121. More list comprehension examples

Example 1 – double the numbers

Standard loop approach:

foo = [1, 2, 3, 4]
bar = []

for x in foo:
    bar.append(x * 2)


[2, 4, 6, 8]

Using list comprehension:

foo = [1, 2, 3, 4]
bar = [x * 2 for x in foo]


[2, 4, 6, 8]

Example 2 – convert Celsius to Fahrenheit

This example calls a function from within the list comprehension.

Define the function:

def convert_celsius_to_fahrenheit(deg_celsius):
    Convert degress celsius to fahrenheit
    Returns float value - temp in fahrenheit
    Keyword arguments:
        def_celcius -- temp in degrees celsius
    return (9/5) * deg_celsius + 32

Standard loop approach:

#list of temps in degree celsius to convert to fahrenheit
celsius = [39.2, 36.5, 37.3, 41.0]

#standard for loop approach
fahrenheit = []
for x in celsius:

print('Using standard for loop: {}'.format(fahrenheit))


Using standard for loop: [102.56, 97.7, 99.14, 105.8]

Using list comprehension

fahrenheit = [convert_celsius_to_fahrenheit(x) for x in celsius]
print('Using list comprehension: {}'.format(fahrenheit))


Using list comprehension: [102.56, 97.7, 99.14, 105.8]

Example 3 – convert the strings to different data types

This example also make use of the zip function. Zip allows you to iterate through two lists at the same time.

inputs = ["1", "3.142", "True", "spam"]
converters = [int, float, bool, str]

values_with_correct_data_types = [t(s) for (s, t) in zip(inputs, converters)]


[1, 3.142, True, 'spam']

Example 4 – Using if statements within a list comprehension

The example filters a list of file names to the python files only

unfiltered_files = ['test.py', 'names.csv', 'fun_module.py', 'prog.config']

# Standard loop form
python_files = []
# filter the files using a standard for loop 
for file in unfiltered_files:
    if file[-2:] == 'py':
print('using standard for loop: {}'.format(python_files))

#list comprehension
python_files = [file for file in unfiltered_files if file[-2:] == 'py']

print('using list comprehension {}'.format(python_files))


using standard for loop: ['test.py', 'fun_module.py']
using list comprehension ['test.py', 'fun_module.py']

Example 5 – List comprehension to create a list of lists

list_of_lists = []

# Standard loop form
for i in range(5):
    sub_list = []
    for j in range(3):
        sub_list.append(i * j)


# List comprehension
list_of_lists = [[i * j for j in range(3)] for i in range(5)]



[[0, 0, 0], [0, 1, 2], [0, 2, 4], [0, 3, 6], [0, 4, 8]]
[[0, 0, 0], [0, 1, 2], [0, 2, 4], [0, 3, 6], [0, 4, 8]]

Example 6: Iterate over all items in a list of lists

The code converts a list of lists to a list of items
We call this flattening the list.

list_of_lists = [[8, 2, 1], [9, 1, 2], [4, 5, 100]]

# Standard loop form
flat_list = []
for row in list_of_lists:
    for col in row:


# List comprehension:
flat_list = [item for sublist in list_of_lists for item in sublist]


[8, 2, 1, 9, 1, 2, 4, 5, 100]
[8, 2, 1, 9, 1, 2, 4, 5, 100]

83. Automatically passing unpacked lists or tuples to a function (or why do you see * before lists and tuples)

Imagine we have a very simple function that adds three numebrs together:

In [1]:
def add_three_numbers (a, b, c):
    return a + b + c

We would normally pass separate numebrs to the function, e.g.

add_three_numbers (10, 20, 35)

But what if our numbers are in a list or a tuple. If we pass that as a list then we are passing only a single argument, and the function declares an error:

In [3]:
my_list = [10, 20, 35]

add_three_numbers (my_list)
TypeError                                 Traceback (most recent call last)
<ipython-input-3-900947bff326> in <module>()
      1 my_list = [10, 20, 35]
----> 3 add_three_numbers (my_list)

TypeError: add_three_numbers() missing 2 required positional arguments: 'b' and 'c'

Python allows us to pass the list or tuple with the instruction to unpack it for input into the function. We instruct Python to unpack the list/tuple with an asterix before the list/tuple:

add_three_numbers (*my_list)



3. Python basics: Nested Lists

So far we have looked at lists which contain a simple series of numbers, text, or a mixture of numbers and texts (Python lists can also hold any Python object, but in Healthcare modelling we are usually dealing with numbers or text in a list).

It is possible though to build nested lists. In the example below we generate a list manually, with each nested list on a separate line. This separation by line is just to make it easier to see; it is not needed in Python, but thought to layout of code is important if other people will be looking at your code.

Continue reading “3. Python basics: Nested Lists”

2. Python basics: Lists

Lists, tuples, sets and dictionaries are four basic objects for storing data in Python. Later we’ll look at libraries that allow for specialised handling and analysis of large or complex data sets.

Lists are a group of text or numbers (or more complex objects) held together in a given order. Lists are recognised by using square brackets [….], with members of the list separated by commas. Lists are mutable, that is their contents may be changed. Note that when Python numbers a list the first element is referenced by the index zero. Python is a ‘zero-indexed’ language.

Below is code demonstrating some common handling of lists
Continue reading “2. Python basics: Lists”