A Beginner’s Guide to Python List Methods

Introduction

Python is a very user-friendly yet powerful programming language, which is why it is used so prolifically in data science for data analysis and building machine learning algorithms, in deep learning to build neural network models, and even in software development for developing applications in python functions list or Python – List Methods.

One of Python’s unique points is that it supports various kinds of data structures like lists, tuples, dictionaries, etc., which in turn come with a plethora of in-built methods making solving programming challenges with Python extremely easy. But unfortunately, newcomers and even veteran Python programmers aren’t aware of all of these methods.

I am going to pick one of these data structures, Python lists, and focus on all the must-know methods and functions that come in handy when solving problems with lists. So, by the end of this article, whether you are a data scientist or a hard-core programmer, you will come out armed with a solid knowledge of Python lists which will make your next task in Python much easier.

Learning Objectives

• Look at the basics of Python lists.
• Understand the difference between functions and methods in Python.
• Cover the must-know functions and methods when working with Python lists.

This article was published as a part of the Data Science Blogathon.

What Are Python Lists?

Python lists are the primary and certainly the foremost common container.

• A Python list is defined as an ordered, mutable, and heterogeneous collection of objects.
• Order here implies that the gathering of objects follows a particular order.
• Mutable means the list can be mutated or changed.
• Heterogeneous implies that you’ll be able to mix and match any kind of object, or data type, within a List like an integer, string, or even another list.
• Lists are contained within a collection of square brackets [ ] and each element is separated by a comma.
• Lists are iterable objects. Meaning we can iterate over all the elements in a list.
• Lists are like dynamically sized arrays found in other programming languages like C++ or Java.

Python List Functions vs Python List Methods

In Python, a Function may be passed input parameters and may or may not return a result. Method, on the other hand, maybe passed off as an object instance and may or may not result in the expected output. The key difference between the two is that Functions may take objects as inputs while Methods, in contrast, act on objects. So, while all methods are functions in the Python programming language, not all functions are methods.

Also Read- Python Interview Questions to Ace Your Next Job Interview in 2024

Must-Know Python List Methods and Functions

Creating a Python List Using the list() Function

Before we look at the functions and methods for Python lists, let’s first see how to create a list in Python.

The list() function allows us to create a list in Python. It takes an iterable as a parameter and returns a list. This iterable can be a tuple, a dictionary, a string, or even another list.

# sample iterables
sample_tuple = (1,2,3,4)
sample_dict = {'a': 1, 'b': 2, 'c': 3}
sample_string = 'hello'

# converting to list
print('tuple to list', list(sample_tuple))
print('dict to list', list(sample_dict))
print('string to list', list(sample_string))

Here is how the output would look like:

[1,2,3,4]
['a', 'b', 'c', 'd']
['h', 'e', 'l', 'l', 'o']

Now let’s see all the functions and methods supported by Python lists, one by one, with the help of examples.

sort() method

The sort() method is a built-in Python method that, by default, sorts the list in ascending order. However, you’ll modify the order from ascending to descending by specifying the sorting criteria.

Example

Let’s say you would like to sort the elements of the product’s prices in ascending order. You’d type prices followed by a . (period) followed by the method name, i.e., sort, including the parentheses. Check out the syntax for it in the following lines of code –

Python Code:

#You can try the codes here

prices = [589.36, 237.81, 230.87, 463.98, 453.42] 
prices.sort() 
print(prices)

type() function

For the type() function, it returns the class type of an object.

Example

In this example, we will see the data type of the formed container.

fam = ["abs", 1.57, "egfrma", 1.768, "mom", 1.71, "dad"]
type(fam)

Output:

list

append() method

The append() method will add some elements you enter to the end of the elements you specified.

Example

In this example, let’s increase the length of the string by adding the element “April” to the list. Therefore, the append() function will increase the length of the list by 1.

months = ['January', 'February', 'March'] 
months.append('April') 
print(months)

Output:

['January', 'February', 'March', 'April']

We can iterate over each element in the list using a for-loop –

for element in months:
    print(element)

Output:

January
February
March
April

extend() method

The extend() method increases the length of the list by the number of elements that are provided to the strategy, so if you’d prefer to add multiple elements to the list, you will be able to use this method.

Example

In this example, we extend our initial list having three objects to a list having six objects.

list = [1, 2, 3] 
list.extend([4, 5, 6]) 
list

Output:

[1, 2, 3, 4, 5, 6]

index() method

The index() method returns the primary appearance of the required value.

Example

In the below example, let’s examine the index of February within the list of months.

months = ['January', 'February', 'March', 'April', 'May'] 
months.index('March')

Output:

2

max() function

The max() function is a built-in function in Python that returns the largest value from the values that are input.

Example

In this example, we’ll look to use the max() function for hunting out the foremost price within the list-named price.

prices = [589.36, 237.81, 230.87, 463.98, 453.42] 
price_max = max(prices) 
print(price_max)

Output:

589.36

min() function

The min() function is another in-built Python function that returns the rock bottom value from the input values.

