{ "source_file": "0930", "source_platform": "Medium", "author": "Federico Trotta", "title_listed": "Python Lists: The Definitive Guide for Working With Ordered Collections of Data", "keywords": "Python,列表,数据结构", "domain": "数据处理", "content_type": "深度技术解析", "is_paid_flag": "部分免费/会员墙", "url": "https://towardsdatascience.com/python-lists-the-definitive-guide-for-working-with-ordered-collections-of-data-53b06a194826/", "publish_date": "2023-07", "corpus_stage": "预训练/SFT", "notes": "", "id": "30b9b64214f0", "collected_at": "2026-10-02T00:40:12", "title": "Python Lists: The Definitive Guide for Working With Ordered Collections of Data | Towards Data Science", "body_markdown": "![Revisit consent button](https://cdn-cookieyes.com/assets/images/revisit.svg)\nWe value your privacy\nWe use cookies to enhance your browsing experience, serve personalised ads or content, and analyse our traffic. 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It also helps in adverstising on the website.\n\n\n * Cookie\nedgebucket\n * Duration\nsession\n * Description\nReddit sets this cookie to save the information about a log-on Reddit user, for the purpose of advertisement recommendations and updating the content.\n\n\n * Cookie\ndid\n * Duration\n1 year\n * Description\nArbor sets this cookie to show targeted ads to site visitors.This cookie expires after 2 months or 1 year.\n\n\nUncategorised\nOther uncategorised cookies are those that are being analysed and have not been classified into a category as yet.\nNo cookies to display.\nReject All Save My Preferences Accept All\nToggle Search[](https://towardsdatascience.com/)Toggle Mobile Navigation\n[](https://towardsdatascience.com/)\nPublish AI, ML & data-science insights to a global community of data professionals.\nSign in[Submit an Article](https://write.insightmediagroup.io)\n[Latest](https://towardsdatascience.com/latest/)[Editor's Picks](https://towardsdatascience.com/tag/editors-pick/)[Newsletter](https://towardsdatascience.com/tag/the-variable/)[ShipAI](https://towardsdatascience.com/shipai/)\n* * *\n[Write For TDS](https://towardsdatascience.com/submissions/)\n[LinkedIn](https://www.linkedin.com/company/towards-data-science/)[X](https://x.com/TDataScience)Toggle Search\n[Artificial Intelligence](https://towardsdatascience.com/category/artificial-intelligence/)\n# Python Lists: The Definitive Guide for Working With Ordered Collections of Data\nA comprehensive guide on lists in Python\n[Federico Trotta](https://towardsdatascience.com/author/federicotrotta/)\nJuly 19, 202311 min read\n![](https://assets.insightmediagroup.io/media/wp-content/uploads/2023/07/1ykoOnRpQPHq46AjbS5CNeg.jpeg)\nWhen programming, we always have to deal with data structures. What I mean is that we need to store information somewhere so that we can reuse it later.\nPython is a very flexible programming language and gives us the possibility to use different types of data structures.\nIn this article, we'll analyze Python lists. So, if you're a beginner in Python and are searching for a comprehensive guide on lists, then this article is definitely for you.\nHere's what you'll learn here:\ntext\n\n```\nTable of Contents:\n\nWhat is a list in Python?\nThe top 9 features in Python lists, with examples\n How to create a list in Python\n Accessing list elements\n Modifying the elements of a list\n Adding elements to a list\n Removing elements from a list\n Concatenating lists\n Calculating the lenght of a list\n Sorting the elements of a list\n List comprehension\n```\n\n* * *\nLearn this step by step with the interactive [AI Engineer](https://roadmap.sh/ai-engineer), [AI and Data Scientist](https://roadmap.sh/ai-data-scientist) and [Computer Science](https://roadmap.sh/computer-science) roadmaps.\n## What is a list in Python?\nIn Python, a list is a built-in data structure that allows us to store and manipulate data in the form of text or numbers.\nLists store data in an ordered way, meaning that the elements of a list can be accessed by their position.\nLists are also a modifiable kind of data structure, as opposed to [tuples](https://towardsdatascience.com/lists-tuples-dictionaries-and-data-frames-in-python-the-complete-guide-7ab54d4819ee).\nFinally, lists can also store duplicated values without raising errors.