{"id":4740,"date":"2023-10-28T14:48:10","date_gmt":"2023-10-28T09:18:10","guid":{"rendered":"https:\/\/python-programs.com\/?p=4740"},"modified":"2023-11-10T12:04:29","modified_gmt":"2023-11-10T06:34:29","slug":"how-to-sort-a-numpy-array-in-python","status":"publish","type":"post","link":"https:\/\/python-programs.com\/how-to-sort-a-numpy-array-in-python\/","title":{"rendered":"How to sort a Numpy Array in Python? | numpy.sort() in Python | Python numpy.ndarray.sort() Function"},"content":{"rendered":"<p>In this article, we are going to show you sorting a NumpyArray in descending and in ascending order or sorts the elements from largest to smallest value or smallest to largest value. Stay tuned to this page and collect plenty of information about the numpy.sort() in Python and How to sort a Numpy Array in Python?<\/p>\n<ul>\n<li><a href=\"#Sorting_Arrays\">Sorting Arrays<\/a><\/li>\n<li><a href=\"#numpy.ndarray.sort()_in_Python\">numpy.ndarray.sort() in Python<\/a><\/li>\n<li><a href=\"#Python_numpy.sort()_method\">Python numpy.sort() method<\/a><\/li>\n<li><a href=\"#Sort_a_Numpy_Array_in_Place\">Sort a Numpy Array in Place<\/a><\/li>\n<li><a href=\"#Sort_a_Numpy_array_in_Descending_Order\">Sort a Numpy array in Descending Order<\/a><\/li>\n<li><a href=\"#Sorting_a_numpy_array_with_different_kinds_of_sorting_algorithms\">Sorting a numpy array with different kinds of sorting algorithms<\/a><\/li>\n<li><a href=\"#Sorting_a_2D_numpy_array_along_with_the_axis\">Sorting a 2D numpy array along with the axis<\/a><\/li>\n<\/ul>\n<h2><a id=\"Sorting_Arrays\"><\/a>Sorting Arrays<\/h2>\n<p>Giving arrays to an ordered sequence is called sorting. An ordered sequence can be any sequence like numeric or alphabetical, ascending or descending.<\/p>\n<p>Python\u2019s Numpy module provides two different methods to sort a numpy array.<\/p>\n<h2><a id=\"numpy.ndarray.sort()_in_Python\"><\/a>numpy.ndarray.sort() method in Python<\/h2>\n<p>A member function of the ndarray class is as follows:<\/p>\n<p><code class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">ndarray.sort(axis=-1, kind='quicksort', order=None)<\/code><\/p>\n<p>This can be ordered through a numpy array object (ndarray) and it classifies the incorporated numpy array in place.<\/p>\n<p><span style=\"color: #ff6600;\">Do Check:<\/span><\/p>\n<ul>\n<li><a href=\"https:\/\/python-programs.com\/numpy-amin-find-minimum-value-in-numpy-array-and-its-index\/\">numpy.amin() | Find minimum value in Numpy Array and it\u2019s index<\/a><\/li>\n<li><a href=\"https:\/\/python-programs.com\/python-convert-matrix-2d-numpy-array-to-a-1d-numpy-array\/\">Python: Convert Matrix \/ 2D Numpy Array to a 1D Numpy Array<\/a><\/li>\n<\/ul>\n<h2><a id=\"Python_numpy.sort()_method\"><\/a>Python numpy.sort() method<\/h2>\n<p>One more method is a global function in the numpy module i.e.<\/p>\n<p><code class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">numpy.sort(array, axis=-1, kind='quicksort', order=None)<\/code><\/p>\n<p>It allows a numpy array as an argument and results in a sorted copy of the Numpy array.<\/p>\n<p>Where,<\/p>\n<table border=\"1\">\n<tbody>\n<tr>\n<th>Sr.No.<\/th>\n<th>Parameter &amp; Description<\/th>\n<\/tr>\n<tr>\n<td>1<\/td>\n<td><b>a<\/b><\/p>\n<p>Array to be sorted<\/td>\n<\/tr>\n<tr>\n<td>2<\/td>\n<td><b>axis<\/b><\/p>\n<p>The axis along which the array is to be sorted. If none, the array is flattened, sorting on the last axis<\/td>\n<\/tr>\n<tr>\n<td>3<\/td>\n<td><b>kind<\/b><\/p>\n<p>Default is quicksort<\/td>\n<\/tr>\n<tr>\n<td>4<\/td>\n<td><b>order<\/b><\/p>\n<p>If the array contains fields, the order of fields to be sorted<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3><a id=\"Sort_a_Numpy_Array_in_Place\"><\/a>Sort a Numpy Array in Place<\/h3>\n<p>The NumPy ndarray object has a function called sort() that we will use for sorting.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">import numpy as np\r\n# Create a Numpy array from list of numbers\r\narr = np.array([9, 1, 3, 2, 17, 5,  2, 8, 14])\r\narray = np.array([9, 1, 3, 2, 17, 5,  2, 8, 14])\r\n# Sort the numpy array inplace\r\narray.sort()\r\nprint('Original Array : ', arr)\r\nprint('Sorted Array : ', array)\r\n<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>RESTART: C:\/Users\/HP\/Desktop\/article3.py\r\nOriginal Array : [ 9 1 3 2 17 5 2 8 14]\r\nSorted Array : [ 1 2 2 3 5 8 9 14 17]\r\n\r\n<\/pre>\n<p>So in the above example, you have seen that using<code>array.sort()<\/code>we have sorted our array in place.<\/p>\n<h3><a id=\"Sort_a_Numpy_array_in_Descending_Order\"><\/a>Sort a Numpy array in Descending Order<\/h3>\n<p>In the above method, we have seen that by default both numpy.sort() and ndarray.sort() sorts the numpy array in ascending order. But now, you will observe how to sort an array in descending order?