{"id":7834,"date":"2023-11-03T08:16:52","date_gmt":"2023-11-03T02:46:52","guid":{"rendered":"https:\/\/python-programs.com\/?p=7834"},"modified":"2023-11-10T12:14:11","modified_gmt":"2023-11-10T06:44:11","slug":"np-ones-create-1d-2d-numpy-array-filled-with-ones-1s","status":"publish","type":"post","link":"https:\/\/python-programs.com\/np-ones-create-1d-2d-numpy-array-filled-with-ones-1s\/","title":{"rendered":"np.ones() \u2013 Create 1D \/ 2D Numpy Array filled with ones (1\u2019s)"},"content":{"rendered":"<h2>Create a 1D \/ 2D Numpy Arrays of zeros or ones<\/h2>\n<p>In this article, we will learn to create array of various shapes where all the values are initialized with 0 &amp; 1.<\/p>\n<h3>numpy.zeros() :<\/h3>\n<p>A function is provided by Python&#8217;s numpy module i.e. <code>numpy.zeros()<\/code> which will create a numpy array of given shape and where all values are initialized with 0&#8217;s.<\/p>\n<p>i.e.<\/p>\n<pre>numpy.zeros(shape, dtype=float, order='C')<\/pre>\n<p>Arguments:-<\/p>\n<ul>\n<li><strong>shape<\/strong> : It denotes shape of the numpy array. It may be single int or sequence of int.<\/li>\n<li><strong>dtype<\/strong> : It denotes data type of elements. Default value for dtype is float64.<\/li>\n<li><strong>order<\/strong> : It denotes the order in which data is stored in a multi-dimension array. It is of two types<\/li>\n<\/ul>\n<ol>\n<li>&#8216;F&#8217;: Data will be stored Row major order<\/li>\n<li>&#8216;C&#8217;: Data will be stored in Column major order. Default value of <em>order <\/em>is &#8216;C&#8217;.<\/li>\n<\/ol>\n<p>Let&#8217;s see the below 4 different types implementation with code<\/p>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><a href=\"#Creating_a_flattened_1D_numpy_array_filled_with_all_zeros\">Creating a flattened 1D numpy array filled with all zeros<\/a><\/li>\n<li><a href=\"#Creating_a_2D_numpy_array_with_4_rows_&amp;_3_columns,_filled_with_0\u2019s\">Creating a 2D numpy array with 4 rows &amp; 3 columns, filled with 0\u2019s<\/a><\/li>\n<li><a href=\"#Creating_a_flattened_1D_numpy_array_filled_with_all_Ones\">Creating a flattened 1D numpy array filled with all Ones<\/a><\/li>\n<li><a href=\"#Creating_a_2D_numpy_array_with_3_rows_&amp;_3_columns,_filled_with_1\u2019s\">Creating a 2D numpy array with 3 rows &amp; 3 columns, filled with 1\u2019s<\/a><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<h3><a id=\"Creating_a_flattened_1D_numpy_array_filled_with_all_zeros\"><\/a>Creating a flattened 1D numpy array filled with all zeros :<\/h3>\n<p>We can create a flattened numpy array with all values as &#8216;0&#8217;.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import numpy as sc\r\n# create a 1D numpy array with values as 0\r\nnumarr = sc.zeros(5)\r\nprint('Contents of the Flattened Numpy Array : ')\r\nprint(numarr)\r\n<\/pre>\n<pre>Output :\r\nContents of the Flattened Numpy Array :\r\n[0. 0. 0. 0. 0.]<\/pre>\n<h3><a id=\"Creating_a_2D_numpy_array_with_4_rows_&amp;_3_columns,_filled_with_0\u2019s\"><\/a>Creating a 2D numpy array with 4 rows &amp; 3 columns, filled with 0\u2019s :<\/h3>\n<p>We can create a 2D numpy array by passing (4,3) as argument in <code>numpy.zeros()<\/code> which will return all values as &#8216;0&#8217;.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import numpy as sc\r\n# create a 2D numpy array with values as 0 \r\nnumarr = sc.zeros((4,3))\r\nprint('Contents of the 2D Numpy Array : ')\r\nprint(numarr)\r\n<\/pre>\n<pre>Output :\r\nContents of the 2D Numpy Array :\r\n[[0. 0. 0.]\r\n [0. 0. 0.]\r\n [0. 0. 0.]\r\n\u00a0[0. 0. 0.]]<\/pre>\n<p>We know that default value of dtype is float64, let&#8217;s try to change the dtype to int64.