1.0Go Chart 简体中文https://www.go-chart.com/cncurtishttps://www.go-chart.com/cn/author/curtis/rich600338<blockquote class="wp-embedded-content" data-secret="Dm6XjFLAm3"><a href="https://www.go-chart.com/cn/understanding-100-stacked-area-charts/">Understanding 100% Stacked Area Charts</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://www.go-chart.com/cn/understanding-100-stacked-area-charts/embed/#?secret=Dm6XjFLAm3" width="600" height="338" title="《 Understanding 100% Stacked Area Charts 》—Go Chart 简体中文" data-secret="Dm6XjFLAm3" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! This file is auto-generated */ !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); </script> https://www.go-chart.com/cn/wp-content/uploads/sites/3/2024/10/img_6710ce523a764.png702413A 100% stacked area chart is a powerful visualization tool that allows you to display the relative contribution of multiple data series over a given time period, showing how each series contributes to the total. This type of chart is particularly useful when you want to emphasize the percentage share of each category while tracking changes over time. Key Concepts Normalization: In a 100% stacked area chart, the total of all series for a given category (e.g., time period) is normalized to 100%. This means that the height of the stacked areas represents the proportion of each category relative to the total. Time Series Data: This chart is often used with time series data, where the x-axis represents time intervals (days, months, years) and the y-axis represents the percentage of total values. Multiple Series Representation: Each area in the chart corresponds to a different category or data series. The areas are stacked on top of each other, making it easy to compare the contributions of