{"version":"1.0","provider_name":"Data Science","provider_url":"https:\/\/www.clarku.edu\/data-science","author_name":"Jordan Aubin","author_url":"https:\/\/www.clarku.edu\/data-science\/author\/jaubin\/","title":"Spotify music recommendation system using EDA","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"TMS7KI5TJo\"><a href=\"https:\/\/www.clarku.edu\/data-science\/spotify-music-recommendation-system-using-eda\/\">Spotify music recommendation system using EDA<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/www.clarku.edu\/data-science\/spotify-music-recommendation-system-using-eda\/embed\/#?secret=TMS7KI5TJo\" width=\"600\" height=\"338\" title=\"&#8220;Spotify music recommendation system using EDA&#8221; &#8212; Data Science\" data-secret=\"TMS7KI5TJo\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/www.clarku.edu\/data-science\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","thumbnail_url":"https:\/\/www.clarku.edu\/data-science\/wp-content\/uploads\/sites\/58\/spotify.avif","thumbnail_width":900,"thumbnail_height":600,"description":"This system utilizes Spotify song data from 2019 to 2022 to uncover trends in \u201csong popularity\u201d through detailed visualizations, achieved via Exploratory Data Analysis (EDA) to identify pertinent features. By applying K-means clustering, the system groups genres based on their audio characteristics, highlighting genre similarities and enabling nuanced song recommendations. Leveraging SpotiPy, a Python library [&hellip;]"}