\n## The top 9 features in Python lists, with examples\nThe best way to learn Python is by putting our fingers on the keyboard and, possibly, solving an actual problem.\nSo, now we'll show the 9 top features of Python lists with code examples because, as we'll see, theory doesn't have much sense in programming: we just need to code and solve problems.\n### How to create a list in Python\nTo create a list, we need to use square brackets:\ntext\n\n```\n# Create a simple list\nnumbers = [1,2,3,\"dog\",\"cat\"]\n\n# Show list\nprint(numbers)\n\n>>>\n\n[1, 2, 3, 'dog', 'cat']\n```\n\nAnother way to create a list is by using the built-in method `list`. For example, suppose we want to create a list of numbers ranging from 0 to 9. We can use the built-in method `range` to create the range, then we can pass it as an argument to the method `list` to create the list like so:\ntext\n\n```\n# Create a list in the range\nlist_range = list(range(10))\n\n# Show list\nprint(range_list)\n\n>>>\n\n[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n```\n\nAlso, we can create the so-called list of lists that are nothing more than nested lists. For example, suppose we want to store the data related to measured times, in seconds, of people running. If we need these data as a list we can create a list of lists like so:\ntext\n\n```\n# Create a list of lists\ntimes = [[\"Jhon\"], [23, 15, 18], [\"Karen\"], [17, 19, 15],\n [\"Tom\"], [21, 19, 25]]\n\n# Print list\nprint(times)\n\n>>>\n\n[['Jhon'], [23, 15, 18], ['Karen'], [17, 19, 15], ['Tom'], [21, 19, 25]]\n```\n\n### Accessing list elements\nThe elements of a list can be accessed by their positions. What we need to remember is that in Python we start counting from 0. This means that the first element is accessed with a 0:\ntext\n\n```\n# Create a list of elements\nvalues = [1,2,3,\"dog\",\"cat\"]\n\n# Print elements by accessing them\nprint(f\"The first element is: {values[0]}\")\nprint(f\"The fourth element is: {values[3]}\")\n\n>>>\n\nThe first element is: 1\nThe fourth element is: dog\n```\n\nSo, we just need to take care to make the right counting.\nAccessing a list of lists is a little bit more complicated, but is not hard. We first need to access the position related to the external list, then we count in the internal one.\nAs we've said, practice is better than theory in Python. So, let's show this concept with an example:\ntext\n\n```\n# Create a list of lists\ntimes = [[\"Jhon\"], [23, 15, 18], [\"Karen\"], [17, 19, 15],\n [\"Tom\"], [21, 19, 25]]\n\n# Print\nprint(f\"The first runner is:{times[0]}.nHis first registered time is:{times[1][0]}nThe min registered time is:{min(times[1])}\")\n\n>>>\n\nThe first runner is:['Jhon'].\nHis first registered time is:23\nThe min registered time is:15\n```\n\nJhon is the first registered runner, so we access it with `times[0]`.\nThen, we want to calculate his first registered time. To do so, we have to type `times[1][0]` because: `[1]` refers to the second position, with respect to the external list. Meaning that we've accessed the internal list `[23, 15, 18]`. Finally, the `[0]` accesses the first number of the internal list which, indeed, is 23.\n### Modifying the elements of a list\nAs we've said, lists are modifiable and to modify an element of a list we need to access it.\nSo, let's make an example:\ntext\n\n```\n# Create a list of numbers\nnumbers = [1, 2, 3, 4, 5]\n\n# Modify the third element\nnumbers[2] = 10\n\n# Print new list\nprint(numbers)\n\n>>>\n\n[1, 2, 10, 4, 5]\n```\n\nSo, in this case, we've modified the third element changing it from 3 to 10.\nBut we can also modify text. In particular, sentences. Let's see an example:\ntext\n\n```\n# Create a sentence in a list\nsentence = list(\"Hello, World!\")\n\n# Substitute \"world\" with \"Python\"\nsentence[7:] = list(\"Python!\")\n\n# Print sentence\nprint(''.join(sentence))\n\n>>>\n\n\"Hello, Python!\"\n```\n\nSo, here we've substituted all the letters in our list \"sentence\" from the seventh (make the count start from 0, as we've said before) element to the last one with `sentence[7:]`.\nWe've, then, used the method `''.join(sentence)` to print the sentence as a whole one. In fact, if we'd just used `print()` it would print the letters as single elements like so:\ntext\n\n```\nprint(sentence)\n\n>>>\n\n['H', 'e', 'l', 'l', 'o', ',', ' ', 'P', 'y', 't', 'h', 'o', 'n', '!']