Control Flow & Truthiness

Control Flow

I believe the main take away from this section is to briefly highlight the various control flows possible.

Here's a traditional if-else statement:

x = 5

if x % 2 == 0:
    parity = "even"
else:
    parity = "odd"

parity # 'odd'

The author may, from time to time, opt to use a shorter ternary if-else one-liner, like so:

parity = "even" if x % 2 == 0 else "odd"

The author points out that while while-loops exist:

x = 0

while x < 10:
    print(f"{x} is less than 10")
    x += 1

for and in will be used more often (the code below is both shorter and more readable):

for x in range(10):
    print(f"{x} is less than 10")

We'll also note that range(x) also goes up to x-1.

Finally, more complex logic is possible, although we'll have to revisit exactly when more complex logic is used in a data science context.

for x in range(10):
    if x == 3:
        continue
    if x == 5:
        break
    print(x)

Truthiness

Booleans in Python, True and False, are only have the first letter capitalized. And Python uses None to indicate a nonexistent value. We'll try to handle the exception below:

1 < 2 # True (not TRUE)
1 > 2 # False (not FALSE)

x = 1
try:
    assert x is None
except AssertionError:
    print("There was an AssertionError because x is not 'None'")

A major takeaway for me is the concept of "truthy" and "falsy". The first thing to note is that anything after if implies "is true" which is why if-statements can be used to check is a list, string or dictionary is empty:

x = [1]
y = []

# if x...is true
# Truthy
if x:
    print("Truthy")
else:
    print("Falsy")

# if y...is true    
# Falsy
print("Truthy") if y else print("Falsy")

You'll note the ternary version here is slightly less readable. Here are more examples to understand "truthiness".

## Truthy example

# create a function that returns a string
def some_func():
    return "a string"

# set s to some_func 
s = some_func()

# use if-statement to check truthiness - returns 'a'
if s:
    first_char = s[0]
else:
    first_char = ""

## Falsy example

# another function return empty string
def another_func():
    return ""

# set another_func to y (falsy example)
y = another_func()

# when 'truthy' return second value,
# when 'falsy' return first value
first_character = y and y[0]

Finally, the author brings up all and any functions. The former returns True when every element is truthy; the latter returns True when at least one element is truthy:

all([True, 1, {3}]) # True

all([True, 1, {}])  # False

any([True, 1, {}])  # True

all([])             # True

any([])             # False

You'll note that the truthiness within the list is being evaluated. So all([]) suggests there are no 'falsy' elements within the list, because it's empty, so it evaluates to True.

On the other hand, any([]) suggests not even one (or at least one) element is 'truthy', because the list is empty, so it evaluates to False.