Charly Wargnier Profile picture
Dec 6, 2022 13 tweets 7 min read Read on X
Among all the cool things #ChatGPT can do, it is super capable of handling and manipulating data in bulk, making numerous data wrangling, scraping, and lookup tasks obsolete.

Let me show you a few cool tricks, no coding skills are required!

(A thread) 👇🧵
Let's start easy by heading to chat.openai.com/chat and pasting a list of 60 countries in the text field Image
Let's ask #ChatGPT to give us the main language, latitude, longitude, and country code for each of these countries Image
That was easy enough, right?

Now let's add more data to our output by asking #ChatGPT to provide the population of each of these countries Image
Uber cool! 😎

Let's ask ChatGPT to wrap these results in a table Image
Magic! ✨

Now we'll add an index to that table Image
Boom! 💥

No #Python, PowerBI or code was needed!

Now let's try something a bit harder by asking #ChatGPT to add crime rates and COVID death tolls for the year 2020 Image
No sweat!

... and it's not even limited to tabular data!

Let's ask #ChatGPT to convert our table to a JSON file Image
Pretty impressive, right?

Now say you want to store that data in a database (e.g. the excellent @detahq), but you're not sure how to do it.

You bet! We can ask #ChatGPT how to do that Image
Let's conclude this thread by asking #ChatGPT to create a @streamlit app with a CSV uploader and filter boxes to filter `longitude`, `latitude`, and `country code`.

Not only does #ChatGPT displays the code, but it also provides clear explanations for each step! 👏 Image
This is just a quick overview of what you can do with #ChatGPT.

I'm only scratching the surface here.

For more cool things you can do with it, check out my other thread

.
If you found this helpful, two requests:

1. Follow me @DataChaz to read more content like this.
2. Share it with an RT, so others can read it too! 🙌
Note that while #AI is capable of handling tasks such as sourcing and sorting, as well as some aspects of app development, it is not yet advanced enough to replace the need for human verification.

Even with its impressive capabilities, AI still requires human oversight.

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Charly Wargnier

Charly Wargnier Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @DataChaz

Feb 7
Anthropic quietly dropped 9 new Free Claude Skills tutorials 💥

Covering Projects, Excel workflows, browsing in Chrome, file editing, app integrations, task automation, and more!

Zero tech background required, so anyone can learn practical AI free and fast. 🧵↓ Image
1/ First things first, did you know you can create and edit files directly with Claude?

Draft documents, iterate on content, and keep everything in one place.
claude.com/resources/tuto…Image
2/ Claude can also assist you while you browse in Chrome.

Summaries, explanations, and quick insights as you move across pages.
claude.com/resources/tuto…Image
Read 11 tweets
Jan 27
folks on X: "Clawdbot is an overnight success"

@steipete’s GitHub profile: Image
When you look at @steipete's previous projects, Clawdbot (now @moltbot btw!) is basically a wrapper that ties all of them together.

It finally clicks.

Everything finally came together.
@steipete @moltbot Screenshot courtesy of my friend @Saboo_Shubham on LinkedIn, as I couldn’t find that GitHub repo myself :)
Read 6 tweets
Jan 25
ClawdBot is blowing up on X.

Everyone’s sharing great experiments, automations, even jokes!

I pulled together the 15 most interesting posts right now 🧵↓ Image
1/

Deploy ClawdBot in less than 5 minutes for $0!

The AWS Free Tier setup everyone’s retweeting.

by @techfrenAJ

2/

The full walkthrough: 27 minutes that explains what it is, setup, and why it’s scary-effective.

by @AlexFinn

Read 18 tweets
Jan 21
NVIDIA just removed one of the biggest friction points in Voice AI.

PersonaPlex-7B is an open-source, full-duplex conversational model.

Free, open source (MIT), with open model weights on @huggingface 🤗

Links to repo and weights in 🧵↓

The traditional ASR → LLM → TTS pipeline forces rigid turn-taking.
It’s efficient, but it never feels natural.

PersonaPlex-7B changes that.

This @nvidia model can listen and speak at the same time.

It runs directly on continuous audio tokens with a dual-stream transformer, generating text and audio in parallel instead of passing control between components.

That unlocks:
→ instant back-channel responses
→ interruptions that feel human
→ real conversational rhythm

Persona control is fully zero-shot!

If you’re building low-latency assistants or support agents, this is a big step forward 🔥
1/ Link to the repo:
github.com/NVIDIA/persona…
2/ The model weights are available on @huggingface here:
huggingface.co/nvidia/persona…
Read 5 tweets
Jan 12
Wow, such a great open-source drop!

Put Claude on steroids with 120+ scientific skills spanning maths, biology, chemistry, medicine, engineering, & more 🤯

If you’ve ever wanted Claude to act like a research assistant, this gets very close.

Free and open source.

Repo in 🧵↓ Image
Here is the link to the repo:
github.com/K-Dense-AI/cla…Image
♻️ If this sparked an idea, hit repost so others can catch it too!

Follow me → @datachaz for daily drops on LLMs, agents, and data workflows! 🦾
Read 4 tweets
Dec 29, 2025
MIT and Oxford released their $2,500 agentic AI curriculum on GitHub at no cost.

15,000 people already paid for it.

Now it's on GitHub!

It covers patterns, orchestration, memory, coordination, and deployment.
A strong roadmap to production ready systems.

Repo in 🧵 ↓ Image
10 chapters:

Part 1. What agents are and how they differ from plain generative AI.
Part 2. The four agent types and when to use each.
Part 3. How tools work and how to build them.
Part 4. RAG vs agentic RAG and key patterns.
Part 5. What MCP is and why it matters.
Part 6. How agents plan with reasoning models.
Part 7. Memory systems and architecture choices.
Part 8. Multi agent coordination and scaling.
Part 9. Real world production case studies.
Part 10. Industry trends and what is coming next.
Here's the repo:
github.com/aishwaryanr/aw…Image
Read 4 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(