Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
| Date | Stars |
|---|---|
| 2026-07-31 | 23673 |
| 2026-08-01 | 23673 |
| 2026-08-06 | 23710 |
Today
+37 stars today
This week
— stars this week
This month
— stars this month
Momentum
28.0
growth rate 0.00%/day
# 
[](https://pypi.org/project/pandasai/)
[](https://github.com/sinaptik-ai/pandas-ai/actions/workflows/ci-core.yml/badge.svg)
[](https://github.com/sinaptik-ai/pandas-ai/actions/workflows/cd.yml/badge.svg)
[](https://codecov.io/gh/sinaptik-ai/pandas-ai)
[](https://discord.gg/KYKj9F2FRH)
[](https://pepy.tech/project/pandasai) [](https://opensource.org/licenses/MIT)
[](https://colab.research.google.com/drive/1ZnO-njhL7TBOYPZaqvMvGtsjckZKrv2E?usp=sharing)
PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps non-technical users to interact with their data in a more natural way, and it helps technical users to save time, and effort when working with data.
# 🔧 Getting started
You can find the full documentation for PandasAI [here](https://docs.pandas-ai.com/).
## 📚 Using the library
### Python Requirements
Python version `3.8+ <=3.11`
### 📦 Installation
You can install the PandasAI library using pip or poetry.
With pip:
```bash
pip install pandasai
pip install pandasai-litellm
```
With poetry:
```bash
poetry add pandasai
poetry add pandasai-litellm
```
### 💻 Usage
#### Ask questions
```python
import pandasai as pai
from pandasai_litellm.litellm import LiteLLM
# Initialize LiteLLM with your OpenAI model
llm = LiteLLM(model="gpt-4.1-mini", api_key="YOUR_OPENAI_API_KEY")
# Configure PandasAI to use this LLM
pai.config.set({
"llm": llm
})
# Load your data
df = pai.read_csv("data/companies.csv")
response = df.chat("What is the average revenue by region?")
print(response)
```
---
Or you can ask more complex questions:
```python
df.chat(
"What is the total sales for the top 3 countries by sales?"
)
```
```
The total sales for the top 3 countries by sales is 16500.
```
#### Visualize charts
You can also ask PandasAI to generate charts for you:
```python
df.chat(
"Plot the histogram of countries showing for each one the gdp. Use different colors for each bar",
)
```
#### Multiple DataFrames
You can also pass in multiple dataframes to PandasAI and ask questions relating them.
```python
import pandasai as pai
from pandasai_litellm.litellm import LiteLLM
# Initialize LiteLLM with your OpenAI model
llm = LiteLLM(model="gpt-4.1-mini", api_key="YOUR_OPENAI_API_KEY")
# Configure PandasAI to use this LLM
pai.config.set({
"llm": llm
})
employees_data = {
'EmployeeID': [1, 2, 3, 4, 5],
'Name': ['John', 'Emma', 'Liam', 'Olivia', 'William'],
'Department': ['HR', 'Sales', 'IT', 'Marketing', 'Finance']
}
salaries_data = {
'EmployeeID': [1, 2, 3, 4, 5],
'Salary': [5000, 6000, 4500, 7000, 5500]
}
employees_df = pai.DataFrame(employees_data)
salaries_df = pai.DataFrame(salaries_data)
pai.chat("Who gets paid the most?", employees_df, salaries_df)
```
```
Olivia gets paid the most.
```
#### Docker Sandbox
You can run PandasAI in a Docker sandbox, providing a secure, isolated environment to execute code safely and mitigate the risk of malicious attacks.
##### Python Requirements
```bash
pip install "pandasai-docker"
```
##### Usage
```python
import pandasai as pai
from pandasai_docker import DockerSandbox
from pandasai_litellm.litellm import LiteLLM
# Initialize LiteLLM with your OpenAI model
llm = LiteLLM(model="gpt-4.1-mini", api_key="YOUR_OPENExcerpt of 5,701 characters
Read on GitHub
724
Arslan Saleem · Sinaptik GMBH · Germany
277
Raoul Scalise
50
Massimiliano Pronesti · IBM Research · Ireland
47
Ihor
34
27
17
14
13
13
11
10
Lorenzo Battistela · Brazil
9
6
5
5
Han
4
Avelino · @buserbrasil · Brazil
4
4
4
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ea457df9dd7f43d4, topic:llm