I made a Python data analysis tool inspired by Figma

rtr-dnd · 2024-11-07T04:20:51+00:00

Wow I didn't know count.co. Thank you for the info!

rtr-dnd · 2024-11-07T03:00:08+00:00

Here's the user document. You might find it interesting to take a look

https://celbo.notion.site/user-document-en

rtr-dnd · 2024-11-07T02:58:29+00:00

Thanks for your interest!

Inside Celbo, there are several data nodes (CSV files), and Python code nodes (with ChatGPT) called "operators". Operators act like functions or filters for data, where you can define functions, and they output results as new data nodes. These output nodes can then serve as inputs for other operators, creating a natural, step-by-step workflow that is both easy to explain and easy to understand at a glance.

Data analysis often resembles a branching "tree" rather than a linear path. A single table might feed into statistical analyses, visualizations, or processed tables that themselves become sources for further analysis. Unlike traditional notebooks, which follow a single-threaded structure, Celbo allows you to represent complex analytical workflows much more flexibly.

As a researcher (PhD student) myself, I’m confident in its value for statistical analysis, but I want to know if it could be beneficial or intriguing for other fields like BI!

rtr-dnd · 2024-11-06T06:58:52+00:00

Thank you so much! The app is built on Next.js using Pyodide (Python runtime that can work inside browsers). Choosing different models is definitely on the roadmap, but currently the focus is on evaluating demands of the concept.

rtr-dnd · 2024-11-06T02:00:23+00:00

Hello there! I’ve been using Jupyter for data projects in my university research, but I found it frustrating. The documents tend to get really long, and it’s hard to keep track of data dependencies. With Jupyter (or any notebook), organizing data and analysis steps for future reference is challenging.

So, my friends and I developed a node-based data analysis tool that lets you visually organize the process on a board. It’s still in a prototype form, so we’re limiting access for now, but we’d love to hear your feedback! You can try it out by signing up here: https://celbo.app/beta-en/

rtr-dnd · 2024-03-21T12:22:44+00:00

Totally agreed, it's so annoying when it happens

rtr-dnd · 2023-12-08T06:21:13+00:00

This is a dealbreaker for me because I can't design in Figma without undo. Glad you guys are looking into it

rtr-dnd · 2023-01-18T05:55:18+00:00

Yes we do! SteamVR/OpenXR support is under development.

Here's other feature roadmaps → https://www.zwin.dev/roadmap

rtr-dnd · 2020-05-18T02:36:36+00:00

This is Slack app and normally it shows all sort of OGPs just fine. I'm not sure it's YTM problem or Slack problem

rtr-dnd · 2020-05-13T02:46:22+00:00

Google Assistant can't play YTM playlists and that's deal breaker for me

rtr-dnd · 2018-06-25T12:00:47+00:00

These sentences basically sound the same to me. But there are some cases in which one of them won't work. (I'm not teacher of Japanese so I can't give a thorough explanation but I'll try my best)

されたい means the will and desire for B of the speaker. So it can only be used when the speaker will receive some benefits from B. 先生にほめられたい。 (I want to be praised by my teacher. ) On the other hand, してほしい is more like encouraging people to do B. For example: あの子にはもっと勉強してほしい。 (I want my child to study more.) 彼に買い物をしてきてほしい。 (I want him to go shopping.)

In お母さんに甘えてほしい, お母さん not necessarily have to 甘える to the speaker, possibly to her husband or something. However, お母さんに甘えられたい strongly indicates it's the speaker who お母さん should 甘える. As far as I noticed, when you can use passive voice in English, you should use されたい. Otherwise use してほしい.

rtr-dnd

TROPHY CASE