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AI Data Analyst Chatbot

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What AI Data Analyst Chatbot is

AI Data Analyst Chatbot is a self-hosted web app for exploring structured datasets through questions in plain English. Upload a CSV or XLSX file to get automated profiling of columns, distributions, summary statistics, missing values, duplicates, and data quality issues. The chatbot can surface variation, outliers, correlations, and patterns, and suggest statistical tests. It pairs statistical insights with interactive visualizations and explanations, so analysts can examine data without SQL or extensive coding knowledge. Uploaded data is processed during the session and is not permanently stored. The project lists Streamlit, pandas, NumPy, SciPy, Plotly, LangChain, and Groq LLM (LLaMA 3.1) among its technologies. To run it, install the dependencies and launch it with Streamlit; the app is then available at localhost:8501. A Groq API key must be set in the GROQ_API_KEY environment variable. The software is free and open source under the MIT License. The project invites contributions through forks, pull requests, and issues.

Who it suits

It suits analysts and data practitioners who want to explore CSV or XLSX datasets through natural-language questions and visualizations. Running it requires setting up the app and providing a Groq API key.

What it does well

  • Accepts CSV and XLSX files.
  • Profiles missing values, duplicates, and data quality.
  • Surfaces outliers, correlations, and patterns.
  • Uploaded data is not permanently stored.
  • Free and MIT-licensed.

What to know first

  • Requires a Groq API key.
  • No SQL connections.
  • No team collaboration.

Plans

PlanBilled and limitsPrice
Open-source softwareMIT-licensed · CSV and XLSX input · Requires a Groq API keyFree

As github.com lists them, read 8 Oct 2026. The maker's own page has the final word.

Getting started

  1. Open the project website on GitHub.
  2. Install the listed project dependencies.
  3. Set a Groq API key as the GROQ_API_KEY environment variable.
  4. Launch the app with Streamlit.
  5. Open the app at localhost:8501 and upload a CSV or XLSX file.

Verdict

AI Data Analyst Chatbot offers dataset profiling, statistical insights, and interactive visualizations through plain-English questions. It is a free, self-hosted option for users comfortable launching a Streamlit app and configuring a Groq API key.

Questions

How much does AI Data Analyst Chatbot cost?

The Open-source software plan is free. It is MIT-licensed.

What file types can I use?

It supports uploaded CSV and Excel (XLSX) files.

Does it connect to SQL databases?

No. SQL connections are not supported.

Where can I run it?

It is self-hosted and web-based. The README describes launching it with Streamlit and opening it at localhost:8501.

Does it require an API key?

Yes. Running the app requires a Groq API key set as the GROQ_API_KEY environment variable.

Who makes the project?

The GitHub profile identifies Priyansh Khandelwal as the maker.

Facts from AI Data Analyst Chatbot's own pages

Data handling
Uploaded data is processed in-session and is not permanently stored. · github.com, 8 Oct 2026
Data inputs
It supports uploaded CSV and Excel (XLSX) files. · github.com, 8 Oct 2026
Data profiling
The project describes automated profiling for columns, distributions, summary statistics, missing values, duplicates, and data quality issues. · github.com, 8 Oct 2026
Deployment
The README instructs users to install dependencies and launch the app with Streamlit, which makes it available at localhost:8501. · github.com, 8 Oct 2026
Integration requirement
Running the app requires a Groq API key set as the GROQ_API_KEY environment variable. · github.com, 8 Oct 2026
License
The repository provides the software under the MIT License. · github.com, 8 Oct 2026
Maker
The GitHub profile identifies the maker as Priyansh Khandelwal and says he is pursuing a Master’s in Computer Science at the University of Sydney. · github.com, 8 Oct 2026
Natural language interface
Users can ask questions in plain English without requiring SQL or extensive coding knowledge. · github.com, 8 Oct 2026
Statistical analysis
It can surface variation, outliers, correlations, patterns, and recommendations for statistical tests. · github.com, 8 Oct 2026
Support and contributions
The README invites users to contribute through forks, pull requests, or issues for enhancements and bug fixes. · github.com, 8 Oct 2026
Technology
The project lists Streamlit, pandas, NumPy, SciPy, Plotly, LangChain, and Groq LLM (LLaMA 3.1) among its technologies. · github.com, 8 Oct 2026
Visualizations
The chatbot provides interactive visualizations and explanations alongside statistical insights. · github.com, 8 Oct 2026
What it does
The chatbot lets users explore, analyze, and understand structured datasets by asking questions in natural language. · github.com, 8 Oct 2026
Who it is for
The project describes itself as built for analysts and data practitioners. · github.com, 8 Oct 2026

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