{"id":7525,"date":"2021-01-10T21:08:15","date_gmt":"2021-01-10T15:38:15","guid":{"rendered":"http:\/\/www.pythonpool.com\/?p=7525"},"modified":"2023-12-30T18:07:01","modified_gmt":"2023-12-30T12:37:01","slug":"numpy-repeat","status":"publish","type":"post","link":"https:\/\/www.pythonpool.com\/numpy-repeat\/","title":{"rendered":"Numpy Repeat Function Explained In-depth in Python"},"content":{"rendered":"\n<p>Hello geeks, and welcome! In this article, we will cover the <strong>NumPy repeat().<\/strong>\u00a0Along with that, we will also look at its syntax and parameters for a better overall understanding. Then, we will see the application of all the theory parts through a couple of examples.<\/p>\n\n\n\n<p>But first, let us try to get a brief overview of our function <strong>NumPy repeat()<\/strong> through its definition. <strong>Suppose you define an array; you define an array. If you want the elements to be repeated multiple times<\/strong>, you can use this function and get your job done easily instead of writing them by hand<strong>. <\/strong>It will become more clear as we discuss a  few examples. But before that, we will look at its parameters in the next section. <\/p>\n\n\n\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_74 counter-hierarchy ez-toc-counter ez-toc-transparent ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #990303;color:#990303\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #990303;color:#990303\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 eztoc-toggle-hide-by-default' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.pythonpool.com\/numpy-repeat\/#Syntax\" >Syntax<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.pythonpool.com\/numpy-repeat\/#Parameter\" >Parameter<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.pythonpool.com\/numpy-repeat\/#Return\" >Return<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.pythonpool.com\/numpy-repeat\/#Examples\" >Examples<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.pythonpool.com\/numpy-repeat\/#Must_Read\" >Must Read<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.pythonpool.com\/numpy-repeat\/#Conclusion\" >Conclusion<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.pythonpool.com\/numpy-repeat\/#Trending_Python_Articles\" >Trending Python Articles<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\" id=\"h-syntax\"><span class=\"ez-toc-section\" id=\"Syntax\"><\/span>Syntax<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<pre class=\"wp-block-code\"><code>numpy.repeat(a,\u00a0repeats)<\/code><\/pre>\n\n\n\n<p>This is the general syntax associated with our function. In the next section, we will cover the various parameters associated with it. <\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-parameter\"><span class=\"ez-toc-section\" id=\"Parameter\"><\/span>Parameter<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"has-medium-font-size\">1. a:array_like<\/p>\n\n\n\n<p>This parameter represents the array on which the operation needs to be performed.<\/p>\n\n\n\n<p class=\"has-medium-font-size\">2. repeat: int or array of int<\/p>\n\n\n\n<p>This parameter represents how many times does an element of the array needs to be repeated. <\/p>\n\n\n\n<p class=\"has-medium-font-size\">3. axis: int<\/p>\n\n\n\n<p>It is an optional parameter that represents the axis along which the values need to be repeated. <\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-return\"><span class=\"ez-toc-section\" id=\"Return\"><\/span>Return<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"has-medium-font-size\">repreated_array:<\/p>\n\n\n\n<p>Upon completion of the code, it returns the repeated array. Which has the same shape as the input array.