{"id":1056,"date":"2023-04-06T21:45:00","date_gmt":"2023-04-06T16:15:00","guid":{"rendered":"https:\/\/geekpython.in\/?p=1056"},"modified":"2023-08-15T13:38:10","modified_gmt":"2023-08-15T08:08:10","slug":"python-sort-vs-sorted","status":"publish","type":"post","link":"https:\/\/geekpython.in\/python-sort-vs-sorted","title":{"rendered":"Difference Between sort() And sorted() In Python"},"content":{"rendered":"\n

We’ll compare the Python’s list sort()<\/code> and sorted()<\/code> functions in this article. We’ll learn about these functions, such as what they are and how they differ programmatically and syntactically.<\/p>\n\n\n\n

Python sort()<\/code> and sorted()<\/code> are used to sort the data in ascending or descending order. Their goals are the same but are used in different conditions.<\/p>\n\n\n\n

<\/a>sort()<\/h2>\n\n\n\n

The sort()<\/code> function is connected to the Python list and by default, sorts the list’s contents in ascending order<\/strong>.<\/p>\n\n\n\n

# List of names\ndata = ['Sachin', 'Yogesh', 'Yashwant', 'Rishu']\nprint(f'Original Data: {data}')\n\n# Using list.sort() function\ndata.sort()\n# Printing sorted data\nprint(f'Sorted Data: {data}')\n\n----------\nOriginal Data: ['Sachin', 'Yogesh', 'Yashwant', 'Rishu']\nSorted Data: ['Rishu', 'Sachin', 'Yashwant', 'Yogesh']<\/pre><\/div>\n\n\n\n
The code above sorts the names in ascending order within the list data<\/code>. That was the most fundamental use of the list sort()<\/code> function. We’ll see more examples where we’ll manipulate the function’s parameters.<\/p>\n\n\n\n
<\/a>Syntax<\/h3>\n\n\n\n
list.sort(reverse=False, key=None)<\/code><\/p>\n\n\n\n
Here<\/p>\n\n\n\n
reverse<\/code> – Defaults to False<\/code>. If reverse=True<\/code>, the data will be sorted in descending order<\/strong>.<\/p>\n\n\n\n
key<\/code> – Defaults to None<\/code>. We can specify a user-defined function<\/strong> to customize the sorting.<\/p>\n\n\n\n
<\/a>Examples<\/h3>\n\n\n\n
We’ll play around with these parameters and try with data having different data types to get a better understanding of this function.<\/p>\n\n\n\n
Example 1 – List having different characters<\/strong><\/p>\n\n\n\n
# Original List\ntyp_data = ['$', '45', '3j+5', 'Hello']\nprint(f'Original Data: {typ_data}')\n\n# Sorting the list\ntyp_data.sort()\n# Printing sorted list\nprint(f'Sorted Data: {typ_data}')\n\n----------\nOriginal Data: ['$', '45', '3j+5', 'Hello']\nSorted Data: ['$', '3j+5', '45', 'Hello']<\/pre><\/div>\n\n\n\n
Example 2 – List containing the different data types<\/strong><\/p>\n\n\n\n
In the following example, data<\/code> is a list that contains tuples<\/strong> and we sorted the data<\/code> in descending order.<\/p>\n\n\n\n
# List containing tuple data\ndata = [\n    ('Hey', 'There'),\n    ('Geeks', 'Welcome'),\n    ('To', 'GeekPython')\n]\n# Printing the type of list item\nprint(f'Type: {type(data[0])}')\n# Sorting the data in descending order\ndata.sort(reverse=True)\n# Printing modified data\nprint(data)\n\n----------\nType: <class 'tuple'>\nSorted Data: [('To', 'GeekPython'), ('Hey', 'There'), ('Geeks', 'Welcome')]<\/pre><\/div>\n\n\n\n
What if we specify a similar name for the first values of the tuple?<\/strong><\/p>\n\n\n\n