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import numpy as sc\r\n# create a 2D numpy array with values as 0 which are of int data type\r\nnumarr = sc.zeros((4,3), dtype=sc.int64)\r\nprint('Contents of the 2D Numpy Array : ')\r\nprint(numarr)\r\n<\/pre>\n<pre>Output :\r\nContents of the 2D Numpy Array :\r\n[[0 0 0]\r\n [0 0 0]\r\n [0 0 0]\r\n\u00a0[0 0 0]]<\/pre>\n<h3>numpy.ones() :<\/h3>\n<p>A function is provided by Python&#8217;s numpy module i.e. <code>numpy.ones()<\/code> which will create a numpy array of given shape and where all values are initialized with 1&#8217;s.<\/p>\n<p>i.e.<\/p>\n<pre>numpy.ones(shape, dtype=float, order='C')<\/pre>\n<p>Arguments:-<\/p>\n<ul>\n<li>shape : It denotes shape of the numpy array. It may be single int or sequence of int.<\/li>\n<li>dtype : It denotes data type of elements. Default value for dtype is float64.<\/li>\n<li>order : It denotes the order in which data is stored in a multi-dimension array. It is of two types<\/li>\n<\/ul>\n<ol>\n<li>&#8216;F&#8217;: Data will be stored Row major order<\/li>\n<li>&#8216;C&#8217;: Data will be stored in Column major order. Default value of <em>order <\/em>is &#8216;C&#8217;.<\/li>\n<\/ol>\n<h3><a id=\"Creating_a_flattened_1D_numpy_array_filled_with_all_Ones\"><\/a>Creating a flattened 1D numpy array filled with all Ones :<\/h3>\n<p>We can make all values as 1 in a flattened array.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import numpy as sc\r\n# create a flattened 1D numpy array of size 5 where all values are 1\r\nnumarr = sc.ones(5)\r\nprint('Contents of the Flattened Numpy Array : ')\r\nprint(numarr)\r\n<\/pre>\n<pre>Output :\r\nContents of the Flattened Numpy Array :\r\n[ 1.\u00a0 1.\u00a0 1.\u00a0 1.\u00a0 1.]<\/pre>\n<h3><a id=\"Creating_a_2D_numpy_array_with_3_rows_&amp;_3_columns,_filled_with_1\u2019s\"><\/a>Creating a 2D numpy array with 3 rows &amp; 3 columns, filled with 1\u2019s\u00a0 :<\/h3>\n<p>We can create a 2D numpy array by passing row and column as argument in <code>numpy.ones()<\/code> where all the values are 1.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import numpy as sc\r\n# create a 2D numpy array with 3 rows &amp; 4 columns with all values as 1\r\nnumarr = sc.ones((3,3))\r\nprint('Contents of the 2D Numpy Array : ')\r\nprint(numarr)\r\nprint('Data Type of the contents in  given Array : ',numarr.dtype)\r\n<\/pre>\n<pre>Output :\r\nContents of the 2D Numpy Array :\r\n[[1. 1. 1.]\r\n [1. 1. 1.]\r\n [1. 1. 1.]]\r\nData Type of the contents in\u00a0 given Array :\u00a0 float64<\/pre>\n<p>We know default type of dtype is float64, let&#8217;s try to change it to int64.<\/p>\n<pre class=\"EnlighterJSRAW\" data-enlighter-language=\"python\">import numpy as sc\r\n# create a 2D numpy array with values as 1 which are of int data type\r\nnumarr = sc.ones((4,3), dtype=sc.int64)\r\nprint('Contents of the 2D Numpy Array : ')\r\nprint(numarr)\r\n<\/pre>\n<pre>Output :\r\nContents of the 2D Numpy Array :\r\n[[1 1 1]\r\n [1 1 1]\r\n [1 1 1]\r\n\u00a0[1 1 1]]<\/pre>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Create a 1D \/ 2D Numpy Arrays of zeros or ones In this article, we will learn to create array of various shapes where all the values are initialized with 0 &amp; 1. numpy.zeros() : A function is provided by Python&#8217;s numpy module i.e. numpy.zeros() which will create a numpy array of given shape and &hellip;<\/p>\n<p class=\"read-more\"> <a class=\"\" href=\"https:\/\/python-programs.com\/np-ones-create-1d-2d-numpy-array-filled-with-ones-1s\/\"> <span class=\"screen-reader-text\">np.ones() \u2013 Create 1D \/ 2D Numpy Array filled with ones (1\u2019s)<\/span> Read More &raquo;<\/a><\/p>\n","protected":false},"author":9,"featured_media":8058,"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 - 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