Are you confused about when to use a list and when to use an array in Python? Well, you’re not alone. In this blog post, we’ll clear up the confusion and show you when to use each data structure.
Python’s built-in data structures (lists, tuples, and dictionaries) are incredibly versatile, but sometimes you need something a little different. In this article, we’ll take a look at two ways to convert between arrays and lists in Python.
The first way is to use the built-in list() function. This function takes an iterable (something you can loop over, like a list, tuple, or string) and converts it into a list:
>>> my_list = [1, 2, 3]
>>> my_array = array.array(‘i’, my_list)
>>> my_list2 = list(my_array)
[1, 2, 3]
Python array vs list
In Python, there are two ways to store data: arrays and lists. Both of these data structures are similar in that they store a collection of data, but they each have their own specific use cases.
Arrays are designed to store a fixed-size collection of data, whereas lists can store a variable number of elements. Lists are also able to store data of different types, whereas arrays can only store data of the same type.
So, when should you use an array and when should you use a list? The answer depends on the type and size of data you need to store, as well as the operations you need to perform on that data.
Arrays are best suited for storing and manipulating large amounts of numerical data. They amortize the cost of adding and removing elements at the end of the array, and they provide efficient indexing for random access to elements. However, arrays are not able to store data of different types, so they are not as flexible as lists.
Lists are best suited for storing and manipulating small amounts of data that need to be accessed sequentially. They do not provide efficient indexing like arrays, but they allow you to insert and remove elements at any position in the list. Lists also give you the flexibility to store data of different types in the same list.
Converting Between Arrays and Lists
Python lists and tuples are very similar, but there are a few key differences. A list is a mutable data structure, meaning that it can be changed after it’s created. A tuple is an immutable data structure, meaning it cannot be changed after it’s created.
Python arrays are structures that store multiple values of the same data type. Lists are one of the most commonly used data structures in Python, and they’re often used to hold strings. When you need to store a collection of strings in an array, you can use the list type.
However, sometimes you need to convert between the two data types. For example, if you have a list of integers and you want to convert it to an array of floats. To do this, you can use the built-in function map().
The map() function takes two arguments: a function and an iterable (usually a list). It then applies the function to each element in the iterable and returns a new iterable (usually a list) with the results. Here’s an example of how to use map() to convert a list of integers to a list of floats:
>>> my_list = [1, 2, 3]
>>> my_array = map(float, my_list)
[1.0, 2.0, 3.0]
Similarly, if you have an array of floats and you want to convert it to a list, you can use map():
>>> my_list = [100.54321, 103.12345] # note that these values are stored as strings!
If we didn’t convert them back to floats here we’d end up with integer division later on which would give us results like 100 instead of 100.5
>>> my_arr = map(int, my_list) # converts back into integers
>>> my_arr # note that now they’re ints again!
[100 , 103 ]
Why Convert Between Arrays and Lists?
In many cases, there is no need to convert between arrays and lists in Python; since Lists are implemented as arrays, they can be used interchangeably in most circumstances. However, there are some reasons why you might want to make the conversion.
One common reason is that some Python libraries work better with one type or the other. For example, the NumPy library is designed for efficient manipulation of arrays, and will usually give better performance when working with arrays rather than lists. In other cases, you may need to convert between types to use a particular library.
Another reason for conversion is that lists can be modified after creation, while arrays cannot. This means that if you need to add or remove elements from a list, you can do so without having to recreate the entire list; with an array, you would have to recreate the entire array (or use a different data structure that supports modification).
When to Convert Between Arrays and Lists?
In general, you should only convert between arrays and lists when absolutely necessary. There are some key differences between arrays and lists:
– Arrays can only store data of a single type. Lists can store data of multiple types.
– Arrays are designed to be compact, so they’re useful when memory is at a premium. Lists take up slightly more memory than arrays, but not enough to usually be a concern.
– Arrays are faster than lists for many operations, including lookups by index and numerical operations like matrix multiplication.
– Lists have built-in methods for many common tasks, like adding/removing items, finding the length of the list, and sorting the list. Arrays do not have equivalent methods.
If you’re working with data that can all be stored as a single type, and you need to perform lots of numerical operations on that data, then an array is probably your best bet. If you’re working with data of mixed types that you need to manipulate in various ways, then a list is probably a better choice.
How to Convert Between Arrays and Lists?
In Python, there are two platforms that you can use to store data: arrays and lists. Arrays are faster than lists, but they are also more limited. You can’t add or remove items from an array, but you can do so with a list. You also can’t sort an array, but you can sort a list. If you need to convert between arrays and lists, there are a few different ways that you can do so. The first is to use the built-in functions in the Python standard library. The second is to use the NumPy library. The third is to use the pandas library. Let’s take a look at how to convert between arrays and lists using each of these methods.
If you want to learn more about the difference between arrays and lists in Python, here are a few resources you can check out:
-The official documentation on Lists and Tuples
-A tutorial on Lists and Tuples
-An article comparing Lists and Arrays