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-examples\"><span class=\"ez-toc-section\" id=\"Examples\"><\/span>Examples<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>As we are done with all the theory portion related to <strong>NumPy repeat()<\/strong>. In this section, we will look at how this function works and how it helps us achieve our desired output.\u00a0We will start with an elementary-level example and gradually move our way to more complicated examples.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-1-basic-example-for-numpy-repeat\">1. Basic example for NumPy repeat()<\/h3>\n\n\n<div class=\"wp-block-syntaxhighlighter-code \"><pre class=\"brush: python; title: ; notranslate\" title=\"\">\n#input\nimport numpy as ppool\na=&#x5B;1,23,4,5]\nprint(ppool.repeat(a,2))\n<\/pre><\/div>\n\n<div class=\"wp-block-syntaxhighlighter-code \"><pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n#output\n&#x5B; 1  1 23 23  4  4  5  5]\n<\/pre><\/div>\n\n\n<p>In the above example, we first imported the <strong>NumPy module<\/strong>. After this, we have defined our<strong> array<\/strong>. After that, we used our syntax along with a print statement. Here, as instructed in the program, we want the elements to be repeated twice. So, our output justifies it. The main motive of this example is to make you aware of the functioning of the syntax. Next, we will see a <a href=\"https:\/\/en.wikipedia.org\/wiki\/Bit\" target=\"_blank\" rel=\"noreferrer noopener\">bit<\/a> more advanced example.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-2-example-with-numpy-repeat-as-an-array\">2. Example with Numpy repeat as an array<\/h3>\n\n\n<div class=\"wp-block-syntaxhighlighter-code \"><pre class=\"brush: python; title: ; notranslate\" title=\"\">\nimport numpy as ppool\na=&#x5B;1,23,4,5]\nprint(ppool.repeat(a,&#x5B;2,1,3,1]))\n<\/pre><\/div>\n\n<div class=\"wp-block-syntaxhighlighter-code \"><pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n#output\n&#x5B; 1  1 23  4  4  4  5]\n<\/pre><\/div>\n\n\n<p>Above, we can see another example. We have followed all the steps similar to that of 1st example. But instead of just using an integer for the<strong> purpose of repetition, we have used an array. Here, we have specified the number of times we want each element to return. <\/strong>The output here justifies our input. By doing this, we get a bit more freedom and control.  <\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-3-example-for-a-2-d-array\">3. Example for a 2-D array<\/h3>\n\n\n<div class=\"wp-block-syntaxhighlighter-code \"><pre class=\"brush: python; title: ; notranslate\" title=\"\">\nimport numpy as ppool\na=&#x5B;&#x5B;1,2,3,4],\n  &#x5B;5,6,7,8],\n  &#x5B;12,32,45,5]]\nprint(ppool.repeat(a,&#x5B;1,2,3,1,\n                    1,4,1,2, \n                    1,2,3,1]))\n<\/pre><\/div>\n\n<div class=\"wp-block-syntaxhighlighter-code \"><pre class=\"brush: plain; title: ; notranslate\" title=\"\">\n&#x5B; 1  2  2  3  3  3  4  5  6  6  6  6  7  8  8 12 32 32 45 45 45  5]\n<\/pre><\/div>\n\n\n<p>Above, we have considered an example of the 2-D array. Here, we have followed steps similar to those in the above examples. But here, we can see that although we are considering a 2-D array, our output is a flattened 1-D array. In the next example, we will see how to retain the shape of a 2-D array when using the repeat function. <\/p>\n\n\n\n<h3 class=\"wp-block-heading\" id=\"h-4-example-with-the-axis-parameter\">4. Example with the axis parameter <\/h3>\n\n\n<div class=\"wp-block-syntaxhighlighter-code \"><pre class=\"brush: python; title: ; notranslate\" title=\"\">\nimport numpy as ppool\na=&#x5B;&#x5B;1,23,4,5],\n   &#x5B;2,45,67,52]]\n   \nprint(ppool.repeat(a,&#x5B;2,1,3,1],axis=1))\n<\/pre><\/div>\n\n<div class=\"wp-block-syntaxhighlighter-code \"><pre class=\"brush: python; title: ; notranslate\" title=\"\">\n&#x5B;&#x5B; 1  1 23  4  4  4  5]\n &#x5B; 2  2 45 67 67 67 52]\n<\/pre><\/div>\n\n\n<p>Another example is similar to the 2 above examples. Here, we have used a 2-d array and the axis parameter. What it does is rather than flattening the array, it divides it into subgroups and works on it respectively.