Check if all values in list are greater than a certain number
function, list, max, python
Solution
Use the `all()` function with a generator expression:
>>> my_list1 = [30, 34, 56]
>>> my_list2 = [29, 500, 43]
>>> all(i >= 30 for i in my_list1)
True
>>> all(i >= 30 for i in my_list2)
False
Note that this tests for greater than or equal to 30, otherwise `my_list1` would not pass the test either.
If you wanted to do this in a function, you'd use:
def all_30_or_up(ls):
for i in ls:
if i < 30:
return False
return True
e.g. as soon as you find a value that proves that there is a value below 30, you return `False`, and return `True` if you found no evidence to the contrary.
Similarly, you can use the `any()` function to test if at least 1 value matches the condition.
Problem
``` my_list1 = [30,34,56] my_list2 = [29,500,43] ``` How to I check if all values in list are >= 30? `my_list1` should work and `my_list2` should not. The only thing I could think of doing was: ``` boolean = 0 def func(ls): for k in ls: if k >= 30: boolean = boolean + 1 else: boolean = 0 if boolean > 0: print 'Continue' elif boolean = 0: pass ``` Update 2016: In hindsight, after dealing with bigger datasets where speed actually matters and utilizing `numpy`...I would do this: ``` >>> my_list1 = [30,34,56] >>> my_list2 = [29,500,43] >>> import numpy as np >>> A_1 = np.array(my_list1) >>> A_2 = np.array(my_list2) >>> A_1 >= 30 array([ True, True, True], dtype=bool) >>> A_2 >= 30 array([False, True, True], dtype=bool) >>> ((A_1 >= 30).sum() == A_1.size).astype(np.int) 1 >>> ((A_2 >= 30).sum() == A_2.size).astype(np.int) 0 ``` You could also do something like: ``` len([*filter(lambda x: x >= 30, my_list1)]) > 0 ```