imnotdev25 / pandas-ai

Pandas AI is a Python library that integrates generative artificial intelligence capabilities into Pandas, allowing for advanced data analysis tasks such as data synthesis and augmentation.

PandasAI 🐼

Pandas AI is a Python library that adds generative artificial intelligence capabilities to Pandas, the popular data analysis and manipulation tool. It is designed to be used in conjunction with Pandas, and is not a replacement for it.

Installation

pip install pandasai

Usage

PandasAI is designed to be used in conjunction with Pandas. It makes Pandas conversational, allowing you to ask questions about your data and get answers back, in the form of Pandas DataFrames. For example, you can ask PandasAI to find all the rows in a DataFrame where the value of a column is greater than 5, and it will return a DataFrame containing only those rows:

import pandas as pd
from pandas_ai import PandasAI

# Sample DataFrame
df = pd.DataFrame({
    "country": ["United States", "United Kingdom", "France", "Germany", "Italy", "Spain", "Canada", "Australia", "Japan", "China"],
    "gdp": [21400000, 2940000, 2830000, 3870000, 2160000, 1350000, 1780000, 1320000, 516000, 14000000],
    "happiness_index": [7.3, 7.2, 6.5, 7.0, 6.0, 6.3, 7.3, 7.3, 5.9, 5.0]
})

# Instantiate a LLM
from llm.openai import OpenAI
llm = OpenAI()

pandas_ai = PandasAI(df, llm)
pandas_ai.run('Which are the 5 happiest countries?')

The above code will return the following:

0     United States
6            Canada
7         Australia
1    United Kingdom
3           Germany
Name: country, dtype: object

Of course, you can also ask PandasAI to perform more complex queries. For example, you can ask PandasAI to find the sum of the GDPs of the 2 unhappiest countries:

pandas_ai.run('What is the sum of the GDPs of the 2 unhappiest countries?')

The above code will return the following:

14516000

You can find more examples in the examples directory.

Environment Variables

In order to set the API key for the LLM (HuggingFaceHub, OpenAI), you need to set the appropriate environment variables. You can do this by copying the .env.example file to .env:

cp .env.example .env

Then, edit the .env file and set the appropriate values.

As an alternative, you can also pass the environment variables directly to the constructor of the LLM:

# OpenAI
llm = OpenAI(api_token="YOUR_OPENAI_API_KEY")

# OpenAssistant
llm = OpenAssistant(api_token="YOUR_HF_API_KEY")

License

PandasAI is licensed under the MIT License. See the LICENSE file for more details.

Contributing

Contributions are welcome! Please check out the todos below, and feel free to open a pull request.

Todo

• Add support for more LLMs
• Make PandasAI available from a CLI
• Create a web interface for PandasAI
• Add CI/CD
• Add support for conversational responses