\n```\n\n### Adding elements to a list\nSince lists are mutable, we can add new elements to them, if we need it and we have a couple of methods to do so.\nThe first one is to use the `append()` method which is particularly suitable if we need to add just one element to a list. For example:\ntext\n\n```\n# Create a list with fruits\nfruits = ['apple', 'banana']\n\n# Append the element \"orange\" to the list\nfruits.append('orange')\n\n# Print list\nprint(fruits)\n\n>>>\n\n['apple', 'banana', 'orange']\n```\n\nAnother way to add elements to an existing list is by using the `extend()` method which is particularly suitable if we need to append more than one element at a time. For example, like so:\ntext\n\n```\n# Create a list of numbers\nnumbers = [1, 2, 3, 4, 5]\n\n# Extend the list with new numbers\nnumbers.extend([6, 7, 8])\n\n# Print list\nprint(numbers)\n\n>>>\n\n[1, 2, 3, 4, 5, 6, 7, 8]\n```\n\n### Removing elements from a list\nThanks to mutability, we can add elements to a list but we can even remove elements.\nAlso here, we have two ways to do so: we can use the slicing possibility or we can directly specify an element to delete.\nLet's see these with Python examples:\ntext\n\n```\n# Create a list with fruits\nfruits = ['apple', 'banana', 'orange']\n\n# Remove the element banana\nfruits.remove('banana')\n\n# Print list\nprint(fruits)\n\n>>>\n\n['apple', 'orange']\n```\n\nSo, the `remove()` method gives us the possibility to directly delete a specific element from a list by typing its value.\nThe other method we can use is to access the position of the element we want to remove like so:\ntext\n\n```\n# Create a list of numbers\nnumbers = [1, 2, 3, 4, 5]\n\n# Delete on element: slicing method\npopped_element = numbers.pop(2)\n\n# Print\nprint(numbers) \nprint(f\"The deleted element is:{popped_element}\") \n\n>>>\n\n[1, 2, 4, 5]\nThe deleted element is:3\n```\n\nSo, the `pop()` method removes an element from a list by accessing its index.\nWhich one to use? It depends on the situation. If we have a very long list, it's generally a good idea to use the `remove()` method so that we directly write the element we actually want to remove, and we don't make mistakes in counting the indexes.\n### Concatenating lists\nThe mutability of lists gives us the possibility to perform numerous tasks, like concatenating multiple lists together in one single list.\nThis operation is simple and is performed with a `+` like so:\ntext\n\n```\n# Create a list\nlist1 = [1, 2, 3]\n\n# Create a second list\nlist2 = [4, 5, 6]\n\n# Concatenate list\ncombined_list = list1 + list2\n\n# Print cncatenated lists\nprint(combined_list)\n\n>>>\n\n[1, 2, 3, 4, 5, 6]\n```\n\nThis feature can, of course, be performed even with strings:\ntext\n\n```\n# Create a list\nhello = [\"Hello\"]\n\n# Create another list\nworld = [\"world\"]\n\n# Concatenate\nsingle_list = hello + world\n\n# Print concatenated\nprint(single_list)\n\n>>>\n\n['Hello', 'world']\n```\n\nAnother way to concatenate lists is to flatten a list of lists. In other words, we can create a single \"straight\" list from a nested list like so:\ntext\n\n```\n# Create a nested list\nlists = [[1, 2], [3, 4], [5, 6]]\n\n# Create a unique list\nflattened_list = sum(lists, [])\n\n# Print unique list\nprint(flattened_list)\n\n>>>\n\n[1, 2, 3, 4, 5, 6]\n```\n\nSo, basically, we've used the `sum()` method to get all the elements of the list `lists` and appended them to an empty list with `[]`.\n### Calculating the length of a list\nIn the previous examples, we've created lists ourselves to make Python examples about how to manipulate lists.\nHowever, when working with Python, it often happens that we retrieve data from different sources, meaning someone created a list we actually don't know anything about.\nThe first thing we'd better do when we are in front of an unknown list is to calculate its length. We can do it like so:\ntext\n\n```\n# Create a list\nfruits = ['apple', 'banana', 'orange']\n\n# Print list lenght\nprint(f\"In this list there are {len(fruits)} elements\")\n\n>>>\n\n In this list there are 3 elements\n```\n\nSo, the method `len()` calculates how many elements are in a list, without worrying about their type. This means that the elements can be all numbers, all strings, or both of them: the `len()` methods will count them all.