Python list methods with examples

In this Example, you will find the month with the tiniest consumer indicator (CPI).

To identify the month with the tiniest consumer index, you initially apply the min() function on prices to identify the min_price. Next, you’ll use the index method to look out for the index location of the min_price. Using this indexed location on months, you’ll identify the month with the smallest consumer indicator.

months = ['January', 'February', 'March'] 
prices = [238.11, 237.81, 238.91]

# Identify min price 
min_price = min(prices) 
 # Identify min price index 
min_index = prices.index(min_price) 
 # Identify the month with min price 
min_month = months[min_index] 
print[min_month]

Output:

February

len() function

The len() function takes the list as input and returns the number of elements in a specified list.

Example

In the below example, we are going to take a look at the length of the 2 lists using this function.

list_1 = [50.29] 
list_2 = [76.14, 89.64, 167.28] 
print('list_1 length is ', len(list_1)) 
print('list_2 length is ', len(list_2))

Output:

list_1 length is 1
list_2 length is 3

clear() method

The clear() method removes all the elements from a specified list and converts them to an empty list.

Example

In this example, we’ll remove all the elements from the month’s list and make it empty.

months = ['January', 'February', 'March', 'April', 'May'] 
months.clear()

Output:

 [ ]

insert() method

The insert() method inserts the required value at the desired position.

Example

In this example, we’ll Insert the fruit “pineapple” at the third position of the fruit list.

fruits = ['apple', 'banana', 'cherry']
fruits.insert(2, "pineapple")

Output:

['apple', 'banana', 'pineapple', 'cherry']

count() method

The count() method returns the number of elements with the desired value.

Example

In this example, we are going to return the number of times the fruit “cherry” appears within the list of fruits.

fruits = ['cherry', 'apple', 'cherry', 'banana', 'cherry']
x = fruits.count("cherry")

Output:

3

pop() method

The pop() method removes the element at the required position.

Example

In this example, we are going to remove the element that’s on the third location of the fruit list.

fruits = ['apple', 'banana', 'cherry', 'orange', 'pineapple']
fruits.pop(2)

Output:

['apple', 'banana', 'orange', 'pineapple']

remove() method

The remove() method removes the first occurrence of the element with the specified value.

Example

In this example, we will Remove the “banana” element from the list of fruits.

fruits = ['apple', 'banana', 'cherry', 'orange', 'pineapple']
fruits.remove("banana")

Output:

['apple', 'cherry', 'orange', 'pineapple']

reverse() method

The reverse() method reverses the order of the elements.

Example

In this example, we will reverse the order of the fruit list so that the first element in the initial list becomes last and vice-versa in the new list.

fruits = ['apple', 'banana', 'cherry', 'orange', 'pineapple']
fruits.reverse()

Output:

['pineapple', 'orange', 'cherry', 'banana', 'apple']

copy() method

The copy() method returns a copy of the specified list and makes a new list.

Example

In this example, we want to create a list having the same elements as the list of fruits.

fruits = ['apple', 'banana', 'cherry', 'orange']
x = fruits.copy()

Output:

['apple', 'banana', 'cherry', 'orange']

filter() function

With the filter() function in Python, we can provide an iterable and the condition on which we want to filter out the data in the iterable. The filter() function then returns an iterator of filtered elements.

Let’s take a sample dataset in a list and filter out elements from it. Say, we take numbers from 1 to 10 and filter out even numbers from the list.

Let’s first define a function that filters out the elements.

def filter_func(num):
     if num%2==0:
         return num
     else:
         return

Now, let’s use the filter() function to filter out the elements from the list.

filtered_output = filter(filter_func, [1,2,3,4,5,6,7,8,9,10])

Let’s put the filtered output in a list and print it.

list(filtered_output)

Here is the output that you will get.

[2, 4, 6, 8, 10]

Conclusion

So in this article, we got acquainted with the various functions and Python Lists methods. We covered the basics and looked at the implementation of the most important functions and methods. These come in handy whether you are doing analysis on datasets as Data Analyst or whether you are building machine learning models as a Data Scientist.

Key Takeaways

• A Python list is defined as an ordered, mutable, and heterogeneous collection of objects. They are defined within square brackets [ ] and each element in the list is separated by a comma.
• Python list functions may take objects as inputs, while methods, in contrast, act on objects.
• List methods in Python include append(), sort(), remove(), index(), etc., whereas max(), min(), filter(), len(), etc. are Python list functions.

If you found this article useful, I encourage you to read the following related articles on Analytics Vidhya’s blog:

• List comprehensions in Python
• Must know built-in functions in Python
• Lambda functions in Python

Frequently Asked Questions

The media shown in this article are not owned by Analytics Vidhya and are used at the Author’s discretion.