{"id":403,"date":"2024-11-10T15:07:12","date_gmt":"2024-11-10T15:07:12","guid":{"rendered":"https:\/\/techkubo.com\/python\/?p=403"},"modified":"2025-06-20T18:01:11","modified_gmt":"2025-06-20T18:01:11","slug":"percentiles","status":"publish","type":"post","link":"https:\/\/techkubo.com\/python\/percentiles\/","title":{"rendered":"Percentiles"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">What are Percentiles?<\/h2>\n\n\n\n<p>In statistics, <strong>percentiles<\/strong> help us understand how a data set is distributed. A <strong>percentile<\/strong> tells us the value below which a certain percentage of the data falls. For example, the 75th percentile tells us the value below which 75% of the data points are located.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Key Concept:<\/h2>\n\n\n\n<p><strong>Percentiles<\/strong> divide a data set into 100 equal parts. For example, the <strong>25th percentile<\/strong> means that 25% of the data points fall below that value.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Example: Ages of People in a Barangay<\/h2>\n\n\n\n<p>Imagine we have the ages of people living on a street in a barangay (neighborhood) in the Philippines. We want to find the <strong>75th percentile<\/strong>, meaning that 75% of the people are younger than a certain age.<br><br><strong>ages = [5, 31, 43, 48, 50, 41, 7, 11, 15, 39, 80, 82, 32, 2, 8, 6, 25, 36, 27, 61, 31]<\/strong><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Step 1: Finding the 75th Percentile<\/h2>\n\n\n\n<p>The <strong>75th percentile<\/strong> means that 75% of the people are younger than or equal to a certain age. In this case, the <strong>75th percentile<\/strong> value is <strong>43<\/strong>. This means that 75% of the people in this group are 43 years old or younger.<\/p>\n\n\n\n<p>To calculate the 75th percentile in Python, we use the <strong>NumPy<\/strong> module:<\/p>\n\n\n\n<div class=\"wp-block-codemirror-blocks-code-block code-block\"><pre class=\"CodeMirror\" data-setting=\"{&quot;showPanel&quot;:true,&quot;languageLabel&quot;:&quot;language&quot;,&quot;fullScreenButton&quot;:true,&quot;copyButton&quot;:true,&quot;mode&quot;:&quot;python&quot;,&quot;mime&quot;:&quot;text\/x-python&quot;,&quot;theme&quot;:&quot;seti&quot;,&quot;lineNumbers&quot;:true,&quot;styleActiveLine&quot;:false,&quot;lineWrapping&quot;:false,&quot;readOnly&quot;:true,&quot;fileName&quot;:&quot;&quot;,&quot;language&quot;:&quot;Python&quot;,&quot;maxHeight&quot;:&quot;400px&quot;,&quot;modeName&quot;:&quot;python&quot;}\">import numpy\n\nages = [5, 31, 43, 48, 50, 41, 7, 11, 15, 39, 80, 82, 32, 2, 8, 6, 25, 36, 27, 61, 31]\nx = numpy.percentile(ages, 75)\n\nprint(x)<\/pre><\/div>\n\n\n\n<p>The output will be <strong>43 <\/strong>meaning 75% of the people are younger than or equal to 43 years old.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Step 2: Finding the 90th Percentile<\/h2>\n\n\n\n<p>Let\u2019s say we want to find the <strong>90th percentile<\/strong>, which tells us the age below which 90% of the people are younger. In this case, the 90th percentile value is <strong>61<\/strong>, meaning that 90% of the people are younger than or equal to 61.<\/p>\n\n\n\n<p>To calculate the 90th percentile in Python, we again use the <strong>NumPy<\/strong> module:<\/p>\n\n\n\n<div class=\"wp-block-codemirror-blocks-code-block code-block\"><pre class=\"CodeMirror\" data-setting=\"{&quot;showPanel&quot;:true,&quot;languageLabel&quot;:&quot;language&quot;,&quot;fullScreenButton&quot;:true,&quot;copyButton&quot;:true,&quot;mode&quot;:&quot;python&quot;,&quot;mime&quot;:&quot;text\/x-python&quot;,&quot;theme&quot;:&quot;seti&quot;,&quot;lineNumbers&quot;:true,&quot;styleActiveLine&quot;:false,&quot;lineWrapping&quot;:false,&quot;readOnly&quot;:true,&quot;fileName&quot;:&quot;&quot;,&quot;language&quot;:&quot;Python&quot;,&quot;maxHeight&quot;:&quot;400px&quot;,&quot;modeName&quot;:&quot;python&quot;}\">import numpy\n\nages = [5, 31, 43, 48, 50, 41, 7, 11, 15, 39, 80, 82, 32, 2, 8, 6, 25, 36, 27, 61, 31]\nx = numpy.percentile(ages, 90)\n\nprint(x)<\/pre><\/div>\n\n\n\n<p><\/p>\n\n\n\n<p>These calculations are helpful in understanding the distribution of data. For example, you can use percentiles to understand income levels in different areas of the Philippines, or to analyze how fast a jeepney or bus completes a route compared to other vehicles. By calculating percentiles, we can identify trends and make data-driven decisions.<\/p>\n\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>What are Percentiles? In statistics, percentiles help us understand how a data set is distributed. A percentile tells us the [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"class_list":["post-403","post","type-post","status-publish","format-standard","hentry","category-python"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Percentiles - Python Tutorial<\/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:\/\/techkubo.com\/python\/percentiles\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Percentiles - Python Tutorial\" \/>\n<meta property=\"og:description\" content=\"What are Percentiles? 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