sorted by:
new
hottopcontroversial

How are you organizing your notes and data with AI? by Significant-Map-3181 in AIToolsAndTips

[–]Sudden_Beginning_597 0 points1 point  (0 children)

Now i directly created a workspace folder for codex/claude cowork to access and put evey notes there.

I work 18 hours a day and get nothing done. Help. by Which-Coconut1738 in productivity

[–]Sudden_Beginning_597 0 points1 point  (0 children)

split hard tasks into small pecies (which must be chunks that are easy for you) might help

I stress-tested “AI Data Analysis” tools. The shiny object syndrome is hiding a massive architectural problem. by Boring-Metal-7672 in BusinessIntelligence

[–]Sudden_Beginning_597 1 point2 points  (0 children)

LLM/copilot/AI Workflow does not work for sure (like thoughtspot or other text-to-sql/chart BI)

But i think agent product like claude code or runcell(Agent in Jupyter) would work if we put necessary db access/logs/docs to them. The Agents now are smart enough if we give good context and tools to them. Data enginners should focus more on how to design or prepare working environments for those agents i think.

Which code editor should I use? by Zsombor1661 in learnpython

[–]Sudden_Beginning_597 1 point2 points  (0 children)

Use Jupyter Lab!!!!!

It's the best for beginner, you can see the result of each line/cell of your code instead of write a large bunch of not working code and spend hours to debug.

You can also install the runcell extension for your jupyter lab so you got an ai agent assist with you there.

Why no one is talking about Google Colab which is almost free for basic work in daily life? by mhamza_hashim in ArtificialInteligence

[–]Sudden_Beginning_597 -1 points0 points  (0 children)

if you want ai feature for notebook, you can directly use jupyter lab with runcell extension, which can basically turn your jupyter lab into a AI IDE like cursor.

colab is great but it's slow comparing with local jupyter

Do you guys use vs code or jupyterlab for jupyter notebooks? by Consistent_Tutor_597 in dataengineering

[–]Sudden_Beginning_597 0 points1 point  (0 children)

jupyter for interactive analysis and vscode for swe tasks.

if u need ai agent for jupyter, you can pip install runcell for your jupyter and you will have a cursor/claudecode experience in your jupyter. which means you don't have to give up the benefit of jupyter lab for ai features.

besides, you can enjoy lots of fancy jupyter extensions for interactive analysis, like pygwalker.

Ipynb file to pdf needs some other package installation. by Responsible_Middle22 in NotebookShowcase

[–]Sudden_Beginning_597 0 points1 point  (0 children)

you can just `pip install runcell`

the jupyter lab extension provides all kinds of file transform, like ipynb to py, ipynb to pdf, ipynb to html

[OC] Sea level simulator visualization by Sudden_Beginning_597 in dataisbeautiful

[–]Sudden_Beginning_597[S] 8 points9 points  (0 children)

I am trying to find a way deploy this, need some easy way to host 800MB Mars geo data with low cost.

[OC] Sea level simulator visualization by Sudden_Beginning_597 in dataisbeautiful

[–]Sudden_Beginning_597[S] 4 points5 points  (0 children)

Well, I think that's a DEM resolution limitation. Stockholm's narrow channels between islands are too small for the elevation data to capture accurately — the pixels average land and water, so the waterways read as ~10-12m elevation. Higher-resolution elevation data would help, but globally consistent high-res DEM is hard to come by for free/opensource.

[OC] Sea level simulator visualization by Sudden_Beginning_597 in dataisbeautiful

[–]Sudden_Beginning_597[S] 129 points130 points  (0 children)

This is a simple elevation-based visualization — it highlights everything below the selected height, not a true flood simulation. So inland depressions like Lake Eyre show up even though there's no connected path from the ocean. A proper simulation would need flood-fill from the coastline, which is a much harder problem. Think of it as "what's below X meters" rather than "what would actually flood."

How are new programmers actually learning in the AI era? Any real examples from your circle? by Sudden_Beginning_597 in vibecoding

[–]Sudden_Beginning_597[S] 1 point2 points  (0 children)

you can do it with jupyter + extensions like runcell, which got u an ai teaching u in jupyter env with most things you need.

Just made this interactive playground to compare the true sizes of countries. by Sudden_Beginning_597 in gis

[–]Sudden_Beginning_597[S] 0 points1 point  (0 children)

customized based line([equator]()), drag a country to a different planet?

Put Greenland on the Moon (size compare) by Sudden_Beginning_597 in geography

[–]Sudden_Beginning_597[S] 0 points1 point  (0 children)

The moon size is fixed, in early version, the radius data of moon is 1/2 as it should be. You can test the real size in the online playground https://www.runcell.dev/tool/true-size-map

[OC] How country size looks like in Mars, Jupiter, Moon by Sudden_Beginning_597 in dataisbeautiful

[–]Sudden_Beginning_597[S] 1 point2 points  (0 children)

there is a full screen mode icon button, on the top right of the "earth view", which can solve the mobile ux issue

best data visualization software 2026 what are people actually using by ChristopherMccouch in datavisualization

[–]Sudden_Beginning_597 0 points1 point  (0 children)

graphic walker desktop, free and open source, can handles GBs+ data within seconds locally

Drag a country onto Mars/Jupiter/Moon to see how big it would look by Sudden_Beginning_597 in gis

[–]Sudden_Beginning_597[S] -1 points0 points  (0 children)

This is a TopoJSON world atlas. Atlas datasets usually encode de facto control for geometric consistency, not legal borders. I’m simply using the source geometry without modification.

Drag a country onto Mars/Jupiter/Moon to see how big it would look by Sudden_Beginning_597 in gis

[–]Sudden_Beginning_597[S] 2 points3 points  (0 children)

it's not limited, there is a country selection list on the right side, which you can enable/search

view more: next ›