THE WORLD'S LARGEST WEB DEVELOPER SITE

Python Tutorial

Python HOME Python Intro Python Get Started Python Syntax Python Comments Python Variables Python Data Types Python Numbers Python Casting Python Strings Python Booleans Python Operators Python Lists Python Tuples Python Sets Python Dictionaries Python If...Else Python While Loops Python For Loops Python Functions Python Lambda Python Arrays Python Classes/Objects Python Inheritance Python Iterators Python Scope Python Modules Python Dates Python Math Python JSON Python RegEx Python PIP Python Try...Except Python User Input Python String Formatting

File Handling

Python File Handling Python Read Files Python Write/Create Files Python Delete Files

Python NumPy

NumPy Intro NumPy Getting Started NumPy Creating Arrays NumPy Array Indexing NumPy Array Slicing NumPy Data Types NumPy Copy vs View NumPy Array Shape NumPy Array Reshape NumPy Array Iterating NumPy Array Join NumPy Array Split NumPy Array Search NumPy Array Sort NumPy Array Filter NumPy Random NumPy ufunc

Python Matplotlib

Matplotlib Intro Matplotlib Get Started Matplotlib Pyplot Matplotlib Plotting Matplotlib Markers Matplotlib Line Matplotlib Subplots Matplotlib Scatter Matplotlib Bars Matplotlib Histograms Matplotlib Pie Charts

Python SciPy

SciPy Intro SciPy Getting Started SciPy Constants SciPy Optimizers SciPy Sparse Data SciPy Graphs SciPy Spatial Data SciPy Matlab Arrays SciPy Interpolation SciPy Significance Tests

Machine Learning

Getting Started Mean Median Mode Standard Deviation Percentile Data Distribution Normal Data Distribution Scatter Plot Linear Regression Polynomial Regression Multiple Regression Scale Train/Test Decision Tree

Python MySQL

MySQL Get Started MySQL Create Database MySQL Create Table MySQL Insert MySQL Select MySQL Where MySQL Order By MySQL Delete MySQL Drop Table MySQL Update MySQL Limit MySQL Join

Python MongoDB

MongoDB Get Started MongoDB Create Database MongoDB Create Collection MongoDB Insert MongoDB Find MongoDB Query MongoDB Sort MongoDB Delete MongoDB Drop Collection MongoDB Update MongoDB Limit

Python Reference

Python Overview Python Built-in Functions Python String Methods Python List Methods Python Dictionary Methods Python Tuple Methods Python Set Methods Python File Methods Python Keywords Python Exceptions Python Glossary

Module Reference

Random Module Requests Module Statistics Module Math Module cMath Module

Python How To

Remove List Duplicates Reverse a String Add Two Numbers

Python Examples

Python Examples Python Compiler Python Exercises Python Quiz Python Certificate

Python - List Comprehension


List Comprehension

List comprehension offers a shorter syntax when you want to create a new list based on the values of an existing list.

Example:

Based on a list of fruits, you want a new list, containing only the fruits with the letter "a" in the name.

Without list comprehension you will have to write a for statement with a conditional test inside:

Example

fruits = ["apple", "banana", "cherry", "kiwi", "mango"]
newlist = []

for x in fruits:
  if "a" in x:
    newlist.append(x)

print(newlist)
Try it Yourself »

With list comprehension you can do all that with only one line of code:

Example

fruits = ["apple", "banana", "cherry", "kiwi", "mango"]

newlist = [x for x in fruits if "a" in x]

print(newlist)
Try it Yourself »


The Syntax

newlist = [expression for item in iterable if condition == True]

The return value is a new list, leaving the old list unchanged.


Condition

The condition is like a filter that accepts only the items that valuates to True.

Example

Only accept items that are not "apple":

newlist = [x for x in fruits if x != "apple"]
Try it Yourself »

The condition if x != "apple"  will return True for all elements other than "apple", making the new list contain all fruits except "apple".

The condition is optional and can be omitted:

Example

With no if statement:

newlist = [x for x in fruits]
Try it Yourself »

Iterable

The iterable can be any iterable object, like a list, tuple, set etc.

Example

You can use the range() function to create an iterable:

newlist = [x for x in range(10)]
Try it Yourself »

Same example, but with a condition:

Example

Accept only numbers lower than 5:

newlist = [x for x in range(10) if x < 5]
Try it Yourself »

Expression

The expression is the current item in the iteration, but it is also the outcome, which you can manipulate before it ends up like a list item in the new list:

Example

Set the values in the new list to upper case:

newlist = [x.upper() for x in fruits]
Try it Yourself »

You can set the outcome to whatever you like:

Example

Set all values in the new list to 'hello':

newlist = ['hello' for x in fruits]
Try it Yourself »

The expression can also contain conditions, not like a filter, but as a way to manipulate the outcome:

Example

Return "orange" instead of "banana":

newlist = [x if x != "banana" else "orange" for x in fruits]
Try it Yourself »

The expression in the example above says:

"Return the item if is not banana, if it is banana return orange".