any() and all() are Python built in functions that let you check whether some iterable object like al ist contains any true values or all true values, respectively. This can be a useful operation when you want to check whether some large sequence conforms to a logical check. any() and all() also treat 0's as false and 1's as true, so they can be run on lists, arrays and pandas data frame columns encoded as indicator variables to check whether any or all of the values are equal to 1.

Code used in the video:

# Check if all elements of an iterable are true with all()

x = [True, True, True]

y = [True, False, True]

z = [False, False, False]

print(all(x))
print(all(y))
print(all(z))

# Check if any elements of an iterable are true with any()

print(any(x))
print(any(y))
print(all(z))

# any() and all() work on 0s and 1s
# 0 = False
# 1 = True

x = [0, 0, 0, 1]

print(any(x))
print(all(x))

# Useful when used with logical operations
import numpy as np

power_level_list = np.array([1000, 4000, 150, 9001, 1500])

any(power_level_list ＞ 9000)


* Note: YouTube does not allow greater than or less than symbols in the text description, so the code above will not be exactly the same as the code shown in the video! I will use Unicode large ＜ and ＞ symbols in place of the standard sized ones.