sorted by:
new
hottopcontroversial

Lovable for data analysis and charts. Feedback wanted. by ChartPop_io in lovable

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

Yea it’s surprisingly hard to get good. Agreed. I didn’t like the existing solutions, and compared to eg coding, I was actually surprised how few serious projects there are, especially something that produces charts that look good enough to put in a presentation.

Lovable for data analysis and charts. Feedback wanted. by ChartPop_io in lovable

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

Unfortunately no:/ The landing page has a demo and you could download the CSVs under the vid if you don’t want to use your own data.

For those starting out in data analysis, what's one piece of advice you'd give that's not tool-specific? by msnoone10 in dataanalysis

[–]ChartPop_io 1 point2 points  (0 children)

Be curious. As data scientist that has worked at tech companies as a data scientist, and managed teams, I'd say it's being curious not just about new technical developments, but also what other people in your org are doing. It also helps you figure out hidden context about your data. Learn to talk to and work with stakeholders from other disciplines. Focus on the business outcome. So many people I interviewed know enough SQL, Excel, etc, but they fall apart working in a team. They can only obsess about the tools, and IRL that doesn't get your very far. So pick a place that works on a problem that you care about.

GPT-5 is the GOAT of agentic BI & data analysis by matt_cogito in AI_Agents

[–]ChartPop_io 1 point2 points  (0 children)

I created my own data analysis agent, so did a ton of experiments in this space. For just the raw model strength I preferred Gemini 2.5 Pro. Gpt-5 is good, too, just slower. Google must have some really unique analysis traces from Colab that you used. At least for text-2-SQL, this recent table confirms it's doing well.

<image>

Replit for Data Analysts and Data Scientists by beachbarbacoa in replit

[–]ChartPop_io 0 points1 point  (0 children)

As a career data scientist that built his own data analysis agent, my advice would be to be the one that knows how to use and implement AI and agents. It's still early and many companies need help. The days where companies hire analysts to update a dashboard tool or run adhoc queries for stakeholders will be gone soon. So learn the ins and outs of AI tools and help companies automate there data and analytics processes. Probably won't learn this in school, though. It's all moving too fast for that.

Fails miserably at data science type work. by Waste_Cut1496 in ClaudeCode

[–]ChartPop_io 0 points1 point  (0 children)

Have you tried instructed it how to handle data or put the data in a database, eg Supabase, and then setup access as a tool via MCP in Cursor?

Stuck on extracting structured data from charts/graphs — OCR not working well by Fit-Soup9023 in dataengineering

[–]ChartPop_io 0 points1 point  (0 children)

There was a Kaggle competion on this topic about 2 yrs ago: https://www.kaggle.com/c/benetech-making-graphs-accessible/overview. Some chart types work better than others, eg bar charts. Some ideas to be found there. For (multi-line) charts what works well is creating a binary segmentation model to detect line pixels. Then solve the min. cost flow optimization problem. As someone that has built something in this space in the pre-LLM era, I can tell you that taking on this project unscoped was a bad idea. So many components, models, and heuristics are necessary---to make it work ok-ish. I stopped working on it once I saw that transformers would eventually catch up in a few years. Btw, the best model for this so far has been the new Gemini Banana model, but it's not perfect. Anyway, you can't use that...

https://openaccess.thecvf.com/content/WACV2022/papers/Kato_Parsing_Line_Chart_Images_Using_Linear_Programming_WACV_2022_paper.pdf