# List containing tuple data with first values having similar name\ndata = [\n    ('item', 2),\n    ('item', 1),\n    ('item', 3)\n]\n# Printing the type of list item\nprint(f'Type: {type(data[0])}')\n# Sorting the data in descending order\ndata.sort(reverse=True)\n# Printing modified data\nprint(f'Sorted Data: {data}')\n\n----------\nType: <class 'tuple'>\nSorted Data: [('item', 3), ('item', 2), ('item', 1)]<\/pre><\/div>\n\n\n\n
The tuples were sorted based on the second value because sort()<\/code> cannot perform sorting on similar values, or more specifically, how can data be sorted in ascending or descending order if they are all similar?<\/p>\n\n\n\n
Example 3 – Using a user-defined function<\/strong><\/p>\n\n\n\n
# List containing dictionary data\ndata = [\n    {'fruit': 'strawberry', 'price': 100},\n    {'fruit': 'banana', 'price': 91},\n    {'fruit': 'mango', 'price': 132},\n    {'fruit': 'cherry', 'price': 82},\n]\n\nprint(f'Original Data: {data}')\n\n# Function for sorting by key 'price'\ndef sort_dict_by_price(item):\n    return item['price']\n\n# Sorting data using the user-defined sorting function\ndata.sort(key=sort_dict_by_price)\nprint('-'*20)\n# Printing the data\nprint(f'Sorted Data: {data}')<\/pre><\/div>\n\n\n\n
We’ve written a function called sort_dict_by_price<\/code> that takes a parameter item<\/code>, which is our dictionary itself, and returns the values of the key 'price'<\/code>.<\/p>\n\n\n\n
This function was passed to the key<\/code> parameter, which will sort the data<\/code> based on the price<\/code> in ascending order.<\/p>\n\n\n\n
Output<\/strong><\/p>\n\n\n\n
Original Data: [{'fruit': 'strawberry', 'price': 100}, {'fruit': 'banana', 'price': 91}, {'fruit': 'mango', 'price': 132}, {'fruit': 'cherry', 'price': 82}]\n--------------------\nSorted Data: [{'fruit': 'cherry', 'price': 82}, {'fruit': 'banana', 'price': 91}, {'fruit': 'strawberry', 'price': 100}, {'fruit': 'mango', 'price': 132}]<\/pre><\/div>\n\n\n\n
Instead of explicitly defining the<\/strong> sort_dict_by_price<\/code> function, we could have used the<\/strong> lambda<\/code> function in the above code.<\/strong><\/p>\n\n\n\n
# List containing dictionary data\ndata = [\n    {'fruit': 'strawberry', 'price': 100},\n    {'fruit': 'banana', 'price': 91},\n    {'fruit': 'mango', 'price': 132},\n    {'fruit': 'cherry', 'price': 82},\n]\n\nprint(f'Original Data: {data}')\n\n# Sorting data using the lambda function\ndata.sort(key=lambda item: item['fruit'])\nprint('-' * 20)\n# Printing the data\nprint(f'Sorted Data: {data}')<\/pre><\/div>\n\n\n\n
We changed the code above and passed the lambda<\/code> function to the key<\/code>. The expression lambda item: item['fruit']<\/code> is equivalent to the previous code’s sort_dict_by_price<\/code> function.<\/p>\n\n\n\n
Output<\/strong><\/p>\n\n\n\n
Original Data: [{'fruit': 'strawberry', 'price': 100}, {'fruit': 'banana', 'price': 91}, {'fruit': 'mango', 'price': 132}, {'fruit': 'cherry', 'price': 82}]\n--------------------\nSorted Data: [{'fruit': 'banana', 'price': 91}, {'fruit': 'cherry', 'price': 82}, {'fruit': 'mango', 'price': 132}, {'fruit': 'strawberry', 'price': 100}]<\/pre><\/div>\n\n\n\n
Example 4 – Sorting tuple data by specifying sorting criteria<\/strong><\/p>\n\n\n\n
In the following example, data<\/code> is a list containing tuples and we sorted the data<\/code> in descending order based on the first items of the tuple.<\/p>\n\n\n\n
