0 for ch in s):
n.append(s)
print(",".join(n))
Now it also works even if you work with more digits.
Thanks for #jpp's advice on generator expression!
And here a faster alternative where you evaluate if any() is not divisable with 2.
l = range(100,401)
n=[]
for i in l:
s = str(i)
if any(int(ch) % 2 != 0 for ch in s):
continue
else:
n.append(s)
print(",".join(n))

You can do this:
l = range(100, 401)
n = []
for i in l:
v = 0
for j in str(i):
if int(j) % 2 == 0:
v += 1
if v == len(str(i)):
n.append(str(i))
print(",".join(n))
Or with some list comprehension:
l = range(100, 401)
n = []
for i in l:
if all(int(j) % 2 == 0 for j in str(i)):
n.append(str(i))
print(",".join(n))
Or with even more list comprehension:
l = range(100, 401)
n = [str(i) for i in l if all(int(j) % 2 == 0 for j in str(i))]
print(",".join(n))
Or with a ridiculous minimizing:
print(",".join([str(i) for i in range(100, 401) if all(int(j) % 2 == 0 for j in str(i))]))
Explaining
OP asked me to explain why his code doesn't work. I'll make it in some steps, also optimizing it:
l = range(100,401)
n = []
ss = []
for i in l: # You don't need this loop, you are just making a new list with string values instead of integers. You could make that on the fly.
s = str(i)
ss.append(s)
for element in ss:
for j in range(3):
if int(element[j]) % 2 == 0: # This only check if the current digit is pair and it append the whole number to the list. You have to check if the 3 numbers are pair AND then append it.
n.append(element)
print(n)
Your code check each digit and if that is true, the number is appended to the result list (n). But you don't want that, you want to check if the 3 digits that make the number are pair, so you have to check the whole group.
For example you could do this:
for element in l:
pairs = 0
for j in range(3):
if int(str(element)[j]) % 2 == 0:
pairs += 1 # Each time a digit of the number is pair, `pairs` variable increase in one
if pairs == 3: # If the 3 digits are true it append your number
n.append(str(element))
That is my first idea of how to improve your code, but instead of element and pairs I use j and v, (also I don't use range(3), I just iterate over the stringed number).
If you are looking for something "better" you could try to use a list comprehension like all(int(j) % 2 == 0 for j in str(i)). That iterate over all the digits to check if the are pair, if all the checks are true (like 222, or 284) it returns true.
Let me know if I should explain something more.

Try this method. You don't need to check all the numbers.
You just need to change the range statement from range(100, 401) to range (100, 401, 2) and add some checks as the Numbers which have first digit as Odd you can skip all the 100 numbers and then in next 10 series you can skip 10 if the tenth digit is odd. It reduces the complexity and decreases your processing time.
l = range(100, 401, 2)
n = []
for i in l:
s = str(i)
if int(s[0]) % 2 == 1:
remainder = i % 100
i = i - remainder + 100 - 1
continue
elif int(s[1])%2 == 1:
remainder = i % 10
i = i - remainder + 10 - 1
continue
n.append(s)
print(",".join(n))

Why are these lines of code in python only outputting the same answer?

I'm trying to get this program to return all possible multiples of 3 and 5 below 1001 and then add them all together and print it but for some reason these lines of code only seem to be printing one number and that number is the number 2 which is obviously wrong. Can someone point me in the right direction to why this code is grossly wrong?
n = 0
x = n<1001
while (n < 1001):
s = x%3 + x%5
print s

You've got a few mistakes:
x is a boolean type
Your loop never ends
adding values to mimic lists?
Edit
Didn't see the part where you wanted sum, so you could employ a for-in loop or just a simple one like so:
sum = 0
for i in range(1001):
if(i % 3 == 0 or i % 5):
sum += i
print(sum)
(Python 3)
You need to stop while at some point by incrementing n. Here is some code:
nums = []
n = 0
while (n < 1001):
# in here you check for the multiples
# then append using nums.append()
n += 1
This creates a loop and a list that accounts for every number in 0 to 1000. In the body, check for either condition and append to the list, then print out the values in the list.
num is a list where you are going to store all the values that apply, (those numbers who are divisible by 3 and 5, which you calculate with modulo). You append to that list when a condition is met. Here is some code:
nums = []
n = 0
while (n < 1001):
if(n % 3 == 0 or n % 5 ==0):
nums.append(n)
n += 1
print(n) #or for loop for each value
Explanation: a list of numbers called num stores the numbers that are divisible by 3 or 5. The loop starts at zero and goes to 1000, and for all the values that are divisible by 3 or 5, they will be added to the list. Then it prints the list.
Of course there is a simpler approach with a range:
for i in range(1001):
if(i % 3 == 0 or i % 5 == 0):
print(i)
This will print out all the values one by one. It is 1001 because the upper limit is exclusive.

true=1
false=0
so:
x = n<1001
we have x=1 because 0<1001 is true
s = x%3 + x%5
the remainder of 1/3 is 1 and 1/5 is 1

In your code:
1. x=n<1001 - generates a boolean value; on which we can't perform a mathematical operation.
In while loop:
your variable n,x are not changing; they are constant to same value for all the iterations.
Solution 1:
Below code will help you out.
s=0
for i in range(1,1002):
if( i%3 == 0 or i%5 == 0):
s = s + i
print(s)
Solution: 2
There is one more approach you can use.
var = [i for i in range(1,1002) if i%3==0 or i%5 ==0]
print(sum(var))