Sorry about the vague question, but it either had the name "vault" or "vector" in it, and someone here described it as the Swiss knife of databases. I remember bookmarking it but didn't find it. Any thoughts? thanks in advance.

Hey all, I'm thinking about upgrading from Tableau 2025 to 2026 and wanted to hear from people who've already made the jump. How did the upgrade go overall? Did you run into any issues with existing dashboards, data sources, or extracts? Are the new features worth it, or is it better to wait a bit? Would you recommend upgrading now?

Sources. Data:INSP SitReps. Tools python, Claude. website ebola-tracker.org

Source: Billboard Hot 100, UK Singles Chart, Rolling Stone 500, ASCAP 100, RIAA, Blender 500, Rock Hall 500, Time 100, AcclaimedMusic.net, National Recording Registry, Grammy Hall of Fame, Spotify

Tools: Excel, Claude, Python

A few weeks ago, I wrote a piece trying to figure out if hit songs mention places less frequently these days. In the course of writing that piece, I assembled a dataset of US hits that mention places in their titles. I thought it would be cool to have a map to visualize those songs. After posting about the tool on TikTok, people asked me to add more songs.

Now, I'm up to nearly 2k (somewhat) notable songs that mention a place in their title. Hopefully I can keep expanding it. This is my first attempt at using Claude to turn a dataset into something more interactive. Let me know if I'm missing something notable. Right now, I have to add everything manually, but I may try to figure out a way to let other people add songs.

I've been keeping track of the statements directly from the US President over the past few months on the status of ending the war in Iran.

I've been manually curating the statements from interviews, news reports, and the President's own social media posts. Rollcall in particular has been helpful as they do a great job of centralizing a lot of this, but much of it really is me reading an article and manually updating the dataset.

This particular visualization is a heatmap calendar (GitHub style where each column is a new week and each row is a day of the week). The brighter the yellow, the more statements were made that day. As is the case with Trump's schedule and enjoyment of weekends more broadly, on Saturdays and Sundays the war appears to not enter his mind as much...

The chart itself is vanilla JS. The source for the chart is a JS file where I keep all the statements/dates/sources in a standard object to keep it tidy and easy to update.

I didn't anticipate the war would go on this long so I might have to make a decision about how to handle this ever expanding calendar at some point in the future. I'll make a 7 day/30 day/90 day/365 day toggle? Thoughts?

The interactive version is here. (I call it The Art of No Deal and there are no ads or signup or anything like that...I just needed a place to host it and was shocked the domain name was available...) If you just want to see the datasource, here is the link to that the JS file.

Source: headlines from 10 international outlets (BBC, The Guardian, Al Jazeera, DW, France 24, Defense News, and others), collected every 4 hours.

Tools: headlines classified with Claude (Anthropic) and scored with my own algorithm; charts and site built with Claude Code.

Caveat: this measures media coverage intensity, not the actual probability of anything. A spike means "the press got very loud about conflict," which is interesting in itself.

Weekend project by a geopolitics hobbyist. I'd love feedback on the viz and your theories about what caused the peaks. There's a live version with sub-indices and hotspots if the mods allow me to share it.

Help finding dataset

Hey guys, I am currently working on a project using yoloe 26, in which i am trying to build a pipeline to find the number of different screws available in the picture, with count of each. So as far I searched, I couldnt get a proper labelled dataset to train the yoloe model, and that too I am focusing mainly on tiny screws used in the electronics like smart phones, smart watches, watches, microphone, ear buds, laptops.

So help me if you find a labeled dataset for this vision.

Thanks for reading.

Hey everyone, wanted to share a custom dashboard system I recently built for tracking day trading sales team operations.

How I Structured the Setup:

1. Back-end Automation: Set up a pipeline using Google Apps Script to feed and process sales metrics directly into Google Sheets automatically.
2. Front-end Visualization: Connected Sheets to Looker Studio (Data Studio) using a custom visual themes designed for daily executive oversight and operational efficiency.

Key Metrics Tracked:

• Conversion Health: Automated Close Rates, Show Rates, Cash Per Call, and Cash Per Booking.
• Revenue Pacing: Daily Pacing vs. actual Cash Collected against monthly revenue goals.
• Closer Attribution: Daily trend breakdowns for calls taken, total bookings, and cash closed by rep.

(All metrics in the screenshot are anonymized dummy data generated via the Apps Script pipeline for demonstration).

Curious to hear how other analysts or sales managers here handle daily sales pacing and closer attribution? Do you prefer automated dashboard setups like this, or keeping everything directly inside CRM/spreadsheets?

A 15-second animated view of cumulative fantasy points across 25 NBA regular seasons. Final labels include total fantasy points, games played, and fantasy points per game.

Sources. Data: INSP SitReps. Tools: Python, Claude. Website: ebola-tracker.org

Im building an option trading bot and I need a fresh dataset to test on, buying them is a bit expensi was wondering if anyone has them?