<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import numpy as np\r\n# Create a Numpy array from list of numbers\r\narr = np.array([9, 1, 3, 2, 17, 5,  2, 8, 14])\r\narray = np.array([9, 1, 3, 2, 17, 5,  2, 8, 14])\r\n# Sort the numpy array inplace\r\narray = np.sort(arr)[::-1]\r\n\r\n# Get a sorted copy of numpy array (Descending Order)\r\nprint('Original Array : ', arr)\r\nprint('Sorted Array : ', array)\r\n<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>RESTART: C:\/Users\/HP\/Desktop\/article3.py\r\nOriginal Array : [ 9 1 3 2 17 5 2 8 14]\r\nSorted Array : [17 14 9 8 5 3 2 2 1]\r\n<\/pre>\n<h3><a id=\"Sorting_a_numpy_array_with_different_kinds_of_sorting_algorithms\"><\/a>Sorting a numpy array with different kinds of sorting algorithms<\/h3>\n<p>While sorting sort() function accepts a parameter &#8216;kind&#8217; that tells about the sorting algorithm to be used. If not provided then the default value is <strong>\u2018<\/strong>quicksort<strong>\u2019<\/strong>. To sort numpy array with another sorting algorithm pass this \u2018kind\u2019 argument.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import numpy as np\r\n# Create a Numpy array from list of numbers\r\narr = np.array([9, 1, 3, 2, 17, 5,  2, 8, 14])\r\narray = np.array([9, 1, 3, 2, 17, 5,  2, 8, 14])\r\n# Sort the numpy array using different algorithms\r\n\r\n#Sort Using 'mergesort'\r\nsortedArr1 = np.sort(arr, kind='mergesort')\r\n\r\n# Sort Using 'heapsort'\r\nsortedArr2 = np.sort(arr, kind='heapsort')\r\n\r\n# Sort Using 'heapsort'\r\nsortedArr3 = np.sort(arr, kind='stable')\r\n\r\n# Get a sorted copy of numpy array (Descending Order)\r\nprint('Original Array : ', arr)\r\n\r\nprint('Sorted Array using mergesort: ', sortedArr1)\r\n\r\nprint('Sorted Array using heapsort : ', sortedArr2)\r\n\r\nprint('Sorted Array using stable : ', sortedArr3)<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>RESTART: C:\/Users\/HP\/Desktop\/article3.py\r\nOriginal Array : [ 9 1 3 2 17 5 2 8 14]\r\nSorted Array using mergesort: [ 1 2 2 3 5 8 9 14 17]\r\nSorted Array using heapsort : [ 1 2 2 3 5 8 9 14 17]\r\nSorted Array using stable : [ 1 2 2 3 5 8 9 14 17]<\/pre>\n<h3><a id=\"Sorting_a_2D_numpy_array_along_with_the_axis\"><\/a>Sorting a 2D numpy array along with the axis<\/h3>\n<p>numpy.sort() and numpy.ndarray.sort() provides an argument axis to sort the elements along the axis.<br \/>\nLet\u2019s create a 2D Numpy Array.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">import numpy as np\r\n# Create a 2D Numpy array list of list\r\n\r\narr2D = np.array([[8, 7, 1, 2], [3, 2, 3, 1], [29, 32, 11, 9]])\r\n\r\nprint(arr2D)\r\n<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>RESTART: C:\/Users\/HP\/Desktop\/article3.py\r\n[[ 8 7 1 2]\r\n[ 3 2 3 1]\r\n[29 32 11 9]]\r\n<\/pre>\n<p>Now sort contents of each column in 2D numpy Array,<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"generic\">import numpy as np\r\n# Create a 2D Numpy array list of list\r\n\r\narr2D = np.array([[8, 7, 1, 2], [3, 2, 3, 1], [29, 32, 11, 9]])\r\narr2D.sort(axis=0)\r\nprint('Sorted Array : ')\r\nprint(arr2D)\r\n<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>RESTART: C:\/Users\/HP\/Desktop\/article3.py\r\nSorted Array :\r\n[[ 3 2 1 1]\r\n[ 8 7 3 2]\r\n[29 32 11 9]]\r\n<\/pre>\n<p>So here is our sorted 2D numpy array.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>In this article, we are going to show you sorting a NumpyArray in descending and in ascending order or sorts the elements from largest to smallest value or smallest to largest value. Stay tuned to this page and collect plenty of information about the numpy.sort() in Python and How to sort a Numpy Array in &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/python-programs.com\/how-to-sort-a-numpy-array-in-python\/\"> <span class=\"screen-reader-text\">How to sort a Numpy Array in Python? | numpy.sort() in Python | Python numpy.ndarray.sort() Function<\/span> Read More &raquo;<\/a><\/p>\n","protected":false},"author":4,"featured_media":5778,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"spay_email":"","jetpack_publicize_message":"","jetpack_is_tweetstorm":false,"jetpack_publicize_feature_enabled":true},"categories":[5],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v18.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>How to sort a Numpy Array in Python? | numpy.sort() in Python | Python numpy.ndarray.sort() Function - Python Programs<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/python-programs.com\/how-to-sort-a-numpy-array-in-python\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to sort a Numpy Array in Python? | numpy.sort() in Python | Python numpy.ndarray.sort() Function - Python Programs\" \/>\n<meta property=\"og:description\" content=\"In this article, we are going to show you sorting a NumpyArray in descending and in ascending order or sorts the elements from largest to smallest value or smallest to largest value. 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