{"id":74725,"date":"2020-01-04T10:22:15","date_gmt":"2020-01-04T04:52:15","guid":{"rendered":"https:\/\/techvidvan.com\/tutorials\/?p=74725"},"modified":"2020-01-04T10:22:15","modified_gmt":"2020-01-04T04:52:15","slug":"python-list-comprehension","status":"publish","type":"post","link":"https:\/\/techvidvan.com\/tutorials\/python-list-comprehension\/","title":{"rendered":"Python List Comprehension – Time to upskill your programming"},"content":{"rendered":"

In today\u2019s article, we are going to discuss a very important topic, that is, Python list comprehension. It is a very powerful<\/strong> way to perform complex operations<\/strong> and manipulate<\/strong> iterables<\/strong>.<\/p>\n

First, we will take a quick look at lists and then move towards the list comprehension. We will see various ways of how you can use list comprehension<\/strong> and become a better programmer<\/strong>.<\/p>\n

What are Lists?<\/h3>\n

Lists are a mutable collection<\/strong> of elements<\/strong>. They can be of any type like strings<\/strong>, numbers<\/strong>, sets<\/strong>, booleans<\/strong>, etc. They are created by using square brackets<\/strong>.<\/p>\n

Code:<\/strong><\/p>\n

List = [1, 2, 3, \u201dAB\u201d, \u201cDC\u201d]<\/pre>\n
We can access them with indexes<\/strong> starting from zero<\/strong>. It also supports slicing<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
print(List[1])\nprint(List[1:3])<\/pre>\n
Output:<\/strong><\/p>\n
2
\n[2, 3]<\/div>\n
Python List comprehension<\/h3>\n
List comprehensions are an easy<\/strong>, concise<\/strong>, and fast <\/strong>way to build lists<\/strong>. It allows you to perform complex operations<\/strong> on lists easily using a single line<\/strong>.<\/p>\n
First, observe this code.<\/p>\n
Suppose you want to iterate over a list<\/strong>, check a condition<\/strong> and then manipulate<\/strong> it with expression<\/strong> and append<\/strong> the result<\/strong> in a new list.<\/p>\n
The code will look something like this.<\/p>\n
Code:<\/strong><\/p>\n
new_list = []\nfor i in old_list:\n    if filter(i):\n        new_list.append(expressions(i))<\/pre>\n
But with Python list comprehension, we can do this in one line<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
new_list = [ expressions(i) for i in old_list if filter(i) ]<\/pre>\n
Once you understand this, it will be a lot easier to code this way.<\/p>\n
Syntax:<\/strong><\/p>\n
[ expression for item in list if conditional ]<\/pre>\n
How you can Use Python List Comprehension<\/h3>\n
1. Simple List Comprehension<\/h4>\n
Simple use of a Python list comprehension is when you want to iterate<\/strong> over a list<\/strong> and perform a quick operation<\/strong> on the elements.<\/p>\n
Code:<\/strong><\/p>\n
nums = [1,2,3,4,5]\n\nnew_nums = [ i+10 for i in nums]\npower_nums = [i**2 for i in nums]\n\nprint(new_nums)\nprint(power_nums)<\/pre>\n
Output:<\/strong><\/p>\n
[11, 12, 13, 14, 15]
\n[1, 4, 9, 16, 25]<\/div>\n
2. List Comprehension with Conditions<\/h4>\n
List comprehensions also provide a way to check for conditions<\/strong> and filter<\/strong> out the elements you don\u2019t need from the list.<\/p>\n
Code:<\/strong><\/p>\n
nums = [1, 12, 8, 14, 9, 23, 36, 5, 4 ]\n\ngreater_ten = [i for i in nums if(i>10)]\nevens = [i for i in nums if(i%2==0)]\n\nprint(\u201cGreater than ten :\u201d,greater_ten)\nprint(\u201cEven numbers list :\u201d,evens)<\/pre>\n
Output:<\/strong><\/p>\n
Greater than ten : [12, 14, 23, 36]
\nEven numbers list : [12, 8, 14, 36, 4]<\/div>\n
3. List Comprehension with Nested Conditions<\/h4>\n
Till now, in Python list comprehension, we have seen simple conditions<\/strong> but what about some nested conditions<\/strong>?<\/p>\n
Let\u2019s see how we can use nested conditions in a list comprehension.<\/p>\n
Code:<\/strong><\/p>\n
print([i for i in range(100) if(i%2==0) if(i%5==0) ])<\/pre>\n
