The world of IT and AI never stands still, and the only way to keep up is to keep learning every single day. I firmly believe that sharing your own knowledge and breaking down new concepts on real data is the best path to understanding. Today we continue exploring data visualization — a foundational discipline in the world of AI and analytics. This time we will break down six types of bar charts: Grouped Bar, Stacked Bar, 100% Stacked Bar, 3D Grouped Bar, 3D Stacked Bar, and 3D 100% Stacked Bar. The data is real: Requests from Cloudflare for the period from September 1 to October 1, 2026, for the site devitpro.uz, along with Edge Requests from Vercel for the period from June 28 to September 1, 2026.

These are not abstract textbook examples. Behind them are 64.87 thousand requests through Cloudflare from 60 countries, 2.3 thousand unique visitors, and 51,785 requests through the Vercel Edge Network from 19 regions worldwide. The live statistics of a working project are the perfect training ground.

My goal: not just to show six beautiful charts, but to teach you to think in visualizations. When you look at data and immediately understand which type of bar chart will reveal it best — that is the real skill of an analyst and an engineer.

The Data We Are Working With

Before building charts, it is important to understand the source data. We have two independent sources. The first is Requests (Cloudflare): request statistics through the global Cloudflare network for the period from September 1 to October 1, 2026. The second is Edge Requests (Vercel): request statistics processed at the peripheral nodes of the Vercel Edge Network for the period from June 28 to September 1, 2026.

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.

64.87k
Total requests
Total requests for 01.09.2026 — 01.10.2026
2.3k
Unique visitors
Total Unique Visitors over the previous 30 days
210
Maximum per day
Maximum Unique Visitors in a single day
29.88k
Requests through Cloudflare
Uncached Requests over the previous 30 days

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.

Six Types of Bar Charts: Breaking Down Each One

Below are six charts, 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.

1. Grouped Bar Chart — Requests by host and country
Grouped columns compare requests across the top Cloudflare hosts: www.devitpro.uz and devitpro.uz.
www.devitpro.uz — 36,050 · devitpro.uz — 20,290 · other sources — 8,530
2. Stacked Bar Chart — Vercel Edge regions by month
Stacked columns show how months add up to the total Edge Requests traffic volume.
Jun 1 – Jul 1 — 14,443 · Jul 1 – Aug 1 — 8,897 · Aug 1 – Sep 1 — 23,267
3. 100% Stacked Bar Chart — Share of Vercel regions
Normalized columns bring each month to 100% — you can see how the traffic structure changes.
Hong Kong dominates all three months: 56.1% of total traffic.
4. 3D Grouped Bar Chart — Top 10 Cloudflare countries
The 3D effect adds depth: grouped volumetric columns across leading countries.
United States — 8,350 · Uzbekistan — 5,576 · Netherlands — 2,112 · Italy — 1,953 · Germany — 1,576
5. 3D Stacked Bar Chart — Vercel Edge regions
Volumetric stacked columns show the contribution of each region to total traffic.
The top 5 Vercel Edge regions account for 88.5% of all traffic.
6. 3D 100% Stacked Bar Chart — Cloudflare countries
3D columns normalized to 100%: comparing traffic structure across countries.
Top 5 Cloudflare countries: United States, Uzbekistan, Netherlands, Italy, Germany.

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.

United States US
8,350 12.9%
Uzbekistan UZ
5,576 8.6%
Netherlands NL
2,112 3.3%
Italy IT
1,953 3.0%
Germany DE
1,576 2.4%
United Kingdom GB
1,244 1.9%
Belgium BE
887 1.4%
Japan JP
855 1.3%
Russia RU
768 1.2%
Canada CA
727 1.1%
Brazil BR
620 1.0%
China CN
406 0.6%
Poland PL
377 0.6%
Australia AU
306 0.5%
Spain ES
285 0.4%
Saudi Arabia SA
280 0.4%
France FR
280 0.4%
Israel IL
266 0.4%
Romania RO
201 0.3%
Czech Republic CZ
155 0.2%
Finland FI
126 0.2%
Luxembourg LU
108 0.2%
Switzerland CH
80 0.1%
Sweden SE
77 0.1%
Bangladesh BD
77 0.1%
Indonesia ID
75 0.1%
Denmark DK
69 0.1%
India IN
52 0.1%
Ukraine UA
50 0.1%
UAE AE
44 0.1%
Kazakhstan KZ
43 0.1%
Hungary HU
27 0.0%
Thailand TH
24 0.0%
Mexico MX
22 0.0%
Iran IR
21 0.0%
Lithuania LT
21 0.0%
Uganda UG
20 0.0%
Ireland IE
20 0.0%
New Zealand NZ
20 0.0%
Jamaica JM
19 0.0%
Austria AT
19 0.0%
South Africa ZA
17 0.0%
Turkey TR
17 0.0%
Colombia CO
9 0.0%
Vietnam VN
7 0.0%
Venezuela VE
5 0.0%
Philippines PH
5 0.0%
Iceland IS
5 0.0%
Slovenia SI
5 0.0%
Korea KR
4 0.0%
Argentina AR
4 0.0%
Bolivia BO
4 0.0%
Portugal PT
2 0.0%
Togo TG
2 0.0%
Bulgaria BG
2 0.0%
Latvia LV
2 0.0%
Azerbaijan AZ
2 0.0%
Malaysia MY
2 0.0%
Peru PE
1 0.0%
Paraguay PY
1 0.0%
Guatemala GT
1 0.0%
Croatia HR
1 0.0%
Belarus BY
1 0.0%
Bhutan BT
1 0.0%

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.

Hong Kong hkg1
29,043 56.1%
San Francisco, USA sfo1
7,739 14.9%
Washington, D.C., USA iad1
4,045 7.8%
Frankfurt, Germany fra1
3,543 6.8%
Cleveland, USA cle1
2,649 5.1%
Paris, France cdg1
1,695 3.3%
Stockholm, Sweden arn1
950 1.8%
Portland, USA pdx1
592 1.1%
London, United Kingdom lhr1
532 1.0%
Singapore sin1
304 0.6%
Montréal, Canada yul1
260 0.5%
Mumbai, India bom1
227 0.4%
Sydney, Australia syd1
65 0.1%
São Paulo, Brazil gru1
43 0.1%
Dublin, Ireland dub1
43 0.1%
Tokyo, Japan hnd1
30 0.1%
Seoul, South Korea icn1
24 0.0%
Osaka, Japan kix1
7 0.0%
Cape Town, South Africa cpt1
1 0.0%

What I Took Away From This Experience

After building all six bar charts, I drew several important conclusions. Here they are — short and to the point.

  • Grouped Bar Chart — for comparison. When you need to compare several categories side by side, this is the best choice.
  • Stacked Bar Chart — for the whole. Shows how parts add up to a total volume.
  • 100% Stacked Bar Chart — for structure. Brings each category to 100% — you can see how shares change.
  • 3D Grouped Bar Chart — for presentations. The 3D effect is impressive, but perception accuracy drops.
  • 3D Stacked Bar Chart — for the wow factor. Volumetric stacked columns look great on slides.
  • 3D 100% Stacked Bar Chart — for emphasis on structure. 3D + normalization = maximum visibility of shares.
  • 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 Bar Charts in 2026?

The answer is a resounding yes. In a world where data has become the new oil, the ability to visualize it 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. Bar charts are the best tool for comparing categories and analyzing structure.

But there is a nuance. Each type of bar chart has its own area of application. Grouped — for comparison. Stacked — for the whole. Normalized — for structure. 3D versions — for impression. 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 chart 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.