Recently, in a Python webinar, someone asked me a question about splitting lists. After researching and testing various methods, I found a few important methods to achieve this task. In this tutorial, I will explain how to split a list in Python with suitable examples and screenshots.
Split a List in Python
One of the simplest ways to split a list in Python is by using the slicing operator (:). Slicing allows you to extract a portion of a list by specifying the start and end indices. Here’s an example:
states = ["California", "Texas", "Florida", "New York", "Illinois", "Pennsylvania", "Ohio", "Georgia", "North Carolina", "Michigan"]
west_coast = states[:3]
east_coast = states[3:6]
midwest = states[6:]
print("West Coast states:", west_coast)
print("East Coast states:", east_coast)
print("Midwest states:", midwest)Output:
West Coast states: ['California', 'Texas', 'Florida']
East Coast states: ['New York', 'Illinois', 'Pennsylvania']
Midwest states: ['Ohio', 'Georgia', 'North Carolina', 'Michigan']You can see this in the screenshot below.
In this example, we split the states list into three sublists using slicing:
west_coast: Contains the first three elements of thestateslist (indices 0 to 2).east_coast: Contains the next three elements (indices 3 to 5).midwest: Contains the remaining elements (index 6 to the end).
Slicing is a quick and easy way to split a list when you know the specific indices you want to use for the split. Slicing is the simplest way to split a list in Python.
Read How to Print Lists in Python?
1. Use a Specific Value
Sometimes, you may want to split a list based on a specific value rather than using indices. For example, let’s say you have a list of US state information where each element contains the state name and its capital, separated by a tab character:
state_info = ["California\tSacramento", "Texas\tAustin", "Florida\tTallahassee", "New York\tAlbany", "Illinois\tSpringfield"]To split this list into separate lists for state names and capitals, you can use the split() method with the tab character as the delimiter:
state_names = []
state_capitals = []
for info in state_info:
name, capital = info.split("\t")
state_names.append(name)
state_capitals.append(capital)
print("State names:", state_names)
print("State capitals:", state_capitals)Output:
State names: ['California', 'Texas', 'Florida', 'New York', 'Illinois']
State capitals: ['Sacramento', 'Austin', 'Tallahassee', 'Albany', 'Springfield']You can see this in the screenshot below.
In this example, we iterate through each element of the state_info list, split it at the tab character, and append the resulting state name and capital to separate lists.
Check out How to Convert a List to a Set in Python?
2. Use List Comprehension
List comprehension is a concise and efficient way to create new lists based on existing lists. You can use list comprehension to split a list by applying a condition or transformation to each element. Here’s an example:
names = ["John Smith", "Emily Johnson", "Michael Davis", "Emma Brown", "Christopher Wilson"]
first_names = [name.split()[0] for name in names]
last_names = [name.split()[-1] for name in names]
print("First names:", first_names)
print("Last names:", last_names)Output:
First names: ['John', 'Emily', 'Michael', 'Emma', 'Christopher']
Last names: ['Smith', 'Johnson', 'Davis', 'Brown', 'Wilson']You can see this in the screenshot below.
In this example, we have a list of full names (names). We use list comprehension to split each name into its first and last name components:
first_names: We applyname.split()[0]to eachnamein thenameslist, extracting the first element of the resulting split (the first name).last_names: We applyname.split()[-1]to eachname, extracting the last element of the resulting split (the last name).
Read How to Get Unique Values from a List in Python?
Advanced List Splitting Techniques
Let us learn some important advanced list splitting techniques:
Split a List into Chunks of Equal Size
Sometimes, you may need to split a list into chunks of equal size. For example, if you have a large dataset of US cities and want to process them in smaller batches. Python’s built-in zip() function, along with the iter() function and list slicing, can be used to achieve this. Here’s an example:
cities = ["New York", "Los Angeles", "Chicago", "Houston", "Phoenix", "Philadelphia", "San Antonio", "San Diego", "Dallas", "San Jose"]
def split_into_chunks(lst, chunk_size):
return [lst[i:i + chunk_size] for i in range(0, len(lst), chunk_size)]
city_chunks = split_into_chunks(cities, 3)
print("City chunks:")
for chunk in city_chunks:
print(chunk)Output:
City chunks:
['New York', 'Los Angeles', 'Chicago']
['Houston', 'Phoenix', 'Philadelphia']
['San Antonio', 'San Diego', 'Dallas']
['San Jose']In this example, we define a function called split_into_chunks() that takes a list (lst) and a chunk size (chunk_size) as arguments. The function uses list comprehension to create a new list of sublists, where each sublist contains chunk_size elements from the original list.
We then call split_into_chunks() with the cities list and a chunk size of 3, splitting the list into chunks of 3 cities each. The resulting city_chunks list contains the sublists of cities.
Check out How to Replace Values in a List Using Python?
Split a List Based on a Condition
In some cases, you may want to split a list based on a specific condition. For example, let’s say you have a list of US states and their populations, and you want to split the list into two sublists: one for states with a population above a certain threshold and another for states below that threshold.
state_populations = [
("California", 39512223),
("Texas", 28995881),
("Florida", 21477737),
("New York", 19453561),
("Illinois", 12671821),
("Pennsylvania", 12801989),
("Ohio", 11689100),
("Georgia", 10617423),
("North Carolina", 10488084),
("Michigan", 9986857)
]
threshold = 15000000
high_population_states = [state for state in state_populations if state[1] > threshold]
low_population_states = [state for state in state_populations if state[1] <= threshold]
print("High population states:")
for state in high_population_states:
print(state)
print("\nLow population states:")
for state in low_population_states:
print(state)Output:
High population states:
('California', 39512223)
('Texas', 28995881)
('Florida', 21477737)
('New York', 19453561)
Low population states:
('Illinois', 12671821)
('Pennsylvania', 12801989)
('Ohio', 11689100)
('Georgia', 10617423)
('North Carolina', 10488084)
('Michigan', 9986857)In this example, we have a list of tuples called state_populations where each tuple contains a state name and its population. We define a population threshold of 15,000,000.
We use list comprehension to create two new lists:
high_population_states: Contains states with a population above the threshold.low_population_states: Contains states with a population less than or equal to the threshold.
We then print the resulting sublists, separating the high and low population states.
Read How to Shuffle a List in Python?
Conclusion
In this tutorial, I explored various techniques to split a list in Python. I discussed using the slicing operator (:) , using a specific value , and using list comprehension. I also covered advanced list splitting techniques, such as splitting a list into chunks of equal size and splitting a list based on a condition.
You may read:
- How to Remove Duplicates from a List in Python?
- How to Randomly Select from a List in Python?
- How to Convert a Dictionary to a List in Python?
Bijay Kumar is an experienced Python and AI professional who enjoys helping developers learn modern technologies through practical tutorials and examples. His expertise includes Python development, Machine Learning, Artificial Intelligence, automation, and data analysis using libraries like Pandas, NumPy, TensorFlow, Matplotlib, SciPy, and Scikit-Learn. At PythonGuides.com, he shares in-depth guides designed for both beginners and experienced developers. More about us.
