List comprehension is a powerful feature in Python that allows you to create a new list by applying a certain operation on each element of an existing list. It is a concise and efficient way to create lists, and it can also be used with conditional statements (if-else) to filter out certain elements or perform different operations on different elements. In this article, we will take a look at how to use list comprehension with if-else statements and some code examples to illustrate the concepts.
The basic syntax of list comprehension is as follows:
new_list = [expression for element in existing_list]
Here, expression is the operation that you want to apply to each element of existing_list, and new_list is the resulting list. For example, you can use list comprehension to create a new list that contains the squares of all the numbers in an existing list:
numbers = [1, 2, 3, 4, 5]
squares = [n ** 2 for n in numbers]
print(squares) # [1, 4, 9, 16, 25]
Now, let's see how to use list comprehension with if-else statements. The basic syntax is as follows:
new_list = [expression for element in existing_list if condition]
Here, condition is a Boolean expression that is evaluated for each element of existing_list. If the condition is true, the expression is applied to the element and the resulting value is added to the new list. If the condition is false, the element is skipped. For example, you can use list comprehension to create a new list that contains only the even numbers from an existing list:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
evens = [n for n in numbers if n % 2 == 0]
print(evens) # [2, 4, 6, 8, 10]
You can also use the else clause to specify a different operation to be performed on the elements that do not meet the condition:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
evens_and_odds = [n if n % 2 == 0 else n*2 for n in numbers]
print(evens_and_odds) # [2, 2, 6, 4, 10, 6, 14, 8, 18, 10]
Here are some more examples:
# extract only string element from list
list_of_strings = ['foo', 1, 'bar', 2, 'baz', 3]
string_list = [s for s in list_of_strings if type(s) == str]
print(string_list) # ['foo', 'bar', 'baz']
# create a matrix using nested list comprehension
matrix = [[x * y for x in range(5)] for y in range(5)]
print(matrix)
# [[0, 0, 0, 0, 0],
# [0, 1, 2, 3, 4],
# [0, 2, 4, 6, 8],
# [0, 3, 6, 9, 12],
# [0, 4, 8, 12, 16]]
# extract only the title from list of dictionary
books = [{'title':
Sure, let's continue discussing list comprehension in Python.
One powerful feature of list comprehension is the ability to use nested loops. This allows you to perform operations on elements of multiple lists at the same time. For example, you can use a nested list comprehension to create a new list that contains the Cartesian product of two existing lists. The syntax for nested list comprehension is as follows:
new_list = [expression for element_1 in existing_list_1 for element_2 in existing_list_2]
Here's an example of using nested list comprehension to create a Cartesian product of two lists:
colors = ['red', 'green', 'blue']
sizes = ['small', 'medium', 'large']
products = [(color, size) for color in colors for size in sizes]
print(products)
[('red', 'small'), ('red', 'medium'), ('red', 'large'),
('green', 'small'), ('green', 'medium'), ('green', 'large'),
('blue', 'small'), ('blue', 'medium'), ('blue', 'large')]
Another topic that is related to list comprehension is the use of the `map()` and `filter()` functions. These functions are similar to list comprehension in that they allow you to apply operations to elements of a list and create a new list, but they are used in different situations. The `map()` function is used to apply the same operation to all elements of a list, while the `filter()` function is used to select only the elements that meet a certain condition. Here's an example of using `map()` and `filter()` to achieve the same result as the previous example of extracting only the even numbers from a list:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
evens = list(filter(lambda n: n % 2 == 0, numbers))
print(evens) # [2, 4, 6, 8, 10]
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
evens = list(map(lambda n: n if n % 2 == 0 else None, numbers))
print(evens) # [None, 2, None, 4, None, 6, None, 8, None, 10]
It's also worth noting that `map()` and `filter()` return iterators, which means that if you want a list you have to convert it to list using `list()` function.
In conclusion, list comprehension is a powerful feature in Python that allows you to create new lists by applying operations on existing lists in a concise and efficient way. It can also be used with conditional statements (if-else) to filter out certain elements or perform different operations on different elements. It's a great tool to have in your Python toolbox, and it can make your code more readable and efficient.
## Popular questions
1. What is the basic syntax of list comprehension in Python?
- The basic syntax of list comprehension is: `new_list = [expression for element in existing_list]`
2. How can list comprehension be used with conditional statements (if-else)?
- The basic syntax is: `new_list = [expression for element in existing_list if condition]` where `condition` is a Boolean expression that is evaluated for each element of existing_list. if the condition is true, expression is applied to the element and the resulting value is added to the new list, if the condition is false, the element is skipped.
3. Can you give an example of using list comprehension to create a new list that contains only the even numbers from an existing list?
- Sure, here's an example:
numbers = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
evens = [n for n in numbers if n % 2 == 0]
print(evens) # [2, 4, 6, 8, 10]
4. Can you use nested list comprehension to create a new list?
- Yes, you can use nested list comprehension to create a new list. It allows you to perform operations on elements of multiple lists at the same time. The syntax for nested list comprehension is as follows: `new_list = [expression for element_1 in existing_list_1 for element_2 in existing_list_2]`
5. Can you differentiate between `map()` and `filter()` functions and when to use them?
- Both `map()` and `filter()` functions are similar to list comprehension in that they allow you to apply operations to elements of a list and create a new list, but they are used in different situations. The `map()` function is used to apply the same operation to all elements of a list, while the `filter()` function is used to select only the elements that meet a certain condition. So use `map()` when you want to apply the same operation to all elements of a list and use `filter()` when you want to select only the elements that meet a certain condition.
### Tag
Pythonic
