PandasAI - new Python library for pandas | LLM | Turtles AI
PandasAI - new Python library for pandas
DukeRem
New #Python #library #PandasAI uses #AI to enable natural #language #queries on #pandas #data. Allows #conversational data #analysis without #coding through large language models (LLM) like #OpenAI's #ChatGPT.
A new Python library called PandasAI aims to add generative AI capabilities to pandas, the popular data analysis and manipulation tool, according to a recent announcement.
Designed to be used in conjunction with pandas rather than replace it, PandasAI makes pandas conversational by enabling users to query data in plain English. For instance, it can find rows where values meet certain criteria or calculate metrics based on verbal instructions.
The library leverages large language models such as OpenAI to generate Python code from natural language prompts. It only sends limited randomized sample data to preserve privacy and security.
PandasAI also offers shortcuts for common queries like data cleaning, missing value imputation, feature generation, and plotting. Users can access these via a command line interface tool called Pai.
Overall, PandasAI brings the power of AI assistants to one of Python's most ubiquitous libraries. It has the potential to make data exploration and analysis more intuitive for a wide range of users. The project is open source and available on GitHub, by clicking here.
PandasAI is an exciting new open source project that could open up pandas and data science to a much wider audience. What are your thoughts on this conversational approach to data analysis? How do you think tools like this could impact and empower non-technical users? I'd love to hear perspectives on both the potential and limitations of using AI in this way. Please share your views below!
Highlights:
- Makes pandas conversational by allowing natural language queries
- Leverages large language models like OpenAI to generate Python code
- Enables data exploration without coding through AI assistant
- Provides shortcuts for common data tasks like cleaning and plotting
- Open source library available on GitHub