How do i make a choice option in python?

Overview

Teaching: 30 min
Exercises: 0 min

Questions

• How can my programs do different things based on data values?

Objectives

• Write conditional statements including if, elif, and else branches.

• Correctly evaluate expressions containing and and or.

In our last lesson, we discovered something suspicious was going on in our inflammation data by drawing some plots. How can we use Python to automatically recognize the different features we saw, and take a different action for each? In this lesson, we’ll learn how to write code that runs only when certain conditions are true.

Conditionals

We can ask Python to take different actions, depending on a condition, with an if statement:

num = 37
if num > 100:
    print['greater']
else:
    print['not greater']
print['done']

The second line of this code uses the keyword if to tell Python that we want to make a choice. If the test that follows the if statement is true, the body of the if [i.e., the set of lines indented underneath it] is executed, and “greater” is printed. If the test is false, the body of the else is executed instead, and “not greater” is printed. Only one or the other is ever executed before continuing on with program execution to print “done”:

Conditional statements don’t have to include an else. If there isn’t one, Python simply does nothing if the test is false:

num = 53
print['before conditional...']
if num > 100:
    print[num, 'is greater than 100']
print['...after conditional']

before conditional...
...after conditional

We can also chain several tests together using elif, which is short for “else if”. The following Python code uses elif to print the sign of a number.

num = -3

if num > 0:
    print[num, 'is positive']
elif num == 0:
    print[num, 'is zero']
else:
    print[num, 'is negative']

Note that to test for equality we use a double equals sign == rather than a single equals sign = which is used to assign values.

Comparing in Python

Along with the > and == operators we have already used for comparing values in our conditionals, there are a few more options to know about:

• >: greater than
• =: greater than or equal to
• 0] and [-1 >= 0]: print['both parts are true'] else: print['at least one part is false']

  at least one part is false
  

  while or is true if at least one part is true:

  if [1 = 0]:
      print['at least one test is true']
  

  at least one test is true
  

  True and False

  True and False are special words in Python called booleans, which represent truth values. A statement such as 1 < 0 returns the value False, while -1 < 0 returns the value True.

  Checking our Data

  Now that we’ve seen how conditionals work, we can use them to check for the suspicious features we saw in our inflammation data. We are about to use functions provided by the numpy module again. Therefore, if you’re working in a new Python session, make sure to load the module with:

  From the first couple of plots, we saw that maximum daily inflammation exhibits a strange behavior and raises one unit a day. Wouldn’t it be a good idea to detect such behavior and report it as suspicious? Let’s do that! However, instead of checking every single day of the study, let’s merely check if maximum inflammation in the beginning [day 0] and in the middle [day 20] of the study are equal to the corresponding day numbers.

  max_inflammation_0 = numpy.max[data, axis=0][0]
  max_inflammation_20 = numpy.max[data, axis=0][20]
  
  if max_inflammation_0 == 0 and max_inflammation_20 == 20:
      print['Suspicious looking maxima!']
  

  We also saw a different problem in the third dataset; the minima per day were all zero [looks like a healthy person snuck into our study]. We can also check for this with an elif condition:

  elif numpy.sum[numpy.min[data, axis=0]] == 0:
      print['Minima add up to zero!']
  

  And if neither of these conditions are true, we can use else to give the all-clear:

  Let’s test that out:

  data = numpy.loadtxt[fname='inflammation-01.csv', delimiter=',']
  
  max_inflammation_0 = numpy.max[data, axis=0][0]
  max_inflammation_20 = numpy.max[data, axis=0][20]
  
  if max_inflammation_0 == 0 and max_inflammation_20 == 20:
      print['Suspicious looking maxima!']
  elif numpy.sum[numpy.min[data, axis=0]] == 0:
      print['Minima add up to zero!']
  else:
      print['Seems OK!']
  

  Suspicious looking maxima!
  

  data = numpy.loadtxt[fname='inflammation-03.csv', delimiter=',']
  
  max_inflammation_0 = numpy.max[data, axis=0][0]
  max_inflammation_20 = numpy.max[data, axis=0][20]
  
  if max_inflammation_0 == 0 and max_inflammation_20 == 20:
      print['Suspicious looking maxima!']
  elif numpy.sum[numpy.min[data, axis=0]] == 0:
      print['Minima add up to zero!']
  else:
      print['Seems OK!']
  

  In this way, we have asked Python to do something different depending on the condition of our data. Here we printed messages in all cases, but we could also imagine not using the else catch-all so that messages are only printed when something is wrong, freeing us from having to manually examine every plot for features we’ve seen before.

  How Many Paths?

  Consider this code:

  if 4 > 5:
      print['A']
  elif 4 == 5:
      print['B']
  elif 4  5 and 4 == 5, are not true, but 4 < 5 is true.
  

What Is Truth?

True and False booleans are not the only values in Python that are true and false. In fact, any value can be used in an if or elif. After reading and running the code below, explain what the rule is for which values are considered true and which are considered false.

if '':
    print['empty string is true']
if 'word':
    print['word is true']
if []:
    print['empty list is true']
if [1, 2, 3]:
    print['non-empty list is true']
if 0:
    print['zero is true']
if 1:
    print['one is true']

That’s Not Not What I Meant

Sometimes it is useful to check whether some condition is not true. The Boolean operator not can do this explicitly. After reading and running the code below, write some if statements that use not to test the rule that you formulated in the previous challenge.

if not '':
    print['empty string is not true']
if not 'word':
    print['word is not true']
if not not True:
    print['not not True is true']

Close Enough

Write some conditions that print True if the variable a is within 10% of the variable b and False otherwise. Compare your implementation with your partner’s: do you get the same answer for all possible pairs of numbers?

Hint

There is a built-in function abs that returns the absolute value of a number:

Solution 1

a = 5
b = 5.1

if abs[a - b]