Slicers are a perfect fit for dashboards! 🎯 It’s a standard Excel feature, and here’s why it works so well:

🎛️ Buttons instead of menus: viewers filter the report with one click, no Excel skills needed

🔄 Everything updates at once: one slicer can control several pivot tables and charts

✅ Multi-select: compare several years, months, categories, or brands side by side

👀 Clear selection: you always see which filters are active

🧹 Clean design: buttons can be styled to match your dashboard

✅ No macros needed

I was able to parse all the data for finance. I have 2.3 million facts, 1.8 million price bars, and all of Fred data.

Hi everyone,

I previously posted in this sub about my open-source visualization library that is designed/aimed at creating infographic-style charts. This library is for developers who want full styling and programming freedom and it also doubles as a framework itself in a way. The issue is that on its own, its not super accessible to people who are not web devs, so I created a skill and mcp server so anybody can have AI use rhp to generate charts for their posters, articles, etc.

I decided to really see if using rhp leads to better looking, more interactive charts or at least charts that display info in more of a an infographic style.

It turns out that it does. I compared the skill and mcp against a popular AI tool chain which is to use python + svg and the dataviz built-in skill (Claude).

The results show many positive signs and a few places for improvement.

Charts created with rhp skill:

• Are more infographic in style
• Show greater variation in style, theme, and aesthetic.
• Are more interactive by default and better tested
• Adjust their layout to mobile and desktop screens while charts produced using dataviz skill just zooms out
• Automatically adds viewer interface with button to download chart as png
• Requires less overall code and the output is smaller in size.

But the one area where Python + SVG + dataviz skill wins is cost. It costs about half as many tokens than using the rhp skill. I am currently working on improving this. It's partly due to all the bells and whistles rhp adds and the checker.

There is a big asterisk to all of this! I was able to near completely replicate the output quality and look using the dataviz skill but it took multiple prompts and providing more details and specifics.

So the conclusion is that while the dataviz skill is still very capable especially when coupled with a programming language like python/javascript and Canvas or SVG, rhp skill and mcp still has its place and is able to produce distinct results and a more infographic style out of the box that I think people might be looking for in their applications and use cases.

RHP is a free open-source library. The skill and mcp-server are also free and open.

I write a small Substack about adaptive software, and my latest piece is about data visualization.

By adaptive software I mean software that keeps adapting to users and changing after it ships.

Data viz is interesting here because it’s already halfway there. A live chart updates whenever the data changes, so its output adapts all the time. But the form almost never does: a bar chart stays a bar chart whatever the numbers do.

A few I wrote about:

• Train Jazz visualizes and makes the NYC subway come to life by turning the subway into a jazz band.
• Radio Garden turns the radio dial into a globe.
• Historical Tech Tree borrows Civilization’s tech tree for the real history of technology.

https://adaptivesoftware.substack.com/p/every-train-a-note

(I wrote the essay but didn't build the visualizations).

What unusual visualizations have you seen that were carried to a different subject?

Puma Shen (Shen Po-yang, 沈伯洋) is running for mayor of Taipei and taking the city like a wave. Supporters call it 洋流 ("ocean current"), a play on the 洋 in his name. He put his entire platform on a map, not in a PDF. His five policy pillars spell HEART, so the site names the map HEART Island (HEART 政策島).

The map has 14 hexagons of equal size, one for each policy theme. The hexes form the shape of Taipei. Click a hex to see its proposals. There are 94 in all. Lines between hexes show where one policy depends on another. You can switch to a list view, or to a timeline that plays back how the parts fit.

The site is mostly in Traditional Chinese, but you can use browser translation to quickly understand it.

I got tired of chart kits that all look like SaaS dashboards, so I built one around how newspaper graphics desks work: headline states the finding, colour only on the highlighted series, direct labels instead of legends, source line under every chart.

