pandasai 2.2.15

Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysi

08-01-2023 261 words 2 minutes 0 views

Contents

Chat with your database (SQL, CSV, pandas, polars, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

12886 Stars :star:

Stars: 12886, Watchers: 12886, Forks: 1247, Open Issues: 105

The Sinaptik-AI/pandas-ai repo was created 1 years ago and the last code push was 2 weeks ago.
The project is extremely popular with a mindblowing 12886 github stars!

How to Install pandasai

You can install pandasai using pip

pip install pandasai

or add it to a project with poetry

poetry add pandasai

Package Details

Author: Gabriele Venturi
License: MIT
Homepage: None
PyPi:: https://pypi.org/project/pandasai/
GitHub Repo:: https://github.com/gventuri/pandas-ai

Classifiers

No pandasai pypi packages just yet.

Errors

A list of common pandasai errors.

Code Examples

Here are some pandasai code examples and snippets.

GitHub Issues

The pandasai package has 105 open issues on GitHub

Support Llama v2 and Text generation inference
Try to import a package when NameError is raised during execution
Token Limits with 420 column and 119546 rows
Clean_data and Impute_missing_values not working as expected
Add support for Azure, OpenAI, Palm, Anthropic, Cohere Models - using litellm
Plotted graph has overlapping labels
Added Poe-api as LLM reference
Database adapters
fix: environment for executing code
Raise "TypeError" when trying to save cache
Semantic search for previously asked questions
Arbitrary file read and arbitrary file write by prompt injection
hello, why did the code like "df = df[df['content'].str.contains('xxxx')] " didn't work?
The fix of #issue399 (RCE from prompt) can be bypassed.
Can pandasai specific the vector db location ?

See more issues on GitHub

Related Packages & Articles

deeplake 3.9.26

Deep Lake is a Database for AI powered by a unique storage format optimized for deep-learning and Large Language Model (LLM) based applications. It simplifies the deployment of enterprise-grade LLM-based products by offering storage for all data types (embeddings, audio, text, videos, images, pdfs, annotations, etc.), querying and vector search, data streaming while training models at scale, data versioning and lineage for all workloads, and integrations with popular tools such as LangChain, LlamaIndex, Weights & Biases, and many more.

pyoptimus 23.5.0b0

PyOptimus is a Python library that brings together the power of various data processing engines like Pandas, Dask, cuDF, Dask-cuDF, Vaex, and PySpark under a single, easy-to-use API. It offers over 100 functions for data cleaning and processing, including handling strings, processing dates, URLs, and emails. PyOptimus also provides out-of-the-box functions for data exploration and quality fixing. One of the key features of PyOptimus is its ability to handle large datasets efficiently, allowing you to use the same code to process data on your laptop or on a remote cluster of GPUs.