Python List Comparison
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Overview
In the Python programming language, a list is defined as an ordered, modifiable container. A list can be used to hold objects that are similar in nature. When writing in Python, comparison is frequently used to check various conditions. For a single condition check, we may need to compare two variables or two sets of variables. In this blog, we will look at various methods for comparing two lists in Python. When comparing, we must determine whether or not both lists include the same components, regardless of the order in which the elements appear in the lists.
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Introduction
Before we begin, we will presume that you have successfully installed Python on your system and are familiar with the Python Fundamentals.
Let us take a step back and look at the List Data Structure, which is needed to understand python list comparison. If you're already familiar with it, go forward to the section "How to compare two lists in Python?" :::
What are Python Lists Exactly?
There are several data structures in Python, but the List is one of the most basic and significant. Along with the linear sequence, the List acts similarly to a dynamic array and has multiple built-in methods for performing different actions on data stored in it. The indexing of the List begins at zero and progresses up to (length of the List - 1). The List supports several operations such as adding, multiplying, slicing, membership, and comparing. Lists are used in Python to hold the series of distinct data type. Python lists are mutable, which means they can have their items changed after they've been created. Lists are one of four Python data structures for storing data collections; the other three are Tuple, Set, and Dictionary, each with its own set of attributes and uses.
Lists in Python, as you may know, are mutable and may store a finite amount of entries. Based on broad criteria, we cannot establish if a list is more or less than any other list. When we talk about comparing lists, we imply determining whether or not two lists contain the same entries.
How to Compare Two Lists in Python?
One of the most fundamental operations in every programming language is comparison. However, even a seemingly basic action can spark a slew of intriguing debates.
In most cases, throughout the development process, we need to compare the data elements in a list. Comparison is an approach for comparing the data element of one list to the data element of another list.
It turns out that comparing two lists in Python is quite stressful, but don't worry, I've got you covered. In this blog, we will explore numerous approaches to compare two lists.
Method 1 : Simple Comparison
The l1 == l2 operator for element-wise comparison is the most Pythonic approach to verify if two ordered lists l1 and l2 are identical. The return result is True if all entries are equal and the lengths of the lists are the same. This comparison approach works well for simple scenarios, but it does not work for sophisticated comparisons, as we will see later.
A list of integer or string objects is an example of a basic case.
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Fairly straightforward, yes?
Exception : Unfortunately, the world, like production quality code, is complicated. Things get difficult quickly in the real world. Consider the following scenarios as examples.
Assume you have a dynamically generated list of floating points. You can combine single element or floating point numbers obtained from mathematical operations like 0.1 + 0.2 + 0.1.
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Clearly, floating point mathematics has limits, and there are occasions when we wish to compare two lists while ignoring precision problems or even specifying a threshold. The == operator will not be sufficient in this scenario.
Using == is not the answer in every circumstance; yet, for certain specific problems, it is! The equality operator == compares a list element by element.
Method 2 : First Sorting and Then Using == Operator
In Python, you can sort lists in two methods. The first is to use the list.sort() method, and other we may use the sorted() function.
The first approach sorts a list in place, which implies that your list will be altered. It is best not to change an existing list because this might bring flaws that are difficult to discover.
The sorted() method is preferable since it returns a new list while leaving the original unchanged.
With the aid of an example, let's see how it works.
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As a result, by sorting the lists first, we ensure that they have the same order and can thus be compared using the == operator.
Method 3 : Using for Loop
The following approach might be used by a developer entering from another programming language or by a newbie who is unfamiliar with the equality operator on lists.
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You loop through all indices from 0 to (the length of the smallest list - 1) , as defined by the component min(len(l1), len(l2). Then you check to see if both components in the same place are different. If they differ, i.e., l1[i]!= l2[i], you may return False right away because the lists vary.
The list components are comparable if you ran through the entire loop without returning False. However, one list may be even longer! So, by returning len(l1) == len(l2), you guarantee that you only return True if all entries are identical and the lists have the same length. A ton of code to do something so easy! Let's have a look at a better approach by utilizing the zip() method to minimize code complexity.
Method 4 : Using zip() Function Along with for Loop
The zip function accepts a list of iterables and combines their i-th values into a tuple for each i.
Let's look at how we can leverage zip() method to make the prior code shorter:
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You now iterate over pairs of items rather than indices (the ones zipped together). If the lists are of varying lengths, the remaining entries from the longer list will be skipped. This simplifies element-wise comparison and eliminates the need for complex indexing techniques.
Method 5 : cmp() Function
Note : The cmp() function is not supported in Python 3.x.
The cmp() function is a Python built-in mechanism for comparing the items of two lists. The function can also compare two items and return a result based on the inputs provided. This return value can be one of three things: 1, 0 or -1.
For instance, if l1 and l2 are two lists, then value 1 is returned if l1 (list 1) is greater than l2 (or list2). If l1 is smaller than l2, the value -1 is returned; otherwise, the value 0 is returned. Let us now look at an example. Code :
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Method 6 : Using map() Function Along With reduce() Function
The map() method in Python takes as inputs a function and a Python iterable object (list, tuple, string, etc.) and produces a map object. The function applies to each list element and returns an iterator as a result.
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Furthermore, python has a method named reduce() that allows us to condense a list. The reduce() method recursively applies the specified function to the iterable object. To utilize the reduce() method, we must first import the functool module.
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To compare two lists, we can utilize both approaches simultaneously. The map() method would apply the function to each iterable object, and the reduce() function would handle that recursively. Consider the following example.
Note : Before utilizing these methods, you must sort the lists.
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Note : A lambda function is a small anonymous function. A lambda function can have an unlimited number of parameters but only one expression.
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The map() function in the above example combines all pairs of items to Boolean values; it examines if the two elements are equal or not. The reduce() method performs an and operation on all Boolean values.
Method 7 : Using collections.Counter()
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To effectively compare lists, use the collection.counter() function. The Python Counter class is included in the Collections module. It is a Dictionary subclass. It keeps track of items as dictionary keys and their counts as dictionary values. Using this, we can calculate the frequency of each element in a list and use the == operator to determine whether two lists are identical.
Note : The ordering of the lists has no influence on the counter() function.
Let us now look at an example. Code :
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Method 8 : Using difference() function
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We also use the difference() method to compare the list. The difference() function delivers the difference between two sets as a set. The returned set includes things that only exist in the first set and not in both.
To utilize the difference() function, we must first transform our list to sets.
So, What Exactly is 'Set'?
Set is one of Python's four built-in data types for storing data collections. A set is an unordered, immutable, and unindexed collection. In Python, the set() method takes an input and converts it into a set object. It accepts parameters like lists, tuples, and dictionaries. Because the items supplied as a list were not in order, the output of elements may not be in the same order. Two elements with the same value cannot exist in a set.
Consider the following example:
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In the above example, we first use the set() function to transform a list into a set, then we use the difference() function to differentiate between these two sets, and last we use the if() condition to check the return value.
This brings us to the end of the blog. You appear to have mastered a few Python list comparison techniques.The optimum strategy is determined on the type of pieces we have and how we want to compare them.
Click here, to know more about Sets in Python.
Explore Scaler Topics Python Tutorial and enhance your Python skills with Reading Tracks and Challenges.
Conclusion
This article taught you about:
- An overview of the python list.
- How to compare Python lists with the == operation
- How to compare lists in Python using sorting and the == operator
- How to compare lists in Python using the map() function and the reduce() function
- To compare Python Lists, utilize the cmp(), collections.Counter(), and difference() functions.