<\/p>\n\n\n\n<h2 class=\"wp-block-heading has-vivid-red-color has-text-color\" id=\"h-must-read\"><span class=\"ez-toc-section\" id=\"Must_Read\"><\/span>Must Read<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"http:\/\/www.pythonpool.com\/numpy-mean\/\" rel=\"noreferrer noopener\" target=\"_blank\">Numpy Mean: Implementation and Importance<\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www.pythonpool.com\/numpy-axis\/\" rel=\"noreferrer noopener\" target=\"_blank\">Numpy Axis in Python With Detailed Examples<\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www.pythonpool.com\/numpy-choose\/\" rel=\"noreferrer noopener\" target=\"_blank\">WHAT IS NUMPY CHOOSE()? EXPLAINED IN DETAIL<\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www.pythonpool.com\/numpy-vstack\/\" rel=\"noreferrer noopener\" target=\"_blank\">Numpy Vstack in Python For Different Arrays<\/a><\/li>\n\n\n\n<li><a href=\"http:\/\/www.pythonpool.com\/numpy-log\/\" rel=\"noreferrer noopener\" target=\"_blank\">NumPy log Function() | What is Numpy log in Python<\/a><\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-conclusion\"><span class=\"ez-toc-section\" id=\"Conclusion\"><\/span>Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In this article, we covered the NumPy repeat(). Besides that, we have also looked at its syntax and parameters. For better understanding, we looked at a couple of examples. We varied the syntax and looked at the output for each case. In the end, we can conclude that NumPy repeat() repeats the element of the array. <\/p>\n\n\n\n<p>I hope this article was able to clear all doubts. But if you have any unsolved queries, feel free to write them down below in the comment section.<\/p>\n\n\n\n<p>If you&#8217;re done reading this, why not read about<a href=\"http:\/\/www.pythonpool.com\/numpy-pad\/\"> padding<\/a> in arrays next?<\/p>\n\n\n<div class=\"monsterinsights-widget-popular-posts monsterinsights-widget-popular-posts-delta monsterinsights-popular-posts-styled monsterinsights-widget-popular-posts-columns-2\"><h2 class=\"monsterinsights-widget-popular-posts-widget-title\"><span class=\"ez-toc-section\" id=\"Trending_Python_Articles\"><\/span>Trending Python Articles<span class=\"ez-toc-section-end\"><\/span><\/h2><ul class=\"monsterinsights-widget-popular-posts-list\"><li ><a href=\"https:\/\/www.pythonpool.com\/fixed-typeerror-cant-compare-datetime-datetime-to-datetime-date\/\"><div class=\"monsterinsights-widget-popular-posts-image\"><img decoding=\"async\" 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https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Fixed-nameerror-name-Unicode-is-not-defined.webp 1200w \" alt=\"[Fixed] nameerror: name Unicode is not defined\" \/><\/div><div class=\"monsterinsights-widget-popular-posts-text\"><span class=\"monsterinsights-widget-popular-posts-title\" >[Fixed] nameerror: name Unicode is not defined<\/span><div class=\"monsterinsights-widget-popular-posts-meta\" ><span class=\"monsterinsights-widget-popular-posts-author\">by Namrata Gulati<\/span><span>&#9679;<\/span><span class=\"monsterinsights-widget-popular-posts-date\">January 2, 2024<\/span><\/div><\/div><\/a><\/li><li ><a href=\"https:\/\/www.pythonpool.com\/solved-runtimeerror-cuda-error-invalid-device-ordinal\/\"><div class=\"monsterinsights-widget-popular-posts-image\"><img decoding=\"async\" src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Solved-runtimeerror-cuda-error-invalid-device-ordinal-300x157.webp\" srcset=\" https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Solved-runtimeerror-cuda-error-invalid-device-ordinal-300x157.webp 