\n### Sorting the elements of a list\nAnother action we may perform when we don't know a list is to sort its elements.\nWe have different methods to do so.\nLet's start with the `sort()` method:\ntext\n\n```\n# Creaye a list of numbers \nnumbers = [5, 2, 1, 4, 3]\n\n# Sort the numbers\nnumbers.sort()\n\n# Print sorted list\nprint(numbers)\n\n>>>\n\n[1, 2, 3, 4, 5]\n```\n\nSo, we can just pass the list as the argument to the `sort()` method and it will sort the elements.\nBut what if we want to sort a list containing strings? For example, suppose we want to sort the elements of a list in alphabetical order. We can do it like so:\ntext\n\n```\n# Create a list of strings\nwords = ['cat', 'apple', 'dog', 'banana']\n\n# Sort in alphabeticla order\nsorted_words = sorted(words, key=lambda x: x[0])\n\n# Print sorted list\nprint(sorted_words)\n\n>>>\n\n['apple', 'banana', 'cat', 'dog']\n```\n\nSo, in this case, we use the `sorted()` method where we have to specify:\n * The parameters regarding the list we want to sort. In this case, `words`.\n * The `key`. Which means we need to specify a methodology. In this case, we've used a lambda function that gets the first letter of each element with `x[0]` by iterating through all the elements: this is the way we can select the first letter for each word.\n\n\nAnother way to sort strings is to sort them by the number of characters for each element. In other words, suppose we want to have the shorter words at the beginning and the longest at the end of our list. We can do it like so:\ntext\n\n```\n# Create a list of words\nwords = ['cat', 'apple', 'dog', 'banana']\n\n# Sort words by lenght\nwords.sort(key=len)\n\n# Print sorted list\nprint(words)\n\n>>>\n\n['cat', 'dog', 'apple', 'banana']\n```\n\nSo, even with the `sort()` method we can pass a parameter `key`. In this case, we've chosen `len` which counts the length of each word. So, the list is now ordered starting with the shortest words and ending with the longest ones.\n### List comprehension\nList comprehension is a fast and concise way to create a new list using the power of loops and statements with one line of code.\nLet's see an example. Suppose we want to take the numbers ranging from 1 to 6 and create a list with their squared values. We can do it like so:\ntext\n\n```\n# Create a list of squared numbers\nsquares = [x ** 2 for x in range(1, 6)]\n\n# Print list\nprint(squares) \n\n>>>\n\n[1, 4, 9, 16, 25]\n```\n\nNow, we can reach the same result without using list comprehension but at the cost of a lot of code like so:\ntext\n\n```\n# Create empty list\nsquares = []\n\n# Iterate over the numbers in the range\nfor squared in range(1, 6):\n # Calculare squares and append to empty list\n squares.append(squared ** 2)\n\n# Print list \nprint(squares)\n\n>>>\n\n[1, 4, 9, 16, 25]\n```\n\nSo, we get the same result but list comprehension makes us reach it with just one line of code.\nWe can also use `if` statements in a list comprehension, making it way quicker and elegant than the \"standard method\", for which we'd need to iterate with a `for` loop, and then select the values we need with an `if` statement.\nFor example, suppose we want to create a new list of squared numbers, but we want only the ones that are even numbers. We can do it like so:\ntext\n\n```\n# Create a list with numbers in a range\nnumbers = list(range(1, 11))\n\n# Get the even squared numbers and create a new list\nsquared_evens = [x ** 2 for x in numbers if x % 2 == 0]\n\n# Print list with squared & even numbers\nprint(squared_evens)\n\n>>>\n\n[4, 16, 36, 64, 100]\n```\n\nSo, here we need to remember that to take even numbers we can use the fact that they are divisible by two. So, `x % 2 == 0` gets the numbers that, when divided by two, give a reminder of 0. Meaning: they're even numbers.\n* * *\n## Conclusions\nIn this article, we've shown a comprehensive guide on Python lists.\nLists are a very important and useful data structure. They're not hard to learn, but are a fundamental asset for every Python programmer.\n* * *\nI'm Federico Trotta and I'm a freelance Technical Writer.\nWant to collaborate with me? 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