OverviewTeaching: 30 min
Exercises: 0 minQuestions
How can my programs do different things based on data values?Objectives
Write conditional statements including
Correctly evaluate expressions containing
In our last lesson, we analyzed multiple files and showed temperature anomalies over several geographical areas. However, it was not easy to customize our plots and for instance label the various areas accordingly. 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
num = 37 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 lines indented underneath it) are executed.
If the test is false,
the body of the
else is executed instead.
Only one or the other is ever executed:
Conditional statements don’t have to include an
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
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')
-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
Falseare special words in Python called
booleans, which represent truth values. A statement such as
1 < 0returns the value
-1 < 0returns the value
Checking our Data
Let’s go back to our temperature anomaly datasets and plot the monthly average, min and max for the entire period i.e. December 1978 to February 2019.
filenames = sorted(glob.glob('../data/uahncdc.lt-*.csv')) composite_data = numpy.zeros((120,27)) for f in filenames: data = numpy.loadtxt(fname = f, skiprows=1, delimiter=',') composite_data += data composite_data/=len(filenames) fig = matplotlib.pyplot.figure(figsize=(10.0, 3.0)) axes = fig.add_subplot(1, 1, 1) axes.set_ylabel('average') axes.plot(numpy.mean(composite_data, axis=0)) fig.tight_layout() matplotlib.pyplot.show()
--------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-4-e9f9fa30176a> in <module> 6 for f in filenames: 7 data = numpy.loadtxt(fname = f, skiprows=1, delimiter=',') ----> 8 composite_data += data 9 10 composite_data/=len(filenames) ValueError: operands could not be broadcast together with shapes (120,27) (13,27) (120,27)
We get an error because the first file does not contain 10 years of data but starts from december 1978 to december 1979 (13 rows instead of 120 rows).
Now that we’ve seen how conditionals work, we can add a
if statement to skip the first filename:
- ‘uahncdc.lt-01.csv’ contains less observations than all the other files and the reason is that it starts from december 1978 to december 1979
import glob import numpy import matplotlib.pyplot %matplotlib inline filenames = sorted(glob.glob('data/uahncdc.lt-*.csv')) composite_data = numpy.zeros((120,27)) nfiles = 0 for f in filenames: data = numpy.loadtxt(fname = f, skiprows=1, delimiter=',') if data.shape == composite_data.shape: composite_data += data nfiles = nfiles + 1 composite_data/=nfiles fig = matplotlib.pyplot.figure(figsize=(10.0, 3.0)) axes = fig.add_subplot(1, 1, 1) axes.set_ylabel('average') axes.plot(numpy.mean(composite_data, axis=0)) fig.tight_layout() matplotlib.pyplot.show()
We can also print a warning if a file is skipped with an
else: print("Warning: file " , f , "skipped")
We could also use
elif to test another condition:
elif data.shape > composite_data.shape: print("Warning: file " , f , " has too many rows so we skip it") else: print("Warning: file " , f , "has not enough rows so we skip it")
So we check if the file has more or less rows than expected.
Let’s test that out:
import glob import numpy import matplotlib.pyplot %matplotlib inline filenames = sorted(glob.glob('data/uahncdc.lt-*.csv')) composite_data = numpy.zeros((120,27)) nfiles = 0 for f in filenames: data = numpy.loadtxt(fname = f, skiprows=1, delimiter=',') if data.shape == composite_data.shape: composite_data += data nfiles = nfiles + 1 elif data.shape > composite_data.shape: print("Warning: file " , f , " has too many rows so we skip it") else: print("Warning: file " , f , "has not enough rows so we skip it") composite_data/=nfiles fig = matplotlib.pyplot.figure(figsize=(10.0, 3.0)) axes = fig.add_subplot(1, 1, 1) axes.set_ylabel('average') axes.plot(numpy.mean(composite_data, axis=0)) fig.tight_layout() matplotlib.pyplot.show()
Warning: file data/uahncdc.lt-01.csv has not enough rows so we skip it Warning: file data/uahncdc.lt-05.csv has not enough rows so we skip it
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
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: print('C')
Which of the following would be printed if you were to run this code? Why did you pick this answer?
- B and C
C gets printed because the first two conditions,
4 > 5and
4 == 5, are not true, but
4 < 5is true.
What Is Truth?
Falsebooleans 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')
That’s Not Not What I Meant
Sometimes it is useful to check whether some condition is not true. The Boolean operator
notcan do this explicitly. After reading and running the code below, write some
ifstatements that use
notto 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')
Write some conditions that print
Trueif the variable
ais within 10% of the variable
Falseotherwise. Compare your implementation with your partner’s: do you get the same answer for all possible pairs of numbers?
a = 5 b = 5.1 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
Falsehave string representations which can be printed.
Python (and most other languages in the C family) provides in-place operators that work like this:
x = 1 # original value x += 1 # add one to x, assigning result back to x x *= 3 # multiply x by 3 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?
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)
passmeans “don’t do anything”. In this particular case, it’s not actually needed, since if
num == 0neither sum needs to change, but it illustrates the use of
Sorting a List Into Buckets
datafolder, 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 method
Trueif 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:
files = ['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
- append the filename to that list
In the end the three lists should be:
large_files = ['inflammation-01.csv', 'inflammation-02.csv'] small_files = ['small-01.csv', 'small-02.csv'] other_files = ['myscript.py']
for file in files: if file.startswith('inflammation-'): large_files.append(file) elif file.startswith('small-'): small_files.append(file) else: other_files.append(file) 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)?
vowels = 'aeiouAEIOU' sentence = 'Mary had a little lamb.' count = 0 for char in sentence: if char in vowels: count += 1 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.