300w, https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Solved-runtimeerror-cuda-error-invalid-device-ordinal-1024x536.webp 1024w, https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Solved-runtimeerror-cuda-error-invalid-device-ordinal-768x402.webp 768w, https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Solved-runtimeerror-cuda-error-invalid-device-ordinal.webp 1200w \" alt=\"[Solved] runtimeerror: cuda error: invalid device ordinal\" \/><\/div><div class=\"monsterinsights-widget-popular-posts-text\"><span class=\"monsterinsights-widget-popular-posts-title\" >[Solved] runtimeerror: cuda error: invalid device ordinal<\/span><div class=\"monsterinsights-widget-popular-posts-meta\" ><span class=\"monsterinsights-widget-popular-posts-author\">by Namrata Gulati<\/span><span>&#9679;<\/span><span class=\"monsterinsights-widget-popular-posts-date\">January 2, 2024<\/span><\/div><\/div><\/a><\/li><li ><a href=\"https:\/\/www.pythonpool.com\/fixed-typeerror-type-numpy-ndarray-doesnt-define-__round__-method\/\"><div class=\"monsterinsights-widget-popular-posts-image\"><img decoding=\"async\" src=\"https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Fixed-typeerror-type-numpy.ndarray-doesnt-define-__round__-method-300x157.webp\" srcset=\" https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Fixed-typeerror-type-numpy.ndarray-doesnt-define-__round__-method-300x157.webp 300w, https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Fixed-typeerror-type-numpy.ndarray-doesnt-define-__round__-method-1024x536.webp 1024w, https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Fixed-typeerror-type-numpy.ndarray-doesnt-define-__round__-method-768x402.webp 768w, https:\/\/www.pythonpool.com\/wp-content\/uploads\/2024\/01\/Fixed-typeerror-type-numpy.ndarray-doesnt-define-__round__-method.webp 1200w \" alt=\"[Fixed] typeerror: type numpy.ndarray doesn&#8217;t define __round__ method\" \/><\/div><div class=\"monsterinsights-widget-popular-posts-text\"><span class=\"monsterinsights-widget-popular-posts-title\" >[Fixed] typeerror: type numpy.ndarray doesn&#8217;t define __round__ method<\/span><div class=\"monsterinsights-widget-popular-posts-meta\" ><span class=\"monsterinsights-widget-popular-posts-author\">by Namrata Gulati<\/span><span>&#9679;<\/span><span class=\"monsterinsights-widget-popular-posts-date\">January 2, 2024<\/span><\/div><\/div><\/a><\/li><\/ul><\/div><p><\/p>","protected":false},"excerpt":{"rendered":"<p>Hello geeks, and welcome! In this article, we will cover the NumPy repeat().\u00a0Along with that, we will also look at its syntax and parameters for &#8230; <\/p>\n<p class=\"read-more-container\"><a title=\"Numpy Repeat Function Explained In-depth in Python\" class=\"read-more button\" href=\"https:\/\/www.pythonpool.com\/numpy-repeat\/#more-7525\" aria-label=\"More on Numpy Repeat Function Explained In-depth in Python\">Read more<\/a><\/p>\n","protected":false},"author":11,"featured_media":7566,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_mi_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[1495],"tags":[3189,3188,3186,3192,3187,3191,3184,3190,3185,3183],"class_list":["post-7525","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-numpy","tag-numpy-array-repeat","tag-numpy-repeat","tag-numpy-repeat-array","tag-numpy-repeat-matrix","tag-numpy-repeat-stack","tag-numpy-repeat-tile","tag-python-numpy-repeat","tag-repeat-array-numpy","tag-repeat-numpy","tag-repeat-row-vector-numpy","infinite-scroll-item"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.1 (Yoast SEO v25.0) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Numpy Repeat Function Explained In-depth in Python - Python Pool<\/title>\n<meta name=\"description\" content=\"let us try to get a brief overview of our function NumPy repeat() through its definition. 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