Making Choices
Last updated on 2024-06-24 | Edit this page
Overview
Questions
- How can my programs do different things based on data values?
Objectives
- Write conditional statements including
if
,elif
, andelse
branches. - Correctly evaluate expressions containing
and
andor
.
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:
OUTPUT
not greater
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:
PYTHON
num = 53
print('before conditional...')
if num > 100:
print(num, 'is greater than 100')
print('...after conditional')
OUTPUT
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.
PYTHON
num = -3
if num > 0:
print(num, 'is positive')
elif num == 0:
print(num, 'is zero')
else:
print(num, 'is negative')
OUTPUT
-3 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 -
<
: less than -
==
: equal to -
!=
: does not equal -
>=
: greater than or equal to -
<=
: less than or equal to
We can also combine tests using and
and
or
.
An and
expression is only true if both parts are
true:
PYTHON
if (1 > 0) and (-1 >= 0):
print('both parts are true')
else:
print('at least one part is false')
OUTPUT
at least one part is false
while or
is true if at least one part is true:
OUTPUT
at least one test is true
Booleans
True
and False
are special words in Python.
They are a type of data 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. If you’re starting this session fresh, make sure to set up your notebook:
If did not continue in the same notebook directly from the last time you accessed Google Drive, you need the following lines:
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.
PYTHON
max_inflammation_0 = numpy.amax(data, axis=0)[0]
max_inflammation_20 = numpy.amax(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:
And if neither of these conditions are true, we can use
else
to give the all-clear:
Let’s test that out:
PYTHON
data = numpy.loadtxt(fname=file_path+'inflammation-01.csv', delimiter=',')
max_inflammation_0 = numpy.amax(data, axis=0)[0]
max_inflammation_20 = numpy.amax(data, axis=0)[20]
if max_inflammation_0 == 0 and max_inflammation_20 == 20:
print('Suspicious looking maxima!')
elif numpy.sum(numpy.amin(data, axis=0)) == 0:
print('Minima add up to zero!')
else:
print('Seems OK!')
OUTPUT
Suspicious looking maxima!
PYTHON
data = numpy.loadtxt(fname=file_path+'inflammation-03.csv', delimiter=',')
max_inflammation_0 = numpy.amax(data, axis=0)[0]
max_inflammation_20 = numpy.amax(data, axis=0)[20]
if max_inflammation_0 == 0 and max_inflammation_20 == 20:
print('Suspicious looking maxima!')
elif numpy.sum(numpy.amin(data, axis=0)) == 0:
print('Minima add up to zero!')
else:
print('Seems OK!')
OUTPUT
Minima add up to zero!
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.
C gets printed because the first two conditions,
4 > 5
and 4 == 5
, are not true, but
4 < 5
is true. In this case only one of these conditions
can be true for at a time, but in other scenarios multiple
elif
conditions could be met. In these scenarios only the
action associated with the first true elif
condition will
occur, starting from the top of the conditional section.
This contrasts with the case of multiple if
statements,
where every action can occur as long as their condition is met.
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.
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.
Close Enough
Write some conditions that print True
if the variable
a
is within 10% of the variable b
and
False
otherwise. Try changing the values of a
and b
. Are your results accurate for each pair of
values?
There is a built-in
function abs
that returns the absolute value of a
number:
OUTPUT
12
Try the following challenge if you want to learn some new operators and use your conditional writing skills at the same time.
Python (and most other languages in the C family) provides in-place operators that work like this:
PYTHON
x = 1 # original value
x += 1 # add one to x, assigning result back to x
x *= 3 # multiply x by 3
print(x)
OUTPUT
6
Write some code that sums the positive and negative numbers in a list separately, using in-place operators. Do you think the result is more or less readable than writing the same without in-place operators?
PYTHON
positive_sum = 0
negative_sum = 0
test_list = [3, 4, 6, 1, -1, -5, 0, 7, -8]
for num in test_list:
if num > 0:
positive_sum += num
elif num == 0:
pass
else:
negative_sum += num
print(positive_sum, negative_sum)
Here pass
means “don’t do anything”. In this particular
case, it’s not actually needed, since if num == 0
neither
sum needs to change, but it illustrates the use of elif
and
pass
.
Sorting a List Into Buckets
In our data
folder, large data sets are stored in files
whose names start with “inflammation-” and small data sets – in files
whose names start with “small-”. We also have some other files that we
do not care about at this point. We’d like to break all these files into
three lists called large_files
, small_files
,
and other_files
, respectively.
Add code to the template below to do this. Note that the string
method startswith
returns True
if and only if the string it is called on
starts with the string passed as an argument, that is:
OUTPUT
True
But
OUTPUT
False
Use the Python code below as your starting point. (To keep it simple, we’ll use the following list with only five filenames in it, but if you do it right, your code should work just as well with five hundred filenames!)
PYTHON
filenames = ['inflammation-01.csv',
'myscript.py',
'inflammation-02.csv',
'small-01.csv',
'small-02.csv']
large_files = []
small_files = []
other_files = []
Your solution should:
- loop over the names of the files
- figure out which group each filename belongs in
- append the filename to that list
In the end the three lists should be:
PYTHON
for filename in filenames:
if filename.startswith('inflammation-'):
large_files.append(filename)
elif filename.startswith('small-'):
small_files.append(filename)
else:
other_files.append(filename)
print('large_files:', large_files)
print('small_files:', small_files)
print('other_files:', other_files)
Try the following bonus challenge if you’d like more practice combining conditionals with loops.
- Write a loop that counts the number of vowels in a character string.
- Test it on a few individual words and full sentences.
- Once you are done, compare your solution to your neighbor’s. Did you make the same decisions about how to handle the letter ‘y’ (which some people think is a vowel, and some do not)?
Thanks for traveling with us so far! You’ve seen Numpy (critical for working with datasets), Matplotlib (a great way to visualize data) and a plethora of important computing fundamentals. If we run out of time cover episode 8, functions are a really powerful programming concept so we encourage you to give it a try using this website.
Key Points
- Use
if condition
to start a conditional statement,elif condition
to provide additional tests, andelse
to provide a default. - The bodies of the branches of conditional statements must be indented.
- Use
==
to test for equality. -
X and Y
is only true if bothX
andY
are true. -
X or Y
is true if eitherX
orY
, or both, are true. - Zero, the empty string, and the empty list are considered false; all other numbers, strings, and lists are considered true.
-
True
andFalse
represent truth values.