Conditionals

Overview

Teaching: 10 min
Exercises: 15 min
Questions
  • How can programs do different things for different data?

Objectives
  • Correctly write programs that use if and else statements and simple Boolean expressions (without logical operators).

  • Trace the execution of unnested conditionals and conditionals inside loops.

Use if statements to control whether or not a block of code is executed.

mass = 3.54
if mass > 3.0:
    print(mass, 'is large')

mass = 2.07
if mass > 3.0:
    print (mass, 'is large')
3.54 is large

Conditionals are often used inside loops.

masses = [3.54, 2.07, 9.22, 1.86, 1.71]
for m in masses:
    if m > 3.0:
        print(m, 'is large')
3.54 is large
9.22 is large

Use else to execute a block of code when an if condition is not true.

masses = [3.54, 2.07, 9.22, 1.86, 1.71]
for m in masses:
    if m > 3.0:
        print(m, 'is large')
    else:
        print(m, 'is small')
3.54 is large
2.07 is small
9.22 is large
1.86 is small
1.71 is small

Use elif to specify additional tests.

masses = [3.54, 2.07, 9.22, 1.86, 1.71]
for m in masses:
    if m > 9.0:
        print(m, 'is HUGE')
    elif m > 3.0:
        print(m, 'is large')
    else:
        print(m, 'is small')
3.54 is large
2.07 is small
9.22 is HUGE
1.86 is small
1.71 is small

Conditions are tested once, in order.

grade = 85
if grade >= 70:
    print('grade is C')
elif grade >= 80:
    print('grade is B')
elif grade >= 90:
    print('grade is A')
grade is C
velocity = 10.0
if velocity > 20.0:
    print('moving too fast')
else:
    print('adjusting velocity')
    velocity = 50.0
adjusting velocity
velocity = 10.0
for i in range(5): # execute the loop 5 times
    print(i, ':', velocity)
    if velocity > 20.0:
        print('moving too fast')
        velocity = velocity - 5.0
    else:
        print('moving too slow')
        velocity = velocity + 10.0
print('final velocity:', velocity)
0 : 10.0
moving too slow
1 : 20.0
moving too slow
2 : 30.0
moving too fast
3 : 25.0
moving too fast
4 : 20.0
moving too slow
final velocity: 30.0

Create a table showing variables’ values to trace a program’s execution.

i 0 . 1 . 2 . 3 . 4 .
velocity 10.0 20.0 . 30.0 . 25.0 . 20.0 . 30.0

Compound Relations Using and, or, and Parentheses

Often, you want some combination of things to be true. You can combine relations within a conditional using and and or. Continuing the example above, suppose you have

mass     = [ 3.54,  2.07,  9.22,  1.86,  1.71]
velocity = [10.00, 20.00, 30.00, 25.00, 20.00]

i = 0
for i in range(5):
    if mass[i] > 5 and velocity[i] > 20:
        print("Fast heavy object.  Duck!")
    elif mass[i] > 2 and mass[i] <= 5 and velocity[i] <= 20:
        print("Normal traffic")
    elif mass[i] <= 2 and velocity[i] <= 20:
        print("Slow light object.  Ignore it")
    else:
        print("Whoa!  Something is up with the data.  Check it")

Just like with arithmetic, you can and should use parentheses whenever there is possible ambiguity. A good general rule is to always use parentheses when mixing and and or in the same condition. That is, instead of:

if mass[i] <= 2 or mass[i] >= 5 and velocity[i] > 20:

write one of these:

if (mass[i] <= 2 or mass[i] >= 5) and velocity[i] > 20:
if mass[i] <= 2 or (mass[i] >= 5 and velocity[i] > 20):

so it is perfectly clear to a reader (and to Python) what you really mean.

Tracing Execution

What does this program print?

pressure = 71.9
if pressure > 50.0:
    pressure = 25.0
elif pressure <= 50.0:
    pressure = 0.0
print(pressure)

Solution

25.0

Trimming Values

Fill in the blanks so that this program creates a new list containing zeroes where the original list’s values were negative and ones where the original list’s values were positive.

original = [-1.5, 0.2, 0.4, 0.0, -1.3, 0.4]
result = ____
for value in original:
    if ____:
        result.append(0)
    else:
        ____
print(result)
[0, 1, 1, 1, 0, 1]

Solution

original = [-1.5, 0.2, 0.4, 0.0, -1.3, 0.4]
result = []
for value in original:
    if value<0.0:
        result.append(0)
    else:
        result.append(1)
print(result)

Processing Small Files

Modify this program so that it only processes files with fewer than 50 records.

import glob
import pandas as pd
for filename in glob.glob('data/*.csv'):
    contents = pd.read_csv(filename)
    ____:
        print(filename, len(contents))

Solution

import glob
import pandas as pd
for filename in glob.glob('data/*.csv'):
    contents = pd.read_csv(filename)
    if len(contents)<50:
        print(filename, len(contents))

Initializing

Modify this program so that it finds the largest and smallest values in the list no matter what the range of values originally is.

values = [...some test data...]
smallest, largest = None, None
for v in values:
    if ____:
        smallest, largest = v, v
    ____:
        smallest = min(____, v)
        largest = max(____, v)
print(smallest, largest)

What are the advantages and disadvantages of using this method to find the range of the data?

Solution

values = [-2,1,65,78,-54,-24,100]
smallest, largest = None, None
for v in values:
    if smallest==None and largest==None:
        smallest, largest = v, v
    else:
        smallest = min(smallest, v)
        largest = max(largest, v)
print(smallest, largest)

Using Functions With Conditionals in Pandas

Functions will often contain conditionals. Here is a short example that will indicate which quartile the argument is in based on hand-coded values for the quartile cut points.

def calculate_life_quartile(exp):
    if exp < 58.41:
        # This observation is in the first quartile
        return 1
    elif exp >= 58.41 and exp < 67.05:
        # This observation is in the second quartile
       return 2
    elif exp >= 67.05 and exp < 71.70:
        # This observation is in the third quartile
       return 3
    elif exp >= 71.70:
        # This observation is in the fourth quartile
       return 4
    else:
        # This observation has bad data
       return None

calculate_life_quartile(62.5)
2

That function would typically be used within a for loop, but Pandas has a different, more efficient way of doing the same thing, and that is by applying a function to a dataframe or a portion of a dataframe. Here is an example, using the definition above.

data = pd.read_csv('Americas-data.csv')
data['life_qrtl'] = data['lifeExp'].apply(calculate_life_quartile)

There is a lot in that second line, so let’s take it piece by piece. On the right side of the = we start with data['lifeExp'], which is the column in the dataframe called data labeled lifExp. We use the apply() to do what it says, apply the calculate_life_quartile to the value of this column for every row in the dataframe.

Key Points

  • Use if statements to control whether or not a block of code is executed.

  • Conditionals are often used inside loops.

  • Use else to execute a block of code when an if condition is not true.

  • Use elif to specify additional tests.

  • Conditions are tested once, in order.

  • Create a table showing variables’ values to trace a program’s execution.