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langchain/docs
Rohan Dey 41a4c06a94
Added support for a Pandas DataFrame OutputParser (#13257)
**Description:**

Added support for a Pandas DataFrame OutputParser with format
instructions, along with unit tests and a demo notebook. Namely, we've
added the ability to request data from a DataFrame, have the LLM parse
the request, and then use that request to retrieve a well-formatted
response.

Within LangChain, it seamlessly integrates with language models like
OpenAI's `text-davinci-003`, facilitating streamlined interaction using
the format instructions (just like the other output parsers).

This parser structures its requests as
`<operation/column/row>[<optional_array_params>]`. The instructions
detail permissible operations, valid columns, and array formats,
ensuring clarity and adherence to the required format.

For example:

- When the LLM receives the input: "Retrieve the mean of `num_legs` from
rows 1 to 3."
- The provided format instructions guide the LLM to structure the
request as: "mean:num_legs[1..3]".

The parser processes this formatted request, leveraging the LLM's
understanding to extract the mean of `num_legs` from rows 1 to 3 within
the Pandas DataFrame.

This integration allows users to communicate requests naturally, with
the LLM transforming these instructions into structured commands
understood by the `PandasDataFrameOutputParser`. The format instructions
act as a bridge between natural language queries and precise DataFrame
operations, optimizing communication and data retrieval.

**Issue:**

- https://github.com/langchain-ai/langchain/issues/11532

**Dependencies:**

No additional dependencies :)

**Tag maintainer:**

@baskaryan 

**Twitter handle:**

No need. :)

---------

Co-authored-by: Wasee Alam <waseealam@protonmail.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
10 months ago
..
api_reference DOCS: core editable dep api refs (#13747) 10 months ago
docs Added support for a Pandas DataFrame OutputParser (#13257) 10 months ago
scripts DOCS: format notebooks (#13371) 10 months ago
src add cookbook table (#12043) 11 months ago
static docs[patch]: update stack diagram (#13902) 10 months ago
.local_build.sh Harrison/docs smith serve (#12898) 11 months ago
README.md Fix typos (#11663) 11 months ago
babel.config.js Restructure docs (#11620) 11 months ago
code-block-loader.js Restructure docs (#11620) 11 months ago
docusaurus.config.js docs[patch]: link to LangSmith docs (#13740) 10 months ago
package-lock.json Upgrade docs postcss (#13031) 11 months ago
package.json Restructure docs (#11620) 11 months ago
settings.ini Restructure docs (#11620) 11 months ago
sidebars.js DOCS: move `adapters` to integrations (#13862) 10 months ago
vercel.json renamed `google_vertex_ai_vector_search` notebook (#13484) 10 months ago
vercel_build.sh template readme's in docs (#13152) 10 months ago
vercel_requirements.txt docs[patch]: install local core (#13990) 10 months ago

README.md

Website

This website is built using Docusaurus 2, a modern static website generator.

Installation

$ yarn

Local Development

$ yarn start

This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server.

Build

$ yarn build

This command generates static content into the build directory and can be served using any static contents hosting service.

Deployment

Using SSH:

$ USE_SSH=true yarn deploy

Not using SSH:

$ GIT_USER=<Your GitHub username> yarn deploy

If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the gh-pages branch.

Continuous Integration

Some common defaults for linting/formatting have been set for you. If you integrate your project with an open-source Continuous Integration system (e.g. Travis CI, CircleCI), you may check for issues using the following command.

$ yarn ci