# List containing tuple data\ndata = [\n    ('strawberry', 100),\n    ('banana', 91),\n    ('mango', 132),\n    ('cherry', 82),\n]\n\nprint(f'Original Data: {data}')\n\n# Sorting data based on first value in descending order\ndata.sort(key=lambda item: item[0], reverse=True)\nprint('-' * 20)\n# Printing the data\nprint(f'Sorted Data: {data}')<\/pre><\/div>\n\n\n\n
Output<\/strong><\/p>\n\n\n\n
Original Data: [('strawberry', 100), ('banana', 91), ('mango', 132), ('cherry', 82)]\n--------------------\nSorted Data: [('strawberry', 100), ('mango', 132), ('cherry', 82), ('banana', 91)]<\/pre><\/div>\n\n\n\n
<\/a>sorted()<\/h2>\n\n\n\n
Python sorted()<\/code> function is used to sort the iterable data<\/strong>. By default, this function sorts the data in ascending order<\/strong>.<\/p>\n\n\n\n
# Tuple data\ntuple_data = ((4, 's'), (1, 'q'), (3, 'z'), (4, 'a'))\nprint(f'Original: {tuple_data}')\n# Using sorted function\nsorting = sorted(tuple_data)\nprint('-'*20)\n# Printing the sorted data\nprint(f'Sorted: {sorting}')<\/pre><\/div>\n\n\n\n
We have nested tuple data stored in the variable tuple_data<\/code>, used the sorted()<\/code> function with our iterable<\/strong> as a parameter, and then printed the sorted data.<\/p>\n\n\n\n
Output<\/strong><\/p>\n\n\n\n
Original: ((4, 's'), (1, 'q'), (3, 'z'), (4, 'a'))\n--------------------\nSorted: [(1, 'q'), (3, 'z'), (4, 'a'), (4, 's')]<\/pre><\/div>\n\n\n\n
The data were sorted based on the first item<\/strong> of the tuple tuple_data<\/code>.<\/p>\n\n\n\n
<\/a>Syntax<\/h3>\n\n\n\n
sorted(iterable, key=None, reverse=False)<\/code><\/p>\n\n\n\n
Here<\/p>\n\n\n\n
iterable<\/code> – Required. Any iterable data<\/p>\n\n\n\n
key<\/code> – defaults to None<\/code>. To specify the sorting criteria.<\/p>\n\n\n\n
reverse<\/code> – Defaults to False<\/code>. When set to True<\/code>, the data will be sorted in descending order.<\/p>\n\n\n\n
<\/a>Examples<\/h3>\n\n\n\n
We have data of various data types that are all iterable; we’ll sort them using the sorted()<\/code> function.<\/p>\n\n\n\n
list_data = [43, 21, 2, 34]\nprint(f'Sorted List: {sorted(list_data)}')\n\n# Seperator\nprint('-'*20)\n\ntuple_data = (('x', 3), ('w', 1), ('1', 4))\nprint(f'Sorted Tuple: {sorted(tuple_data)}')\n\n# Seperator\nprint('-'*20)\n\ndict_data = {9: 'G', 1: 'V', 4: 'E'}\nprint(f'Sorted Dictionary Keys: {sorted(dict_data)}')\nprint(f'Sorted Dictionary Values: {sorted(dict_data.values())}')\nprint(f'Sorted Dictionary Items: {sorted(dict_data.items())}')<\/pre><\/div>\n\n\n\n
Output<\/strong><\/p>\n\n\n\n
Sorted List: [2, 21, 34, 43]\n--------------------\nSorted Tuple: [('1', 4), ('w', 1), ('x', 3)]\n--------------------\nSorted Dictionary Keys: [1, 4, 9]\nSorted Dictionary Values: ['E', 'G', 'V']\nSorted Dictionary Items: [(1, 'V'), (4, 'E'), (9, 'G')]<\/pre><\/div>\n\n\n\n
Example 2 – Using<\/strong> key<\/code> and<\/strong> reverse<\/code> parameters<\/strong><\/p>\n\n\n\n
# Tuple data\ntuple_data = (\n    ('Mango', 25),\n    ('Walnut', 65),\n    ('Cherry', 10),\n    ('Apple', 68),\n)\n\nprint(f'Original: {tuple_data}')\n# Separator\nprint('-'*20)\n\n# Function for grabbing 2nd item from the data\ndef sorting_tup_data(item):\n    return item[1]\n\n# Sorting based on sorting criteria in descending order\nsorting = sorted(tuple_data, key=sorting_tup_data, reverse=True)\nprint(f'Sorted: {sorting}')<\/pre><\/div>\n\n\n\n
Output<\/strong><\/p>\n\n\n\n
Original: (('Mango', 25), ('Walnut', 65), ('Cherry', 10), ('Apple', 68))\n--------------------\nSorted: [('Apple', 68), ('Walnut', 65), ('Mango', 25), ('Cherry', 10)]<\/pre><\/div>\n\n\n\n
