def is_list_even(my_list):
for i in my_list:
if(i%2 != 0):
return False
return True
def is_list_odd(my_list):
for i in my_list:
if(i%2 == 0):
return False
return True
def main():
n = int(input())
lst = []
for i in range(n):
lst.append(int(input()))
if(is_list_even(lst)):
print('all even')
elif(is_list_odd(lst)):
print('all odd')
else:
print('not even or odd')
if __name__ == '__main__':
main()
Answer:
Good job!! You deserve it.
Explanation:
Convert
0.625 to binary
Translate 0.625 into a fraction. We all know that 0.5 is ½. We know that the remainder, 0.125, is ⅛. Add them together, and you get ½ + ⅛ = ⅝.
Now, in binary, the positions to the right of the point are , which is ½, ¼, and ⅛ respectively.
⅝ is 5 × ⅛. 5 in binary is 101. So, ⅝ is
= 0.101
Answer:
O(N!), O(2N), O(N2), O(N), O(logN)
Explanation:
N! grows faster than any exponential functions, leave alone polynomials and logarithm. so O( N! ) would be slowest.
2^N would be bigger than N². Any exponential functions are slower than polynomial. So O( 2^N ) is next slowest.
Rest of them should be easier.
N² is slower than N and N is slower than logN as you can check in a graphing calculator.
NOTE: It is just nitpick but big-Oh is not necessary about speed / running time ( many programmers treat it like that anyway ) but rather how the time taken for an algorithm increase as the size of the input increases. Subtle difference.
You can access various sites on WWW by using hyperlinks or by?
Answer is: A following directions on-screen
