Last updated on 2023-11-17 | Edit this page
Estimated time 30 minutes
- How can my programs do different things based on data values?
- Write conditional statements including
- Correctly evaluate expressions containing
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.
We can ask Python to take different actions, depending on a
condition, with an
The following example will lead to a syntax error in the Python
prompt, as it seems to expect exactly one top-level statement per
print('done') from the example will
fix the problem.
IPython executes the example from a single prompt without throwing an error.
= 37 num if num > 100: print('greater') else: print('not greater') print('done')
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
(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
there isn’t one, Python simply does nothing if the test is false:
= 53 num 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
which is short for “else if”. The following Python code uses
elif to print the sign of a number.
= -3 num if num > 0: print(num, 'is positive') elif num == 0: print(num, 'is zero') else: print(num, 'is negative')
-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.
We can also combine tests using
and is only true if both parts are true:
if (1 > 0) and (-1 >= 0): print('both parts are true') else: print('at least one part is false')
at least one part is false
or is true if at least one part is true:
if (1 < 0) or (1 >= 0): print('at least one test is true')
at least one test is true
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 and data with:
import numpy = numpy.loadtxt(fname='inflammation-01.csv', delimiter=',')data
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.
= numpy.amax(data, axis=0) max_inflammation_0 = numpy.amax(data, axis=0) max_inflammation_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 numpy.sum(numpy.amin(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:
else: print('Seems OK!')
Let’s test that out:
= numpy.loadtxt(fname='inflammation-01.csv', delimiter=',') data = numpy.amax(data, axis=0) max_inflammation_0 = numpy.amax(data, axis=0) max_inflammation_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!')
Suspicious looking maxima!
= numpy.loadtxt(fname='inflammation-03.csv', delimiter=',') data = numpy.amax(data, axis=0) max_inflammation_0 = numpy.amax(data, axis=0) max_inflammation_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!')
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
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
where every action can occur as long as their condition is met.
False booleans are not the only
values in Python that are true and false. In fact, any value
can be used in an
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')
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
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')
= 5 a = 5.1 b if abs(a - b) <= 0.1 * abs(b): print('True') else: print('False')
print(abs(a - b) <= 0.1 * abs(b))
This works because the Booleans
False have string representations which can be printed.
Python (and most other languages in the C family) provides in-place operators that work like this:
= 1 # original value x += 1 # add one to x, assigning result back to x x *= 3 # multiply x by 3 x print(x)
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?
= 0 positive_sum = 0 negative_sum = [3, 4, 6, 1, -1, -5, 0, 7, -8] test_list for num in test_list: if num > 0: += num positive_sum elif num == 0: pass else: += num negative_sum print(positive_sum, negative_sum)
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
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
Add code to the template below to do this. Note that the string
True if and only if the string it is called on
starts with the string passed as an argument, that is:
Use the following Python code as your starting point:
= ['inflammation-01.csv', filenames '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:
= ['inflammation-01.csv', 'inflammation-02.csv'] large_files = ['small-01.csv', 'small-02.csv'] small_files = ['myscript.py']other_files
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)
- 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)?
= 'aeiouAEIOU' vowels = 'Mary had a little lamb.' sentence = 0 count for char in sentence: if char in vowels: += 1 count print('The number of vowels in this string is ' + str(count))
if conditionto start a conditional statement,
elif conditionto provide additional tests, and
elseto provide a default.
- The bodies of the branches of conditional statements must be indented.
==to test for equality.
X and Yis only true if both
X or Yis true if either
Y, or both, are true.
- Zero, the empty string, and the empty list are considered false; all other numbers, strings, and lists are considered true.
Falserepresent truth values.