{"id":27552,"date":"2022-08-30T21:06:27","date_gmt":"2022-08-30T15:36:27","guid":{"rendered":"https:\/\/python-programs.com\/?p=27552"},"modified":"2022-08-30T21:06:27","modified_gmt":"2022-08-30T15:36:27","slug":"python-numpy-matrix-partition","status":"publish","type":"post","link":"https:\/\/python-programs.com\/python-numpy-matrix-partition\/","title":{"rendered":"Python Numpy matrix.partition() Function"},"content":{"rendered":"<p><strong>NumPy Library\u00a0<\/strong><\/p>\n<p>NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import it into our program and then we can easily use the functionality of NumPy in our program.<\/p>\n<p>NumPy is a Python library that is frequently used for scientific and statistical analysis. NumPy arrays are grids of the same datatype\u2019s values.<\/p>\n<p><strong> Numpy matrix.partition() Function:<\/strong><\/p>\n<p>Using the matrix.partition() method of the Numpy module, we can partition the matrix in such a manner that the index value that we pass sorts the matrix in such a way that all the values smaller than that value are moved to the left, and others are moved to the right.<\/p>\n<p><strong>Syntax:<\/strong><\/p>\n<pre> matrix.partition(index)<\/pre>\n<p><strong>Return Value:<\/strong><\/p>\n<p>The partitioned matrix is returned by the partition() function.<\/p>\n<h2>Numpy matrix.partition() Function in Python<\/h2>\n<p><strong>For 1-Dimensional (1D) Matrix(array)<\/strong><\/p>\n<p><strong>Approach:<\/strong><\/p>\n<ul>\n<li>Import numpy module using the import keyword<\/li>\n<li>Create a matrix(1-Dimensional) using the matrix() function of numpy module by passing some random 1D matrix as an argument to it and store it in a variable<\/li>\n<li>Print the given matrix<\/li>\n<li>Apply partition() function on the given matrix by passing some random index value as an argument to it to partition the given matrix.<\/li>\n<li>Here index value = 3, and the value at that 3rd index is 4. The values less than 4 (i.e, 1,2) are moved to the left, and others (6) are moved to the right.<\/li>\n<li>Print the given matrix after partition.<\/li>\n<li>The Exit of the Program.<\/li>\n<\/ul>\n<p><strong>Below is the implementation:<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\"># Import numpy module using the import keyword\r\nimport numpy as np\r\n            \r\n# Create a matrix(1-Dimensional) using the matrix() function of numpy module by passing \r\n# some random 1D matrix as an argument to it and store it in a variable\r\ngvn_matrx = np.matrix('[2, 1, 6, 4]')\r\n# Print the given matrix\r\nprint(\"The given matrix is:\") \r\nprint(gvn_matrx)   \r\n\r\n# Apply partition() function on the given matrix by passing some random index value as an argument to it\r\n# to partition the given matrix.\r\n# Here index value = 3, the value at the 3rd index is 4. The values less than 4 (i.e, 1,2) are \r\n# moved to the left and others (6) are moved to the right\r\ngvn_matrx.partition(3)\r\n# Print the given matrix after partition.\r\nprint(\"The given matrix after partition is:\")\r\nprint(gvn_matrx)<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>The given matrix is:\r\n[[2 1 6 4]]\r\nThe given matrix after partition is:\r\n[[1 2 4 6]]<\/pre>\n<p><strong>Explanation:<\/strong><\/p>\n<pre>Here index value = 3, the value at the 3rd index is 4. \r\nThe values less than 4 (i.e, 1 and 2) are moved to the left and \r\nother number 6 is moved to the right<\/pre>\n<p><strong>For 2-Dimensional (2D) Matrix<\/strong><\/p>\n<p><strong>Approach:<\/strong><\/p>\n<ul>\n<li>Import numpy module using the import keyword<\/li>\n<li>Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing some random 2D matrix as an argument to it and store it in a variable<\/li>\n<li>Print the given matrix<\/li>\n<li>Apply partition() function on the given matrix by passing some random index value as an argument to it to partition the given matrix.<\/li>\n<li>Print the given matrix after partition.<\/li>\n<li>The Exit of the Program.<\/li>\n<\/ul>\n<p><strong>Below is the implementation:<\/strong><\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\"># Import numpy module using the import keyword\r\nimport numpy as np\r\n            \r\n# Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing \r\n# some random 2D matrix as an argument to it and store it in a variable\r\ngvn_matrx = np.matrix('[10, 1; 2, 7]')\r\n# Print the given matrix\r\nprint(\"The given matrix is:\") \r\nprint(gvn_matrx)   \r\n\r\n# Apply partition() function on the given matrix by passing some random index value as an argument to it\r\n# to partition the given matrix.\r\ngvn_matrx.partition(1)\r\n# Print the given matrix after partition.\r\nprint(\"The given matrix after partition is:\")\r\nprint(gvn_matrx)<\/pre>\n<p><strong>Output:<\/strong><\/p>\n<pre>The given matrix is:\r\n[[10 1]\r\n [ 2 7]]\r\nThe given matrix after partition is:\r\n[[ 1 10]\r\n [ 2 7]]<\/pre>\n","protected":false},"excerpt":{"rendered":"<p>NumPy Library\u00a0 NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/python-programs.com\/python-numpy-matrix-partition\/\"> <span class=\"screen-reader-text\">Python Numpy matrix.partition() Function<\/span> Read More &raquo;<\/a><\/p>\n","protected":false},"author":7,"featured_media":0,"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>Python Numpy matrix.partition() 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\/python-numpy-matrix-partition\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python Numpy matrix.partition() Function - Python Programs\" \/>\n<meta property=\"og:description\" content=\"NumPy Library\u00a0 NumPy is a library in python that is created to work efficiently with arrays in python. 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