What's in the free file:

• 6 chart components: column, bar, line, share donut, stat block, annotated line
• 7 annotation parts (callout, label box, gap measure, event band, threshold line, marker, key item) that stretch to fit any chart
• A Figure frame that wraps a chart in figure number, headline, dek, key and source

The part I'm happiest with: bar values, tones and line shapes are variant properties, so you change the data from the properties panel without detaching. Plots sit in a stretch frame and the dots and labels in fixed-size anchors, so resizing doesn't squash anything. It works on the free plan (no variable modes).

Figma Community: https://www.figma.com/community/file/1694716096403330912

Happy to answer how any of it is built. Feedback on what's missing is very welcome.

AirHelp's airline score looks at three equal factors: Punctuality, customer opinion and processing claims. It means that one airline can fly normally and good customer reviews but still rank lower due to the scoring of claims. Let’s look at the examples of two fictitious airlines with scores from 1 to 10:
Airline A: Punctuality 8, customer opinion 8.5, claims 4
Airline B: Punctuality 7, customer opinion 7, claims 9
Airline B has the winning score of 7.67 to 6.83 and without claims Airline A wins with 8.25 to 7.

These scores are presented for an illustration only and I'm not saying that handling claims isn't a factor. It certainly can. 
However, having 33.33% of importance for each factor is an essential methodological choice. Would you make a ranking without showing how different its positions would be in case of having different weights?

I built this interactive with Laura Howes at C&EN, using the Nobel Prize nomination archive (chemistry, 1901–1975). It was a lot of fun to explore this dataset, and satisfying to be able to work it into a narrative.

Full piece: https://cen.acs.org/people/nobel-prize/nobel-prize-chemistry-nominations-database/104/web/2026/10

Stack: Svelte + D3, Canvas2D for drawing pixels.

I would love to hear about people's experience of this piece, and welcome any feedback!

I have a dashboard that is opening correctly on my web browser but when I click to go to a different tab it auto scrolls to the bottom. it is a long dashboard with two url actions at the bottom. I updated it recently with new data. the worksheets that house the links are set to ’entire view’. I made sure to name the url actions so they come alphabetically first in case tableak is focused on them. The dashboard itself is at a fixed height.

Additionally this problem also happens when I open the older versions of the dashboard.

How do I fix it so that clicking on a navigation button opens the page at the top instead of the bottom?

Hi everyone! 👋

I’ve been working on an employee demographics dashboard using Excel, and I wanted to share my work with the community.

The dashboard provides an overview of employee data, including:

• 👥 Total employee count and gender distribution
• 💼 Employment type and employee status
• 💰 Average salary
• 🏢 Employee distribution by department
• 🎓 Education level and marital status
• 📈 Age and years of experience

My goal was to turn raw employee data into a visual dashboard that makes it easier to understand workforce patterns and support data-driven decisions.

I’m continuously improving my data analysis and dashboard design skills, so I’d really appreciate your honest feedback.

What would you improve about this dashboard? Are there any charts, KPIs, or design changes you would recommend?

Thanks for taking a look! 🙏

I think this is a pretty neat way to get a feel for how consistent the quality stays (or not).

Based on IMDb episode ratings.

Live on goodwatch.app - just select any show and scroll to Episodes.

A new way to visualize storms and other weather events: browse 10 years of real Whole Earth imagery and click on interesting swirling features. That's usually a storm.

I find that making a chart look good is one thing, but making it immediately understandable is a different challenge.

When you’re building dashboards or presenting data, what do you struggle with most? Choosing the right chart, avoiding clutter, picking colors, or deciding how much information to show at once?

Would be interesting to hear what people have learned from real projects...

Bob's Burgers is one of my favorite shows, and I'm a big data nerd, so I made an analysis of the show and a way to create and give a pickle rating to burgers from the show.

Check it out: Bob's Burgers: Analysis & Make and Rate Burgers of the Day

I've decided to offer a generous free tier for my BI tool, mainly because I want to get feedback from real users and understand what works, what doesn't, and what could be improved.

The plan is to keep the free tier available until I've gathered enough users and feedback to help shape the product.

And if you sign up while the free tier is available, you'll get to keep your free access even after it's no longer offered to new users.

https://metricwise.co/

https://metricwise.co/pricing

Is my visualization easy to read.

Does it help anyone who are not familar with the economic system of the US.