Due to the use of the key<\/code> parameter where we passed the custom function, the tuple was sorted based on the second item<\/strong> and data was sorted in descending order because the reverse<\/code> was set to True<\/code>.<\/p>\n\n\n\n
<\/a>Difference<\/h2>\n\n\n\n
sort()<\/td>sorted()<\/td><\/tr><\/thead>
Used to sort the Python List<\/strong>.<\/td>Used to sort any iterable data such as List<\/strong>, Tuple<\/strong>, Dictionary,<\/strong> and more.<\/td><\/tr>
Takes two parameters: key<\/code> and reverse<\/code>.<\/td>Takes three parameters: iterable<\/code>, key<\/code> and reverse<\/code>.<\/td><\/tr>
It is a List<\/code> function(list.sort()<\/code>) and can only work with Lists.<\/td>It is a function to sort any data which can be iterated.<\/td><\/tr>
sort()<\/code> modifies the original list.<\/td>sorted()<\/code> doesn’t modify the original data instead it returns the new modified data.<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
<\/a>Conclusion<\/h2>\n\n\n\n
We’ve seen a comparison of the list sort()<\/code> and sorted()<\/code> functions. We’ve coded the examples to understand how these functions work. Both functions are used to sort data, but the sort()<\/code> function only sorts Python lists<\/strong>, whereas the sorted()<\/code> function sorts iterable data<\/strong>.<\/p>\n\n\n\n
We’ve also seen the differences between the two in a table format.<\/p>\n\n\n\n
\n\n\n\n
\ud83c\udfc6Other articles you might be interested in if you liked this one<\/strong><\/p>\n\n\n\n
\u2705Comparing the list reverse and reversed functions<\/a>.<\/p>\n\n\n\n
\u27058 different ways to reverse a Python list<\/a>.<\/p>\n\n\n\n
\u2705NumPy argmax() and TensorFlow argmax() – Are they similar<\/a>?<\/p>\n\n\n\n
\u2705Execute your code dynamically using the exec() in Python<\/a>.<\/p>\n\n\n\n
\u2705Perform high-level file operations on files in Python<\/a>.<\/p>\n\n\n\n
\u2705Number your iterable data using the enumerate() in Python<\/a>.<\/p>\n\n\n\n
\u2705Understanding args and kwargs in function parameter in Python<\/a>.<\/p>\n\n\n\n
\n\n\n\n
That’s all for now<\/strong><\/p>\n\n\n\n
Keep Coding\u270c\u270c<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"
We’ll compare the Python’s list sort() and sorted() functions in this article. We’ll learn about these functions, such as what they are and how they differ programmatically and syntactically. Python sort() and sorted() are used to sort the data in ascending or descending order. Their goals are the same but are used in different conditions. sort() The sort() function is connected to the Python list […]<\/p>\n","protected":false},"author":1,"featured_media":1058,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"ocean_post_layout":"","ocean_both_sidebars_style":"","ocean_both_sidebars_content_width":0,"ocean_both_sidebars_sidebars_width":0,"ocean_sidebar":"0","ocean_second_sidebar":"0","ocean_disable_margins":"enable","ocean_add_body_class":"","ocean_shortcode_before_top_bar":"","ocean_shortcode_after_top_bar":"","ocean_shortcode_before_header":"","ocean_shortcode_after_header":"","ocean_has_shortcode":"","ocean_shortcode_after_title":"","ocean_shortcode_before_footer_widgets":"","ocean_shortcode_after_footer_widgets":"","ocean_shortcode_before_footer_bottom":"","ocean_shortcode_after_footer_bottom":"","ocean_display_top_bar":"default","ocean_display_header":"default","ocean_header_style":"","ocean_center_header_left_menu":"0","ocean_custom_header_template":"0","ocean_custom_logo":0,"ocean_custom_retina_logo":0,"ocean_custom_logo_max_width":0,"ocean_custom_logo_tablet_max_width":0,"ocean_custom_logo_mobile_max_width":0,"ocean_custom_logo_max_height":0,"ocean_custom_logo_tablet_max_height":0,"ocean_custom_logo_mobile_max_height":0,"ocean_header_custom_menu":"0","ocean_menu_typo_font_family":"0","ocean_menu_typo_font_subset":"","ocean_menu_typo_font_size":0,"ocean_menu_typo_font_size_tablet":0,"ocean_menu_typo_font_size_mobile":0,"ocean_menu_typo_font_size_unit":"px","ocean_menu_typo_font_weight":"","ocean_menu_typo_font_weight_tablet":"","ocean_menu_typo_font_weight_mobile":"","ocean_menu_typo_transform":"","ocean_menu_typo_transform_tablet":"","ocean_menu_typo_transform_mobile":"","ocean_menu_typo_line_height":0,"ocean_menu_typo_line_height_tablet":0,"ocean_menu_typo_line_height_mobile":0,"ocean_menu_typo_line_height_unit":"","ocean_menu_typo_spacing":0,"ocean_menu_typo_spacing_tablet":0,"ocean_menu_typo_spacing_mobile":0,"ocean_menu_typo_spacing_unit":"","ocean_menu_link_color":"","ocean_menu_link_color_hover":"","ocean_menu_link_color_active":"","ocean_menu_link_background":"","ocean_menu_link_hover_background":"","ocean_menu_link_active_background":"","ocean_menu_social_links_bg":"","ocean_menu_social_hover_links_bg":"","ocean_menu_social_links_color":"","ocean_menu_social_hover_links_color":"","ocean_disable_title":"default","ocean_disable_heading":"default","ocean_post_title":"","ocean_post_subheading":"","ocean_post_title_style":"","ocean_post_title_background_color":"","ocean_post_title_background":0,"ocean_post_title_bg_image_position":"","ocean_post_title_bg_image_attachment":"","ocean_post_title_bg_image_repeat":"","ocean_post_title_bg_image_size":"","ocean_post_title_height":0,"ocean_post_title_bg_overlay":0.5,"ocean_post_title_bg_overlay_color":"","ocean_disable_breadcrumbs":"default","ocean_breadcrumbs_color":"","ocean_breadcrumbs_separator_color":"","ocean_breadcrumbs_links_color":"","ocean_breadcrumbs_links_hover_color":"","ocean_display_footer_widgets":"default","ocean_display_footer_bottom":"default","ocean_custom_footer_template":"0","ocean_post_oembed":"","ocean_post_self_hosted_media":"","ocean_post_video_embed":"","ocean_link_format":"","ocean_link_format_target":"self","ocean_quote_format":"","ocean_quote_format_link":"post","ocean_gallery_link_images":"off","ocean_gallery_id":[],"footnotes":""},"categories":[2,41],"tags":[40,12,31],"class_list":["post-1056","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python","category-function","tag-functions","tag-python","tag-python3","entry","has-media"],"_links":{"self":[{"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/posts\/1056","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/comments?post=1056"}],"version-history":[{"count":3,"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/posts\/1056\/revisions"}],"predecessor-version":[{"id":1300,"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/posts\/1056\/revisions\/1300"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/media\/1058"}],"wp:attachment":[{"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/media?parent=1056"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/categories?post=1056"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/geekpython.in\/wp-json\/wp\/v2\/tags?post=1056"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}