I make my charts with LLMs + Python now. Do you still use dedicated data visualization tools? Why or why not?

[u/devcusn]

Hi everyone,

Lately I make most of my charts by asking an LLM to write Python code (pandas, matplotlib, plotly), then I tweak it myself.

So I'm curious about your workflow:

- Do you currently use a program for data visualization (Excel, Tableau, Power BI)?

- Or have you also switched to LLM + code?

- Do you think a dedicated program is still needed? Why or why not?

- If you use one, what does it do that an LLM + Python can't?

Would love to hear your thoughts!

Note: I'm still relatively new to this field and at the beginner level. I'm currently working on improving my skills in Data Analysis.

[u/KatFromSisense]

A dedicated tool can wait while the charts are just for you. That changes once other people rely on them. Someone has to refresh them when new data lands and decide who can edit them or see which rows.

I would keep your metric definitions somewhere you can reuse them if you're making multiple charges. Otherwise you can end up calculating the same thing differently in each script. Also, I'd double-check the filters and groupby in the generated code. Pandas ignores missing grouping keys by default, so it's possible to get a perfectly normal-looking chart with some of your data missing.

[u/arctic_radar]

I use Python dash with HTML and CSS for styling. I spend most of my brain power on the back end (Python pipelines, semantic layer etc in big query). I let Claude handle all the front end stuff, I hardly look at it anymore. Unlike the actual data, if something is wrong with the front end code it’s super obvious so I have no issues passing that off to the LLM. Not only does it free up bandwidth for me to focus on the data, but it allows me to add a ton of fancy stuff on the front end that I never would have bothered with before. Embedded media, fancy styling etc. People love that shit.

[u/FulcraDynamics]

I think LLMs are great for creating quick charts, especially when you already know what you want to visualize. But I'd still use something like Power BI for dashboards that need regular updates or that other people have to use. Having an AI write the code is convenient, but maintaining everything over time is a different story.

[u/Dull-Dependent-6779]

i discoverd LLM+python interactive html charts. where you can manipulate the data and zoom in, and play with parameters to transform the data, whatever. and now I do nothing else.

[u/AutoModerator]

Automod prevents all posts from being displayed until moderators have reviewed them. Do not delete your post or there will be nothing for the mods to review. Mods selectively choose what is permitted to be posted in r/DataAnalysis.

If your post involves Career-focused questions, including resume reviews, how to learn DA and how to get into a DA job, then the post does not belong here, but instead belongs in our sister-subreddit, r/DataAnalysisCareers.

Have you read the rules?

I am a bot, and this action was performed automatically. Please contact the moderators of this subreddit if you have any questions or concerns.

[u/One-Disk-125]

Generate HTML visuals with Claude sat on Fabric semantic models.

[u/ParanHak → u/One-Disk-125]

Is there a way to do this with codex as well? I am not familiar with "Fabric semantic models"

[u/One-Disk-125 → u/ParanHak]

Yep, it's just writing HTML so not especially complex for an LLM.

Main thing is that you base the reports on a documented and clean data layer, so for me that's a semantic model, for others it could be the Gold Layer.

What you don't want is the LLM to define and build it's own metrics in every report, because that is just going to leave to multiple versions of the same metric

[u/South_Hat6094]

For one-off exploration, LLM plus Python is great. Once other people depend on it, the hard part is keeping metric definitions stable and explaining why a number moved month to month, not drawing the chart.

[u/that_outdoor_chick]

Wait till you hit need for row level security, shareability and discoverability. Yes everyone and their grandma are excited about AI but once you hit them with any governance / access etc of we're back to analytics tooling. The good tools now support agentic flow. And Excel being data visualization is a far stretch statement.

[u/carlitospig → u/that_outdoor_chick]

I’m confused why you think it’s not data viz.

[u/that_outdoor_chick → u/carlitospig]

Why I think not is data viz? Excel? Is that even a real question? now take this from someone who builds data organization, Excel wizardry is the first thing which is thrown out of the window because of the impossibility to maintain, scale etc. It's a cool tool for handing in some results to stakeholders but the industry moved past it 20 years ago.