Submission declined on 28 March 2024 by
BuySomeApples (
talk). This submission's references do not show that the subject
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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: Declined by
Shewasafairy 4 months ago.
| ![]() |
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.
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, in the format of a pandas dataframe, a number, a string or a chart.
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], matplotlib, seaborn and plotly for data visualization [5] [6].
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 [7].
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 [8] [9] [10].
In Q1 2024, the company has taken part of the Y Combinator W24 batch [11].
{{
cite book}}
: CS1 maint: date and year (
link)
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.
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
| ![]() |
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: Declined by
Shewasafairy 4 months ago.
| ![]() |
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.
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, in the format of a pandas dataframe, a number, a string or a chart.
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], matplotlib, seaborn and plotly for data visualization [5] [6].
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 [7].
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 [8] [9] [10].
In Q1 2024, the company has taken part of the Y Combinator W24 batch [11].
{{
cite book}}
: CS1 maint: date and year (
link)