<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/e2ba6d12f79343de8ed869838cb71288&quot; frameborder=&quot;0&quot; width=&quot;1758&quot; height=&quot;1318&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1318</height><width>1758</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1318</thumbnail_height><thumbnail_width>1758</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/e2ba6d12f79343de8ed869838cb71288-0d1e3de6b6f019e4.gif</thumbnail_url><duration>288.14</duration><title>Symbol Map Part 1</title><description>In this video, I walk you through the process of creating a simple map using Data Wrapper, focusing on air pollution data from cities in Asia for the year 2019. I sourced this data from stateofglobalair.org, which provides PM2.5 pollution levels. We’ll select a basemap of Asia, input our prepared data, and match the relevant columns for city names, latitude, longitude, population, and pollution values. I encourage you to follow along and replicate this mapping process with your own data. Let’s get started!</description></oembed>