Draft:PandasAI
| Submission declined on 28 March 2024 by BuySomeApples (talk). This submission's references do not show that the subject qualifies for a Wikipedia article—that is, they do not show significant coverage (not just passing mentions) about the subject in published, reliable, secondary sources that are independent of the subject (see the guidelines on the notability of websites). Before any resubmission, additional references meeting these criteria should be added (see technical help and learn about mistakes to avoid when addressing this issue). If no additional references exist, the subject is not suitable for Wikipedia.
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| Submission declined on 10 March 2024 by Shewasafairy (talk). This draft's references do not show that the subject qualifies for a Wikipedia article. In summary, the draft needs multiple published sources that are:
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Comment: see WP:MEDIUM, WP:CRUNCHBASE, WP:ROUTINE. She was afairy 05:54, 10 March 2024 (UTC)
| Developer(s) | Gabriele Venturi, Massimiliano Pronesti, Arslan Saleem |
|---|---|
| Initial release | April 2023 |
| Stable release | v2.0
/ March 2024 |
| Repository | github.com/Sinaptik-ai/pandas-ai |
| Written in | Python and JavaScript |
| Type | library for conversational data analysis |
| License | MIT License |
| Website | pandas-ai.com |
PandasAI is an open-source Python library that enhances the functionality of the popular pandas library by integrating it with Large Language Models (LLMs). This approach allows users to interact with data frames through natural language.[1], making data analysis more accessible and efficient[2]. PandasAI is distributed under MIT license.
How it works[edit]
PandasAI provides a natural language semantic layer that uses large language models (LLMs) to convert the user query into pandas and SQL code[3]. The code is then executed and the output of the analysis is returned to the user.
PandasAI is not limited to the pandas library, but it can use the whole ecosystem, including libraries like NumPy for computantion-heavy calculation, scikit-learn for basic ML tasks[4] and matplotlib, seaborn and plotly for data visualization[5].
History[edit]
PandasAI was launched on April 2023 as an open source project by Gabriele Venturi. It immediately earned traction, reaching the milestone of 5.000 stars on GitHub in approximately 2 weeks[6].
The company, based in Munich, after incorporating in May 2023 announced a $1.1M pre-seed round from Runa Capital, Episode 1 and Exor Ventures in September 2023[7][8][9]
References[edit]
- ^ "Pandas AI: Supercharging data analysis with generative AI". DEV Community. 2023-06-18. Retrieved 2024-03-10.
- ^ "Pandas AI: The Generative AI Python Library". GeeksforGeeks. 2023-06-08. Retrieved 2024-03-10.
- ^ "Pandas AI: The Generative AI Python Library". KDnuggets. Retrieved 2024-03-10.
- ^ "Official documentation". docs.pandas-ai.com. Retrieved 2024-03-11.
- ^ Muskan, Vivek (2023-07-01). "How to leverage AI for Data Visualization using pandas?". Medium. Retrieved 2024-03-10.
- ^ "GitHub Star History". star-history.com. Retrieved 2024-03-10.
- ^ "PandasAI raises $1.1M in Pre-Seed round for AI-powered data analysis". Tech.eu. 2023-09-29. Retrieved 2024-03-10.
- ^ Escárzaga, Antonio L. (2023-09-29). "Munich-based PandasAI raises over €1 million for its AI-powered data analysis assistant". EU-Startups. Retrieved 2024-03-10.
- ^ "Why 'AI copilot' startups are so hot with VCs right now". Fortune. Retrieved 2024-03-11.