Python library that adds natural-language querying to pandas dataframes
Pandas AI is an open-source Python library that sits on top of pandas and lets you ask questions about a dataframe in plain language. It sends a description of the data and the question to a language model, receives generated code, runs it locally and returns the result, which keeps the actual computation on your machine. Beyond single answers, it supports multi-turn conversations, plotting, and combining several dataframes into one semantic layer so questions can span tables. It supports multiple model providers and local models. It is a developer library rather than a product, so results depend on your data descriptions and the model you configure.
Last updated: 2026-09-20. This site only provides an index; for exact features, pricing, and licensing, see the official website.
developer workflows, dataframe exploration, notebook analysis and report automation
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By default the library sends a schema summary and your question, not the full dataset, and the generated code runs locally. Exact behaviour depends on configuration, so review what is transmitted before pointing it at sensitive data.
Reliability follows the model and the clarity of your column names. Straightforward aggregations and filters usually work well; anything relying on undocumented business rules should be checked by reading the generated code.
For repeated production transformations, hand-written code is clearer, testable and faster. The library earns its place during exploration, when the question changes every few minutes and writing code each time is the bottleneck.
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