Charts: Map, Cartogram — Learning Data Visualization in IT and AI using Requests (Cloudflare) for devitpro.uz
We continue our journey into the world of data visualization. Not long ago we broke down scatter and bubble charts in depth, and now the time has come for an equally powerful and expressive class — charts, maps, and cartograms. These are tools that let you see data not just as numbers, but as living geography: where your users live, how traffic is distributed across countries, and which regions form the core of your audience. We will explore three big classes: Chart, Map, and Cartogram. The data is real: Requests statistics from Cloudflare for the period from September 1 to October 1, 2026, and Edge Requests from Vercel for the period from June 28 to September 1, 2026, for the site devitpro.uz.
These are not abstract textbook examples — behind them are 64.87 thousand requests through Cloudflare from 60 countries worldwide, 2.3 thousand unique visitors with a daily peak of 210, and 51,785 requests through the Vercel Edge Network from 19 regions worldwide. The live traffic of a working project is the perfect training ground for honing visualization skills.
Key idea: charts, maps, and cartograms are not just "pictures with data." They are a tool that reveals geography, density, distribution, and relationships all at once. Once you learn to choose the right type, you will be able to spot patterns where others see chaos.
The Data We Are Working With
We have two independent sources. The first is Requests (Cloudflare) for the period from September 1 to October 1, 2026. The second is Edge Requests (Vercel) for the period from June 28 to September 1, 2026. Below are the key figures on which all charts are built.
Requests (Cloudflare) — 01.09.2026 — 01.10.2026
During this period, 64.87 thousand requests passed through Cloudflare, and the site was visited by 2.3 thousand unique visitors from 60 countries around the world. The maximum number of unique visitors in a single day was 210. 29.88 thousand requests went through Cloudflare, and all of them were uncached, meaning the responses were fetched from the origin server. This is an important metric: the higher the share of cached requests, the lower the load on the origin.
Distribution by host: www.devitpro.uz leads with 36.05 thousand requests, followed by devitpro.uz with 20.29 thousand requests.
Edge Requests (Vercel) — 28.06.2026 — 01.09.2026
During this period, 51,785 requests passed through the Vercel Edge Network, distributed across 19 regional nodes. Hong Kong (hkg1) leads with 29,043 requests — that is 56.1% of all traffic. This imbalance is explained by the geography of the main visitors and the location of the nearest edge nodes.
Breakdown by month: Jun 1 – Jul 1, 2026 — 14,443, Jul 1 – Aug 1, 2026 — 8,897, Aug 1 – Sep 1, 2026 — 23,267. August was the record month for traffic.
Three Classes of Visualization: Breaking Down Each One
Below are three big classes of visualization, each answering its own question. I built them on real data from Cloudflare and Vercel Edge so you can compare how perception changes depending on the type of visualization. All charts are interactive: hover over them to see exact values.
What is a Chart?
A chart is a graphical representation of data in which numeric values are displayed using geometric shapes: bars, lines, sectors, or dots. Charts are universal: they work with any categories that are not tied to geography. When you have a list of countries, hosts, or regions and their metrics — a chart will show it as clearly as possible.
What is a Map?
A map is a geographic representation of data in which each point is tied to real coordinates on the Earth's surface. Maps are indispensable when it is important to understand exactly where events happen: where your users live, where servers are located, and which regions of the world interact with your site the most.
What is a Cartogram?
A cartogram (choropleth map) is a type of map in which regions are colored based on the value of a specific metric. It is a hybrid of a map and a chart: the geographic shape is preserved, but the color conveys numeric data. Cartograms are ideal for comparing countries, regions, and areas on a single metric.
Regional Map of Requests (Cloudflare)
I have separated the regional statistics from Cloudflare into its own block — it deserves a dedicated section. The data covers 60 countries worldwide. Each card shows the number of requests and the percentage of the total. The top 3 countries are highlighted with a golden accent.
Regional Map of Edge Requests (Vercel)
The second block is the regional statistics from Vercel Edge. The data covers 19 regional nodes worldwide. Each card shows the number of requests and the percentage of the total. The top 3 regions are highlighted with a golden accent.
What I Took Away From This Experience
After building all seven visualizations, I drew several important conclusions. Here they are — short and to the point.
- Chart — for universal comparisons. When you need to compare categories without geographic ties, this is the best choice.
- Bar chart — for rankings. Top regions, top countries, top hosts — bars read instantly.
- Donut chart — for shares. When it's important to show who forms the core of your audience.
- Map — for geography. When you need to understand exactly where your users live.
- Heatmap — for density. Color shows traffic intensity without extra numbers.
- Cartogram — for comparing regions. A choropleth is ideal when you need to compare countries on a single metric.
- Bubble cartogram — for three dimensions. Geography + size + value — three variables in one visualization.
- Cloudflare and Vercel provide invaluable data. 64.87k + 51.79k requests are a live laboratory for learning visualization.
- Traffic geography is strategy. Looking at the distribution by country, you understand where infrastructure needs optimization.
Verdict: Is It Worth Learning Charts, Maps, and Cartograms in 2026?
The answer is a resounding yes. In a world where data has become the new oil, the ability to spot correlations and outliers is not a "bonus skill" but basic literacy for an engineer and analyst. Especially now, when AI generates huge volumes of data, a human needs to be able to quickly separate signal from noise. Charts, maps, and cartograms are the best tools for uncovering hidden patterns.
But there is a nuance. Each type of visualization has its own area of application. A chart — for universal comparisons. A map — for geography. A cartogram — for comparing regions on a single metric. Only by learning to choose the right type for the task will you become a true master of visualization.
For me personally, this breakdown was another step in understanding how data turns into knowledge. I realized that behind every visualization there is a story — a story of people, countries, technologies. And if you learn to read these stories, you will gain an advantage in any field of IT and AI.