Output:<\/strong><\/p>\n
[0, 10, 20, 30, 40, 50, 60, 70, 80, 90]<\/div>\n
Here, we used two conditions separated by space<\/strong>.<\/p>\n
It works by first checking the first condition<\/strong> and filters out<\/strong> the numbers that are divisible<\/strong> by 2<\/strong> and then from those numbers, it will filter out<\/strong> the numbers divisible by 5<\/strong>.<\/p>\n
4. If-else Condition in List Comprehension<\/h4>\n
Let us see how we can use the if-else statements<\/strong> in a Python list comprehension. If-else conditions are very useful<\/strong> and widely used<\/strong>, using them in list comprehensions will make it even more powerful<\/strong>.<\/p>\n
Code:<\/strong><\/p>\n
print([ x+1 if(x%2==0) else x**2 for x in [1,2,3,4,5,6,7,8] ])<\/pre>\n
Output:<\/strong><\/p>\n
[1, 3, 9, 5, 25, 7, 49, 9]<\/div>\n
Here, we use the if-else statement in the first position<\/strong> and we incremented<\/strong> one<\/strong> to even numbers<\/strong> and squared<\/strong> the odd numbers<\/strong>.<\/p>\n
List comprehensions make this an easy task.<\/p>\n
5. Nested List Comprehension<\/h4>\n
Suppose you have a list like this:<\/p>\n
Code:<\/strong><\/p>\n
List = [[1,2,3], [4,5,6], [3,4] ]<\/pre>\n
Now to iterate over each element, we will have to nest<\/strong> inside<\/strong> the list comprehension.<\/p>\n
Code:<\/strong><\/p>\n
[ res for x in List for res in x]<\/pre>\n
Output:<\/strong><\/p>\n
[1, 2, 3, 4, 5, 6, 3, 4]<\/div>\n
For understanding purposes, you can think of this statement as:<\/p>\n
Code:<\/strong><\/p>\n
for x in List:\n  for res in x:\n    print(res)<\/pre>\n
This way we can flatten<\/strong> a nested list<\/strong>.<\/p>\n
So far, we were discussing list comprehensions<\/strong> in Python but now we can see similar comprehension techniques in the dictionary<\/strong>, sets<\/strong>, and generators<\/strong>.<\/p>\n
Python Dictionary Comprehension<\/h3>\n
Python allows us to create dictionary comprehensions<\/strong>. The syntax is similar<\/strong> to list comprehensions in Python<\/strong>.<\/p>\n
Syntax:<\/strong><\/p>\n
{key: expression(i) for (key, i) in iterable}<\/pre>\n
Code:<\/strong><\/p>\n
num=[1,2,3,4]\nname=['one','two','three','four']\n\nmy_dict = {num:name for (num,name) in zip(num,name)}\nprint(my_dict)<\/pre>\n
Output:<\/strong><\/p>\n
{1: ‘one’, 2: ‘two’, 3: ‘three’, 4: ‘four’}<\/div>\n
You can also use list comprehensions to create<\/strong> dictionary comprehensions.<\/p>\n
Code:<\/strong><\/p>\n
even_squares = {x: x**2 for x in range(0,12,2)}\nprint(even_squares)<\/pre>\n
Output:<\/strong><\/p>\n
{0: 0, 2: 4, 4: 16, 6: 36, 8: 64, 10: 100}<\/div>\n
Python Sets Comprehension<\/h3>\n
Lets us now see how sets comprehensions work.<\/p>\n
Syntax:<\/strong><\/p>\n
{ expression(i) for i in iterable condition }<\/pre>\n
Code:<\/strong><\/p>\n
odd = { num for num in [1,2,3,4,5,6] if num%2==1}\nprint(odd)<\/pre>\n
Output:<\/strong><\/p>\n
{1, 3, 5}<\/div>\n
Python Generator Comprehensions<\/h3>\n
A quick way to create generators is with generator comprehensions<\/strong>.<\/p>\n
Syntax:<\/strong><\/p>\n
(expression(i) for i in iterable)<\/pre>\n
Code:<\/strong><\/p>\n
gen = (x**2 for x in range(100))\nprint(gen)\nnext(gen)\nnext(gen)\nnext(gen)\nnext(gen)<\/pre>\n
Output:<\/strong><\/p>\n
<generator object <genexpr> at 0x000001EA897B0BA0>
\n0
\n1
\n4
\n9<\/div>\n
Summary<\/h3>\n
This was all about the Python list comprehensions<\/strong>. Now you can clean up your code by writing simple<\/strong> and concise code<\/strong>. You can easily modify<\/strong> lists using list comprehensions.<\/p>\n
You should use list comprehensions in Python more often whenever possible but make sure not to write lengthy<\/strong> list comprehensions, then it would be better to use for loops<\/strong>.<\/p>\n","protected":false},"excerpt":{"rendered":"
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